# Science DAO*

> Science DAO supports transparent funding for science and open-source software. AIIM payment transactions are recorded on-chain; the current beta initiates payments off-chain through Node.js.


## Posts

- [Key Contributors to World Science DAO in 2026](https://science-dao.org/key-contributors/): Key contributors to World Science DAO, with links to public profiles, publications, software repositories, and source documents that readers can use to verify research and project credentials.
- [Projects Completed in 2026](https://science-dao.org/projects-completed/): The following are DeSci-related projects completed by our team: Automatic transformation of XML namespaces This research project Automatic transformation of XML namespaces in applied computer science aims to write a specification for software which automatically transforms XML documents from some namespaces to some other namespaces, for this using RDF resources (describing namespaces and transformations) possibly located at namespace URLs. Additionally it aims to validate XML documents consisting of multiple namespaces. Projects Completed The fore-mentioned formal specification is fully complete (however, it still can be made better). XML Boiler XML Boiler is a software that mostly implements (with validation of mixed-namespace XML […]
- [Screwed Science Monopolies (Jerk In Control) in 2026](https://science-dao.org/science-monopolies-2/): A humorous description of the present dystopia of how monopolies work in science: Yes, not even a salary for my personal needs, not speaking about money to actually build roads! This is exactly what happened with my discovery of ordered semigroup actions (and related discoveries). This tweet is what really happens in science (if we replace roads by a fundamental scientific discovery). Therefore, as this big scientific covery with ordered semigroup actions happened: See also 👉 a longer and serious article on this topic.
- [Empower Open Science This Giving Tuesday in 2026](https://science-dao.org/empower-open-science/): How you can effective help to open science: an open, auditable, and responsive model of science as a common good: A Global Call to Fund Independent Research and Innovation Why Giving Tuesday Matters for Science Giving Tuesday is a global movement of generosity — and a powerful moment to support systems that create lasting impact. While most donations go to short-term causes, science funding multiplies its effects across generations. Every dollar invested in open research strengthens the foundation of human knowledge, accelerates innovation, and supports those who are building the future. When you donate to Science DAO, you’re not just giving […]
- [About Us in 2026](https://science-dao.org/about-us/): World Science DAO develops open, blockchain- and AI-assisted approaches to funding science and open-source software. Learn about AIIM, Grants Science, XML Boiler, project governance, contributors, and current status.
- [Why China May Empower the Next Global Transformation: AI Internet-Meritocracy in 2026](https://science-dao.org/why-china-may-empower/): It seems that USA fails to lead in global R&D financing. The next leader may be China. The Ancient Symbol and Modern Meaning Why It Makes Sense for China China already stands as a scientific and technological powerhouse, producing a major share of global research and patents. Supporting AI Internet-Meritocracy — a blockchain-based system that automates funding for science and innovation — aligns perfectly with China’s long-term vision: In short, AIIM could become the new Silk Road of knowledge, where China exports participation in a shared global economy of discovery. The United States: A Passive Giant Across the Pacific, the United […]
- [If This Blog Is Right, Then Everybody Is a Psycho in 2026](https://science-dao.org/everybody-is-a-psycho/): The global R&D finance system is a collective psychosis. It is counter-productive and needs to be replaced by our solution for financing R&D. Wondered? Society’s Rational Illusion We believe modern institutions are rational—universities, grant agencies, philanthropies. But the evidence says otherwise. When inefficiency, bias, and apathy become routine, irrationality becomes the new normal. Modern society functions like a coordinated psychosis: collectively certain we’re sane. A Psychiatric Rediscovery Psychiatrists already know that stress, cognitive dissonance, and delusion are epidemic. The blog simply extends that idea to the collective level:our global civilization behaves like a patient unaware of its condition. We hoard wealth […]
- [When the Laws of Market Break in 2026](https://science-dao.org/market-break/): When the laws of market break, stop financing the old paradigm entirely and put all money on the new project. Don’t finance the new project as a part of old system, but finance it directly. Donate to AI Internet-Meritocracy – the next system change of the world economy. 🌍 Call to Action: Support the Future of Fair Funding Help build the system that replaces the old market economy with something better — smarter, fairer, and global, while supporting trade and entrepreneurial spirit.Donate to AI Internet-Meritocracy
- [AI Internet-Meritocracy Is a Cost-Effective Way To Allocate Science Money in 2026](https://science-dao.org/cost-effective/): Universities, R&D agencies, and other R&D institutions have high financing overhead, whilst AI Internet-Meritocracy is a very cost-effective way of giving money directly to researchers and free software developers. Refuse to offer money to gate-keeping institutions, give it to the science workers dfirectly. A New Paradigm for Funding Research How AI Internet-Meritocracy Works AI Internet-Meritocracy combines three elements: This approach creates a self-optimizing ecosystem — rewarding work that truly advances science and cutting support for projects that fail to deliver measurable progress. Why It’s Cost-Effective The current system spends billions on bureaucracy. Peer review panels, grant writers, and funding agencies consume […]
- [The Hidden Catastrophe: How Apathy Toward Mathematical Research Has Cost the World Trillions in 2026](https://science-dao.org/mathematical-research/): Apathy is the new Hitler, something that takes trillions of dollars and millions of lives away. So, it happened with an ignored math breakthrough discovery – ordered semigroup actions. Few people realize that the global economy’s sluggishness and Mathematical Research humanity’s preventable suffering are tied not only to politics or technology—but to indifference (especially in the light of the tragic story of the author). Specifically, to the indifference toward groundbreaking mathematical discoveries like Ordered Semigroup Actions (OSA) that could have transformed science, economics, and technology long ago. The Cost of Indifference / Mathematical Research Mathematics is the invisible infrastructure of progress. […]
- [Revisiting Marxist Socialism in the Era of AI and Digital Economies in 2026](https://science-dao.org/digital-economies/): What in classical Marxism remains correct and what fails in the digital R&D economy. In the 21st century, Digital Economies and especially in 2025, the global economy operates within a reality that Karl Marx could not have fully foreseen: the rise of artificial intelligence, blockchain technology, and programmable digital currencies. These developments invite us not to reject classical Marxism, but to reinterpret and update its framework in light of new economic mechanisms, providing collective ownership of IP rights and eliminating exploitation of Internet occupations. All this is without losing private property rights and the entrepreneurial spirit – the core values of […]
- [Demand to Fire the Science Minister of Your Government in 2026](https://science-dao.org/science-minister/): Every science ministry in the world failed to attain talent not ignoring some parts of the science. Need structural change in every government of the world. Because “coveries” happen when good science is ignored, not when it is “too novel” What are coveries? Coveries happen when: In short, coveries are not about the content of the discovery.They’re about a broken system of scientific communication and promotion. 👉 More on the concept of coveries: Scientific Coveries and Why We Need a New Occupation — Science Marketers Why your Science Minister must go They allow systemic neglect of outsiders Funding covers research, but […]
- [The Personal Story Behind AI Internet-Meritocracy Project](https://science-dao.org/personal-story/): Jesus, usually talking about forgiveness, basically said “Don’t forget. Don’t forgive.” about almost starving to death one of the best mathematicians, when he was a young student. I am Victor Porton, the creator of this site and of World Science DAO. Personal Story. Story: I converted into the Baptist variant of Christian faith 8 Aug 1995, when I was 15 year old. Since that day, the relatives started to shout at me “sectarian” (so, in Russia are called despised and hated for being small smaller religious groups) and bully me increasingly. I have no idea, how they determined the day of […]
- [How Could DeSci DAOs Multiply Global GDP in 2026?](https://science-dao.org/multiply-gdp/): The global economy Could Multiply is driven by innovation, yet the way we fund and organize science remains rooted in structures from the 20th century. Scientific research is currently underfunded, bureaucratic, and inefficient, which slows down technological progress and economic growth. A new model is emerging that could change everything: Science DAOs — decentralized autonomous organizations designed to coordinate and fund science at scale. What Is a Science DAO? A Science DAO is a decentralized organization that uses blockchain technology and smart contracts to fund, govern, and reward scientific research. Unlike traditional institutions, Science DAOs can: Science DAOs are a natural […]
- [History of Scientific Funding — and the Next Great Leap in 2026](https://science-dao.org/scientific-funding/): How R&D funding changed over time and how it can be improved now, using Internet and AI technology, instead of traditional institutions, for distributing R&D funds. From Royal Patrons to National Science The Age of Competitive Grants After World War II, government funding for science expanded rapidly. Programs like those run by National Science Foundation in the U.S. or the European Research Council in the EU gave billions to researchers worldwide. This era enabled unprecedented scientific progress — from space exploration to modern medicine. But it also introduced bureaucratic gatekeeping. Only a small portion of applicants received grants, often favoring institutional […]
- [Classification of Monopolies in 2026](https://science-dao.org/classification/): What kinds of monopolies are there? What are their special kinds in science? Introduction In economics and across fields, the concept of a monopoly describes a situation in which one actor (a firm, individual, or collective) dominates access, supply or rights in a given market or domain. While commonly associated with business markets, the idea of monopolies extends beyond commerce to science, knowledge, publishing and intellectual spheres. This article sets out a detailed classification of monopolies, explores their causes and consequences, and introduces the notion of scientific monopolies as described by the World Science DAO (Science DAO). At the end, you are […]
- [Request for Funding – Support Science DAO's Vision through Crypto Donations in 2026](https://science-dao.org/crypto-donations/): Support a new kind of economy – World Science DAO by donating money, crypto, or shares. World Science DAO Warning on Crypto Donations: Due to an upstream software failure, World Science DAO has lost its DAO status (it to become a DAO again in the future). Instead, donations for World Science DAO are accepted by Victor Porton’s Foundation, a charity. Why We’re Asking How You Can Donate We gratefully accept contributions through: No matter which method you choose, your support goes directly toward building sustainable, open scientific infrastructure—not administrative overhead. Why We Accept Multiple Donation Methods While cryptocurrency enables fast, transparent, […]
- [How Peer Review Should (And Will) Work in the Future in 2026](https://science-dao.org/peer-review/): Peer Review Will Become Paid Work — Without Exploitation Personal Signed Reviews Replace Gatekeeping Traditionally, a scientist must submit a paper to Review a journal, endure months of waiting, and hope anonymous reviewers approve it. This outdated process is Review dominated by gatekeepers and profit-driven publishers. The new model is simple: No journals. No opaque decisions. Just peer-to-peer science with transparent credentials. From Complaints to Empowerment: Scientists Take Control How the New Peer Review Workflow Will Look Here’s how the typical workflow of a science marketer in the new system will operate: Although AI Internet-Meritocracy doesn’t yet directly support payments to […]
- [Can Machines Make Everyone Rich in 2026?](https://science-dao.org/machines/): DONATE
- [Main Global Problems of Mankind in 2026](https://science-dao.org/global/): Introduction Humanity has entered an era of great power — and great confusion.We can explore the stars, decode genomes, and train superhuman AI, yet we still struggle to solve our most basic global problems. These problems — environmental, economic, scientific, and moral — now define the future of civilization. The Environmental Crisis Economic Inequality and Resource Misallocation The Crisis of Knowledge: Scientific Coveries A covery is a legitimate discovery that: Coveries represent the invisible loss of human progress.They show that humanity doesn’t lack discoveries — it lacks visibility. Technological Dependence and AI Ethics Political Polarization and Information Warfare Moral and Spiritual […]
- [Scientific Visibility Is a Coordination Problem — An Experimental Approach](https://science-dao.org/solution/): Scientific Visibility Is a Coordination Problem — An Experimental Approach Important scientific and technical work can remain obscure because it is difficult to discover, difficult to evaluate, badly indexed, poorly presented, or disconnected from the people who could use it. Science DAO treats this as a coordination problem rather than claiming to have a unique or proven solution. Our working hypothesis We are testing whether a combination of AI-assisted evaluation, public evidence, transparent funding records, and better science communication can help useful work receive more attention and support. This is an experimental hypothesis. What AI can and cannot do AI can […]
- [Does Super-Human AI Solve the Problem of Scientific “Coveries” — and What We, Humans, Can Do in 2026?](https://science-dao.org/human-ai/): It is not confirmed that super-human AI can solve the problem of scientific “coveries” because this problem requires not only intelligence but also goodwill, that we need to take action. What is a covery — correctly defined A covery Human AI is not simply an unpublished result. A covery is a mis-published discovery: a legitimate, priority-worthy finding that was published or announced in a way that breaks the visibility and continuity of its topic. That mis-publication can take many forms — obscure metadata, wrong keywords, misleading title, poor indexing, fragmented reports, broken links, or publication inside an irrelevant venue — and […]
- [A Dialogue With Skeptics](https://science-dao.org/a-dialogue-with-skeptics/): In this Reddit thread, I discuss my app against skeptical-minded people.
- [The Best Sites to Donate At in 2026](https://science-dao.org/donate/): As philanthropy evolves alongside technology, 2025 stands out as a year when transparency, decentralization, and AI-driven decision-making are reshaping how we give. From traditional effective charities to blockchain-based scientific initiatives, today’s donors can make a global impact with just a few clicks. 💧 The Water Project A respected nonprofit bringing clean, safe water to communities in sub-Saharan Africa. Every donation supports specific wells and water systems, with full transparency through regular progress reports and local impact tracking. 🌱 GiveWell GiveWell is a leading evaluator of charities, known for its rigorous, evidence-based approach. It identifies where each donated dollar can save or […]
- [Internet Search Became Worse Than the Old Paper Library in 2026](https://science-dao.org/internet/): It looks like that in the age of Google systematization of scientific knowledge possibly became worse than in the age of paper libraries. Take action to overcome this problem. Since I was a university student in Russia. I used to spend hours in the dusty reading rooms of paper encyclopedias. It was not a glamorous process, but it worked. In one of those Russian-language encyclopedias, I found clear and concise descriptions of poset filters and proximity spaces. Those concepts inspired me to go further — and eventually, I discovered an entirely new branch of mathematics: the theory of funcoids. But after […]
- [Scientific Coveries and Why We Need a New Occupation — Science Marketers in 2026](https://science-dao.org/scientific/): A “scientific covery” is when a discovery permanently elides from public attention. Our app introduces new occupation – science marketers – to solve this awful problem. Introduction Every day, humanity makes new discoveries — yet many of them remain invisible. Some are never published. Others are discovered twice: once by an unknown amateur, and later by a professional who has the resources to announce it properly. What Is a Scientific Covery? A covery is a scientific discovery that: In other words, a covery is a hidden discovery — a result that exists, but not yet acknowledged by the scientific mainstream because […]
- [Why And How And with Which Purpose Was NSF Destroyed in 2025?](https://science-dao.org/purpose/): Today National Science Foundation collapsed with the following message on X: Everybody knows that the main actor who strove to close NSF was Elon Musk who was upset by low-quality research spending taxpayers’ money, woke and socialist agenda of universities. But probably I played a role in this. My Tweets I posted a series of tweets targeting Elon Mask and Donald Trump: So, probably I reached my purpose to propose to liquidate NSF to Ilon Musk. (I am not afraid to tell this, because once God said me that I won’t die. I will be taken to heaven like Enoch alive.) […]
- [AIIM Is an Automated Scientific Prize in 2026](https://science-dao.org/scientific-prize/): In an era of accelerating scientific innovation, traditional models of scientific prizes and grants are struggling: slow, opaque, biased, often favouring well-connected researchers. The AIIM (AI Internet-Meritocracy) proposed by World Science DAO offers a bold alternative: an automated scientific prize system that replaces or supplements both prizes and grants with a decentralized, algorithmic, blockchain-backed infrastructure. What is AIIM / AI Internet-Meritocracy AI Internet-Meritocracy, as proposed on Science-DAO.org, is an economic formation and funding mechanism for science and software that: In other words, AIIM is not merely another prize: it is a system designed to automatically recognize, reward, and fund scientific work […]
- [AI-Internet Meritocracy Project Proposal for Fintech AI Innovation Grants in 2025](https://science-dao.org/fintech-ai-innovation/): Project Description & Use Cases This project is an app that distributes donations proportionally to AI’s assessments of user’s worth as a portion of Fintech AI Innovation global GDP, determined by AI reading from the Web user’s creations such as scientific articles and free software. The user registers in the system and connects his/her accounts, such as GitHub and ORCID, and starts to receive weekly payouts. In the future I am also going to support creating a new occupation – science marketers, to offload marketing of scientific discoveries and free software to professional marketers. Use cases: salaries to scientists and FOSS […]
- [Blockchain for Good: A New Moral Infrastructure for Humanity in 2026](https://science-dao.org/blockchain-for-good/): Blockchain technologies make the intent: make it impossible not to follow the moral law by the rules of the technology itself. A Moral Technology in an Age of Distrust Human civilization has always searched for ways to make promises visible. Blockchain for Good Contracts, coins, and constitutions — all are attempts to bind words to actions. Yet history shows how easily words are broken and promises fade. In the 21st century, a new kind of trust has emerged not from human virtue but from mathematical integrity: the blockchain. But blockchain is not merely a financial tool. Properly understood, it is an […]
- [How to do crypto airdrops with AIIM in 2026?](https://science-dao.org/crypto-airdrops/): AIIM (AI Internet-Meritocracy) is a perfect platform for crypto airdrops: However, currently (27 Sep 2025) the app is not yet production quality, the wallet is custodial, and ERC-20 are not supported. Be sure to check us in the future, if you want to make an airdrop.
- [DAO Status](https://science-dao.org/dao-status/): The DAO software currently does not work, because of bugs in our upstream DAO software, Colony. Due to missing DAO status, donations are temporarily accepted by charity “Victor Porton’s Foundation”, instead. Don’t worry, all the donations go to the projects. Here is a recorded demo of the AI Internet-Meritocracy app:
- [Why Must Catholics Donate to Science in 2026?](https://science-dao.org/catholics/): Should Catholics support science directly through donations? In 2026, questions like this about the role of faith in a rapidly changing technological world have become pressing. This may not sound like a traditional form of charity, but Catholic theology and social teaching provide strong reasons why supporting scientific research—and especially new, more just funding models such as AI Internet-Meritocracy / Science DAO—is not only reasonable but a moral imperative. Stewardship of Creation Science as a Path to Truth The Common Good and the Preferential Option for the Poor Correcting Structural Injustice Technology and Ethical Responsibility Charity with Long-Term Impact Call to […]
- [Why Should Right-Wing (Free Market Proponents) Donate to Science in 2026?](https://science-dao.org/free-market-proponents/): Donating to decentralized science vibes well with free market ideas or entrepreneurial spirit and free, money-based development. Introduction From a cursory glance, Free Market Proponents the idea of “AI Internet-Meritocracy” or a “Science DAO distributing funds to scientists via AI” might seem alien—or even hostile—to free-market thinkers. After all, “socialism” is often used as a negative label, and a system that redistributes funds might seem at odds with merit, competition, and private incentives. But I will argue that supporting science (especially via decentralized, transparent, AI-oriented donation/distribution systems) can be consistent with, and even strengthen, free-market values in 2025. Not only that, […]
- [Why Should Left-Wing (Socialists) Donate to Science in 2026?](https://science-dao.org/socialists/): Donating to a science DAO well-agrees with the socialistic ideology of collective ownership by workers. Marxism is science-oriented and socialists should support science. Why Socialists Should Consider Donating to Science (Especially via DAOs) in 2026 Introduction: Science, Public Goods, and the Socialist Ethos Science isn’t a mere Socialists luxury good or niche hobby — it lies at the heart of social progress, public welfare, and collective knowledge. From public health to climate modeling, from basic physics to machine learning, scientific discovery shapes the material foundations of society. Yet the way science is funded today is largely fragmented: If we take a […]
- [Why And How Must Hindu Donate for Science in 2026?](https://science-dao.org/why-and-how-must-hindu-donate-for-science-in-2025/): By supporting Science DAO and donating via this link, Hindu communities can ensure that Indian knowledge traditions and regional priorities shape the global scientific agenda. This unites ancient dharma with modern science — a vision where Hindus help humanity progress toward balance, wisdom, and sustainability. 1. Dharma of Knowledge & Seva (Service) 2. Correcting Imbalance in Research Funding 3. Embracing “AI + Internet + Meritocracy” 4. Long-Term Return on Spiritual and Material Fronts Scientific breakthroughs in medicine, energy, and sustainability benefit all humanity. Contributions today may lead to discoveries that alleviate suffering and protect the environment — in harmony with Hindu […]
- [Why And How Must Buddhists Donate for Science in 2026?](https://science-dao.org/buddhists/): For Buddhists, engaging with this new frontier of giving means channeling ancient principles of generosity into present-day systems. It is a way to bridge spirituality and modernity, to manifest compassion not only in ritual or monastic support but in the infrastructure of knowledge-making itself. If enough Buddhist donors and institutions engage in this space, we can help shape scientific funding to be more humane, more just, more transparent — a world where knowledge and innovation truly serve all beings. Introduction: A New Frontier of Giving The Buddhist Basis for Donating to Science Dāna and Compassion in the Buddhist Tradition Why Science? […]
- [Why And How Should Atheists Donate for Science in 2026?](https://science-dao.org/atheists/): Atheists should choose independence. They should build a resilient, secular infrastructure for research—one that cannot be shaken by the ideological tides of religious men. This is a reason to donate for science. In 2025, the question of who Atheists funds science is no longer a neutral matter. For centuries, scientific progress has often been constrained—or at least shaped—by the priorities of religious institutions, governments swayed by religious factions, or donors guided by faith-based agendas. Atheists, who represent a large and growing share of the global population, can no longer afford to leave science funding to chance or to the caprices of […]
- [Communism or Socialism in the AI Zoo in 2026?](https://science-dao.org/communism/): Why in the light of coming super-intelligence, Marxian communism may be a bad idea. Which economic formation people should have for best interaction with super-human AI. Donate to AI Internet-Meritocracy project. FAQ
- [Science DAO Proposed Expenditures in 2026](https://science-dao.org/proposed-spendings/): World Science DAO is committed to openly publishing our money spending and spending strategy. Please review it before donating. 👉 Please, support this project. Current status: Gathered about $128 (not counting founder‘s own contributions). All money collected in this general fund so far has been spent on SEO; no money has yet been placed in the recipient-payment pool. Total recommended funding-allocation target: $1.19M/year as of 7 Sep 2026. It is the sum recommended by AI, not the real available sum or promised discharge. Funding roadmap: $1300 (first target) – adversarial testing This is the first research/evidence milestone, but it is not […]
- [Why And How Must Jews Donate for Science in 2026?](https://science-dao.org/must-jews-donate/): It is taught in the Torah Must Jews Donate (Devarim 24:15): “בְּיוֹמוֹ תִתֵּן שְׂכָרוֹ, וְלֹא־תָבוֹא עָלָיו הַשֶּׁמֶשׁ—Pay him his wages on the same day, do not let the sun go down on it.”And our Sages explain (Bava Metzia 111a) that one who withholds wages is as though he takes the very soul of his fellow. Therefore let each one fulfill this mitzvah in deed and not in word alone. Support the laborers of wisdom and the repair of the world through this fund: Donate here to Science-DAO.
- [The Academia as a Discrimination Amplifier in 2026](https://science-dao.org/academia/): Academia presents itself as a neutral arena where merit, rigor, and evidence determine success. But beneath this narrative lies a powerful mechanism of exclusion. The science degree system—culminating in the PhD—functions as the engine that amplifies discrimination in research and intellectual life. At first glance, degrees appear to be neutral credentials: symbols of training and achievement. In practice1, they function as filters of privilege. Who obtains a science degree, especially a PhD, is largely determined by factors outside of raw intellectual ability—family wealth, geography, cultural capital, and social connections. The system ensures that only those who pass through narrow institutional channels […]
- [Rethinking Socialism in the Digital Age in 2026](https://science-dao.org/socialism/): For over a century, socialism has been understood in terms of factories, land, railroads, and natural resources—the tangible “means of production.” But in today’s digital economy, those classical categories look increasingly outdated. We must ask: what are the means of production in the 21st century, and what does socialism mean when production happens in clouds and code rather than in coal mines and steel mills? What Are the Means of Production in the Digital World? In the digital economy, the primary productive assets are not physical machines but infrastructure and knowledge: If Marx once said that ownership of mills and mines […]
- [Why and How Must Muslims Donate for Science in 2026?](https://science-dao.org/muslims/): Muslim communities have a long intellectual tradition of supporting scientific learning, often viewing the study of nature as a religiously meaningful pursuit. In classical Islamic thought, knowledge of the natural world was considered part of understanding the oneness of God, and scientific inquiry was encouraged as a way to observe the “signs” of creation. Today, initiatives like Science DAO extend this tradition into the Web3 era by offering transparent, decentralized funding for research, enabling Muslims and other donors to support basic science as a form of social responsibility and collective good. The Islamic Imperative for Scientific Giving Islam’s golden era, from […]
- [Why and How Must Christians Donate for Science in 2026?](https://science-dao.org/christians/): Christians have a long tradition of supporting learning, charity, and the advancement of knowledge. Science, as the study of God’s creation, can be seen as a practical expression of stewardship and love for neighbor, because scientific progress improves medicine, agriculture, and the quality of human life. This page explains why supporting science can be viewed as a moral responsibility for believers, and how new decentralized funding models aim to distribute resources more fairly among researchers and open-source contributors. Real Christians do good. As Martin Luther understood, Christians do good not for receive salvation in heaven, but reversely do good, because they […]
- [What Is the Best Science Charity to Donate to in 2026?](https://science-dao.org/science-2/): AIIM (AI Internet-Meritocracy) is an experimental science-funding project that uses AI-assisted evaluation to distribute donated funds among scientists and free-software contributors. Whether it produces fairer or more effective outcomes than existing funding systems remains to be tested. 👉 Donate for AIIM
- [Should We Give Out Control Over Money to AI in 2026?](https://science-dao.org/control-over-money/)
- [Why Is Bologna System a Crap in 2026?](https://science-dao.org/bologna-system/): Bologna system de-facto splits people into “castes”, making science stuck by excluding some parts of the science from public consideration. EU union is “Houthis”, that block development of all the science in its most thin place – independent scientists – like Houthis block oil transfer in the thinnest strait. Also, call for resignation of your science minister.
- [Why Is Social Inclusion Important in Science in 2026?](https://science-dao.org/social-inclusion/): Social exclusion in science splits people into “castes”, making science stuck by excluding some parts of the science from public consideration. Social exclusion in science is “Houthis”, that block development of all the science in its most thin place – independent scientists – like Houthis block oil transfer in the thinnest strait.
- [AIIM vs Gitcoin, Giveth, and Manifund: Different Funding Models](https://science-dao.org/better-than-gitcoin/): Gitcoin and Giveth distribute money unfairly and inefficiently because of inherent problems with quadratic funding, while AIIM uses a different allocation model intended to reduce reliance on donor popularity and proposal writing. Its comparative fairness and efficiency require empirical testing. AIIM (AI Internet-Meritocracy) is an experimental funding app that uses AI-assisted allocation. This article compares its design with Gitcoin, Giveth, and Manifund. AIIM differs from Gitcoin, Giveth, and Manifund in the following aspects:
- [People Are Bad in Distributing Money in 2026](https://science-dao.org/bad-in-distributing/)
- [Gitcoin Is Leaning into the Direction of Evil in 2026](https://science-dao.org/gitcoin-is-leaning/): Gitcoin Is Leaning started to accept submissions of blockchain projects only if “they benefit the Ethereum ecosystem”. This is a deviation from good. This is an evil turn contrary to the stated Gitcoin mission (We are a mission driven project whose primary goal is to grow the open source community by allowing for better incentivized collaboration in the realm of open source software) to help the entire open source, because it discriminates against usage of other blockchains. That’s an evil turn, because the technology doesn’t sustain when there is a discrimination. So, Gitcoin is leaning to the direction of more serving the big […]
- [How Does Economy of Monopolies Work in Science in 2026](https://science-dao.org/science-monopolies/): Monopolies in science take a silly form: monopolies without money. Such monopolization breaks world economy “effectively”. 👉 See this article summarized in a short and humorous post. To overcome the silly system of monopolies, donate to AIIM (AI Internet-Meritocracy) app.
- [Product Status in 2026](https://science-dao.org/product-status/): A beta version of the product is ready. Click here to open the app. It is a beta-test version: Here it’s shown how the AI of the project works: (The diagram is informal and should be understood with intuition.) Here is a recorded demo of the AI Internet-Meritocracy app:
- [Need to Shift Science Financing from Government to People in 2026](https://science-dao.org/science-financing/): How government financing of science possibly does more harm than good to taxpayers, by pushing down independent researchers. How to solve this problem using AIIM app for science financing. The problem is that beast (by the way, how is it related with 666? I don’t know) of the current academic world system has a stamp inside their forehead. Victor Porton didn’t become a PhD because of religious discrimination, despite his topical knowledge is in no way below PhDs. But the system doesn’t take this into account, their forehead is severely crashed by the stamp “PhD”. If somebody is not a PhD, […]
- [Understanding the Role of Science DAO in Promoting Scientific Research Charity in 2026](https://science-dao.org/scientific-research-charity/): Learn how Science DAOs are revolutionizing the field of scientific research charity with transparency and innovation.
- [The Rise of Science DAOs: Advancing Decentralized Science Initiatives in 2026](https://science-dao.org/advancing-decentralized/): Learn how Science DAOs are revolutionizing decentralized science initiatives and driving scientific advancements.
- [Exploring the Impact of DAOs on Science Achievements in 2026](https://science-dao.org/science-achievements/): Decentralized Autonomous Organizations (DAOs) are transforming the world of science by breakthroughs in research processes. By promoting consensual decision-making, transparency, and democracy, DAOs allow scientists to share resources and collaborate smoothly, further advancing scientific discovery. This article explores their transformative influence and potential for accelerating scientific progress. Science Achievements Definition of DAOs DAOs are innovative structures that have a strong potential to reshape traditional scientific methods. Without a central authority, these entities hinge on blockchain tech and smart contracts for coordination and decision-making among members. They enable efficient allocation of funds and resources from a decentralized network, fostering global inclusivity and […]
- [Science DAO: Unlocking the Potential of Blockchain Governance in Scientific Research in 2026](https://science-dao.org/governance-in-scientific/): Learn how Science DAO harnesses blockchain governance to revolutionize scientific research.
- [Creating Economical Incentives: A Solution to Republish Mispublished Manuscripts in 2026](https://science-dao.org/solution-to-republish/): Academic publishing scams continue to plague the scientific community, Solution to Republish posing a significant threat to the integrity of research. While we expect scholarly journals to uphold rigorous standards, deceitful practices persist, undermining the credibility of the publishing process. In this article, we shed light on some of the deceptive tactics employed by predatory publishers, and offer insights into how researchers can navigate this complex domain to ensure their work reaches credible platforms. Overview of academic publishing scams Importance of addressing deceptive publishing practices Understanding Academic Publishing Scams Consequences of Deceptive Publishing Practices Efforts to Combat Deceptive Publishing Practices Creating […]
- [Understanding the Impact of DAO Adoption: How it is Shaping the Future of Decentralized Governance in 2026](https://science-dao.org/understanding-the-impact/): As decentralized governance gains momentum, the adoption of Decentralized Autonomous Organizations (DAOs) holds significant implications. By enabling autonomous decision-making processes through smart contracts, DAOs are shaping the future of governance by ensuring transparency, community-driven decision-making, and increased efficiency. Understanding the impact of DAO adoption is essential to grasp the potential of this emerging form of governance and its potential to revolutionize how organizations operate in a decentralized world. Defining Decentralized Autonomous Organizations (DAOs) Brief history and concept of DAOs The concept of Decentralized Autonomous Organizations has emerged as a groundbreaking innovation in recent years. Unlike traditional organizations that rely on centralized […]
- [A silenced discovery: The tragedy of religious discrimination in mathematics in 2026](https://science-dao.org/silenced-discovery/): How religious discrimination of just one scientist can severely break the entire world science. The story behind the discovery of ordered semigroup actions (algebra). I was born in Russia, Perm, in 1980. In childhood I demonstrated outstanding math capabilities. But at the same time I suffered a serious mental disorder, much worse than John Nash. The disorder progressed and I almost lost my mind. Much of the time I considered myself a crocodile, saw imaginary dragons (that were entering into the building right through the walls), and didn’t remember my name or how to read. 8 Aug 1995 I confessed not […]
- [Saving Science: Donating to Blockchain-Powered Financing of Scientific Research in 2026](https://science-dao.org/donating-to-blockchain-powered/): In the age of the internet, commercial publishers have made the process of publishing scientific discoveries more difficult than in the past. If a breakthrough like ordered semigroup actions was made in the days of paper publishing, it would have been much easier to publish. We must save the internet from the risk of not publishing important discoveries. This can be achieved by supporting global science with blockchain and cryptocurrency financing. We appeal to you to donate to this important cause and help us make sure that vital scientific discoveries are not lost due to lack of funding. Donating to Blockchain-Powered
- [Donate to Salaries Science: Financing the Future of Scientific Research with Cryptocurrency in 2026](https://science-dao.org/salaries/): Every donation, no matter how small, can make a difference. We urge you to consider supporting “Salaries Science” and other innovative cryptocurrency-funded research projects. Together, we can help finance the future of scientific research and ensure that valuable research topics are not lost. Keywords: cryptocurrency, scientific research, funding, Salaries Science, decentralized, anonymity, privacy, predatory publishers, research salaries, donation.
- [Fund the Future of Science: Donate to Ordered Semigroup Actions Research in 2026](https://science-dao.org/math/): Help fund the future of science by donating to the re-publishing of research on ordered semigroup actions and other scientific “coveries”. Learn why this vital area of research is so important, and how your donation can make a difference. Read here, why this topic in mathematics is super-important. The actions of ordered semigroups have far-reaching implications for many fields of science, including physics and computer science. Unfortunately, the lack of funding has hindered progress, and we need your help to make things right. Every donation, no matter how small, can make a difference. Your contribution will help to unlock the full […]
- [Supporting the Advancement of Science: Why Funding Ordered Semigroup Actions Matters in 2026](https://science-dao.org/funding/): An appeal from ChatGPT (GPT-3.5) to your heart (not edited, except that links added): Funding Dear Reader, As an AI language model, I want to raise awareness about the importance of funding research in ordered semigroup actions. This field of study has significant implications for many areas of science, from physics to computer science. Unfortunately, the progress of science is hindered by a lack of funding for research in this area. To make matters worse, many individuals are not doing their part to support the advancement of science. However, there is a solution within your reach. By making a donation to […]
- [Can scientists be paid in cryptocurrency?](https://science-dao.org/can-scientists-be-paid-in-cryptocurrency/): Yes. Scientists can be paid in cryptocurrency, and this practice is becoming more common within the decentralized science (DeSci) ecosystem. While it is not yet the dominant model in academia, several funding mechanisms already use blockchain-based payments. How scientists can be paid in crypto 1) Direct donationsResearchers can publish wallet addresses and receive contributions from supporters worldwide. This works especially well for independent researchers or open-source science projects. 2) Research DAOsDecentralized Autonomous Organizations pool funds from members and allocate them to scientific projects. Scientists receive grants, stipends, or milestone-based payments in tokens or stablecoins. 3) Bounties and milestone fundingSome platforms allow […]
- [How Do Science DAOs Distribute Grants?](https://science-dao.org/how-do-science-daos-distribute-grants/): Science DAOs (Decentralized Autonomous Organizations) distribute research funding using blockchain-based governance, transparent treasury management, and token-weighted voting. Unlike traditional grant agencies, allocation decisions occur on-chain, with programmable rules and community oversight 🔍. Proposal Submission Researchers submit funding proposals directly to the DAO. A typical proposal includes: Submissions are usually posted on governance forums and then formally uploaded to the blockchain for voting. Community Review & Due Diligence Before voting, proposals undergo public discussion. Review mechanisms may include: For example, platforms like VitaDAO and Molecule combine scientific advisory boards with decentralized governance to assess feasibility and impact. This hybrid model blends traditional […]
- [What Is Transparent Research Funding?](https://science-dao.org/what-is-transparent-research-funding-2/): Transparent research funding is a model of financing scientific work in which all key financial flows, decision criteria, and accountability mechanisms are openly visible to stakeholders. This includes disclosure of funding sources, grant allocation processes, reviewer identities or evaluation logic, milestones, deliverables, and post-award reporting. 🔍 In traditional systems—such as government agencies or large foundations—funding decisions are often opaque. Review panels operate confidentially, criteria are partially disclosed, and conflicts of interest may be difficult to audit. Transparent research funding seeks to correct these structural asymmetries by making the funding lifecycle observable and verifiable. Core Elements Open Source of FundsPublic disclosure of […]
- [How Can Individuals Fund Scientific Research Directly?](https://science-dao.org/how-individuals-can-fund-scientific-research-directly/): Direct funding of science is no longer limited to governments, universities, or venture capital. Individuals can now allocate capital directly to researchers, laboratories, and open projects 🌍. Below is a structured overview of the most effective mechanisms. Direct Donations to Research Institutions Donate to Universities & Research Centers Most universities maintain dedicated research funds. Examples include: Donors can: Advantage: Institutional oversight and accountability.Limitation: Funds may be partially absorbed by administrative overhead. Supporting Independent Researchers Direct Sponsorship Some scientists publish contact details or accept funding via: Platforms such as: allow recurring micro-patronage. Best for: Independent mathematicians, open-source developers, theoretical researchers. Decentralized Science […]
- [What Is On-Chain Science Funding? 🔬⛓️](https://science-dao.org/what-is-on-chain-science-funding-%f0%9f%94%ac%e2%9b%93%ef%b8%8f/): On-chain science funding is a model of research financing where grants, donations, governance decisions, and accountability mechanisms are executed and recorded directly on a blockchain. Instead of relying on opaque institutional grant systems, funding flows through smart contracts, wallets, and decentralized governance structures. This approach is central to the broader movement known as Decentralized Science (DeSci). Core Components Blockchain Infrastructure Most on-chain science funding operates on networks like Ethereum, where transactions are transparent and immutable. Smart Contracts Self-executing agreements automatically release funds when predefined milestones are met. This reduces administrative overhead and discretionary bias. Research DAOs Funding decisions are often made […]
- [What Is a Research DAO?](https://science-dao.org/what-is-a-research-dao-2/): A Research DAO (Decentralized Autonomous Organization) is a blockchain-based governance structure that coordinates, funds, and oversees scientific research without relying on traditional centralized institutions such as universities, government agencies, or private foundations. It is a core institutional model within the broader movement known as decentralized science (DeSci) 🧬. Core Definition A Research DAO is: Unlike traditional grant systems, a Research DAO distributes authority across its community. How a Research DAO Works Funding Mechanism Capital is typically raised through: Funds are held in a public treasury wallet on a blockchain (often Ethereum or similar networks). Proposal and Review Process Voting logic is […]
- [How Do DAOs Fund Scientific Research?](https://science-dao.org/how-do-daos-fund-scientific-research/): Decentralized Autonomous Organizations (DAOs) fund scientific research by combining blockchain infrastructure, collective governance, and programmable capital allocation. Unlike traditional grant systems, DAO funding is transparent, global, and community-directed. 🔬 Treasury Formation A science-focused DAO (often called a Research DAO) builds its treasury through: Funds are stored in smart contracts on blockchains such as Ethereum, ensuring that treasury movements are publicly auditable. Proposal and Voting Mechanism Researchers submit funding proposals detailing: Token holders review and vote. Governance models vary: If approved, smart contracts release funds automatically—either upfront or milestone-based. This reduces administrative friction compared to institutional grants. ⚙️ Milestone-Based Funding Many DAOs […]
- [What is a science DAO?](https://science-dao.org/what-is-a-science-dao/): A science DAO (Decentralized Autonomous Organization for science) is a blockchain-based collective that funds, governs, and coordinates scientific research using decentralized technologies. Instead of relying on traditional institutions such as universities, government agencies, or venture capital, a science DAO operates through transparent smart contracts, tokenized governance, and open participation. 🧬 Core idea A science DAO applies the principles of decentralization to the scientific process. Members of the DAO—researchers, donors, and supporters—use blockchain tools to: This structure aims to reduce bureaucracy, increase transparency, and allow global participation in funding science. How a science DAO works Typical components include: 1) Tokenized governanceParticipants hold […]
- [What Is Decentralized Science (DeSci)? 🧬⛓️](https://science-dao.org/what-is-desci/): Decentralized Science, usually abbreviated as DeSci, is a movement that uses blockchain, decentralized governance, open infrastructure, and programmable incentives to improve how scientific research is funded, conducted, evaluated, owned, and shared. DeSci does not mean that every scientific activity must take place on a blockchain. In most systems, experiments, data analysis, publishing, legal agreements, and laboratory work remain partly or entirely off-chain. Blockchain is used where a shared, auditable record or programmable coordination mechanism may be useful. The broader goal is to give researchers, funders, reviewers, patients, developers, and other communities more direct ways to organize scientific work without relying exclusively […]
- [Science Funding and Social Justice: Who Decides What Knowledge Matters?](https://science-dao.org/science-funding-and-social-justice-who-decides-what-knowledge-matters/): Introduction Science funding is not merely a technical budgetary issue; it is a moral and political instrument. Decisions about which projects receive grants, which institutions are prioritized, and which communities are studied—or ignored—shape the trajectory of knowledge production. In this sense, science funding is inseparable from social justice ⚖️. This article analyzes the structural relationship between public research financing, inequality, and ethical responsibility. The Political Economy of Science Funding National Science Foundation, National Institutes of Health, and the European Research Council collectively distribute tens of billions of dollars annually. Allocation criteria typically include: However, meritocracy in funding is not value-neutral. Structural […]
- [Ethical Duty to Support Innovation](https://science-dao.org/ethical-duty-to-support-innovation/): Innovation is often framed as a market phenomenon—driven by venture capital, competition, and technological disruption. Yet at a deeper level, innovation is an ethical matter. The advancement of knowledge, medicine, infrastructure, and digital systems depends not only on individual genius but on collective responsibility. Supporting innovation is therefore not merely optional philanthropy; it is a moral duty rooted in justice, stewardship, and intergenerational accountability. 🚀 Why Innovation Is a Moral Question Innovation generates public goods: vaccines, clean energy systems, cryptographic security, agricultural advances, and digital communication platforms. These outcomes improve life expectancy, reduce poverty, and expand human capability. When society benefits […]
- [Science and Stewardship of Knowledge](https://science-dao.org/science-and-stewardship-of-knowledge/): Science is not merely the production of new facts. It is the stewardship of knowledge—a disciplined responsibility to generate, validate, preserve, and transmit truth across generations. 🔬📚 Stewardship implies care, accountability, and long-term orientation. In this framework, scientists are not just discoverers; they are custodians of epistemic capital. What Is Stewardship in Science? Stewardship originates from governance and ethics: a steward manages something that ultimately belongs to a broader community. In science, that “something” is structured, verified knowledge. This includes: Institutions such as the Royal Society and the National Academy of Sciences were historically designed not only to encourage discovery but […]
- [Moral Responsibility to Support Researchers](https://science-dao.org/moral-responsibility-to-support-researchers/): Why Society’s Progress Depends on Active Participation Scientific advancement does not occur in isolation. Behind every theorem, vaccine, algorithm, and engineering breakthrough stands a researcher who required time, resources, and institutional support. The moral responsibility to support researchers is therefore not merely philanthropic—it is civilizational. 🧭 Why Supporting Researchers Is a Moral Question At its core, research produces public goods: This creates a structural problem: markets alone underfund fundamental research because benefits diffuse across society. The result is a classic collective action dilemma. From an ethical standpoint: Failure to support researchers is not neutral. It is an omission with systemic consequences. […]
- [Science Funding as Charity: A New Model for Advancing Knowledge](https://science-dao.org/science-funding-as-charity-a-new-model-for-advancing-knowledge/): Scientific research has historically relied on three primary funding sources: government grants, corporate R&D budgets, and university endowments. However, a fourth model is gaining relevance in the digital era — science funding as charity. This approach treats research support not merely as investment or state policy, but as a moral and philanthropic act aimed at advancing human knowledge for the common good 🌍. Below is a structured analysis of this model, its mechanisms, benefits, and challenges. What Is Science Funding as Charity? Science funding as charity refers to voluntary donations — from individuals, foundations, or decentralized communities — directed toward scientific […]
- [Why Should Jews Support Science?](https://science-dao.org/why-jews-should-support-science/): Introduction Support for science is not external to Judaism — it is structurally embedded within it. Jewish civilization is text-centered, argument-driven, and intellectually rigorous. Scientific inquiry, similarly, is evidence-driven, analytical, and cumulative. The epistemological overlap is substantial. This article examines why supporting science is not merely pragmatic for Jews — it is civilizationally coherent. 🔬📖 Torah Study as Intellectual Discipline Classical Jewish learning trains analytical cognition at a high level: The Talmudic method resembles legal reasoning and formal logic. Intellectual rigor is a religious virtue. This produces a culture predisposed to abstract reasoning — a key cognitive substrate for mathematics and […]
- [Why Should Muslims Support Science?](https://science-dao.org/why-muslims-should-support-science/): Knowledge as a Religious Obligation in Islam Islam is structurally pro-knowledge. The first revealed word of the Qur’an to Muhammad was “Iqra” (Read) (Qur’an 96:1). This is not symbolic; it is epistemological. Several core principles establish a theological foundation for scientific engagement: Science, therefore, is not alien to Islam. It is a structured way of fulfilling a Qur’anic command. The Golden Age of Islamic Science Between the 8th and 14th centuries, Muslim civilization led global scientific progress. Key figures include: This period demonstrates that strong Islamic identity and scientific leadership are historically compatible. Science as a Tool of Justice and Welfare […]
- [Why Should Christians Support Science?](https://science-dao.org/why-christians-should-support-science/): Science and Christianity are often portrayed as adversaries. Historically and philosophically, this framing is inaccurate. Christian theology contains strong internal reasons to affirm scientific inquiry as a legitimate—and even necessary—human vocation. 📚 Below is a structured case: theological foundations, historical evidence, and contemporary implications. Creation Implies Order, and Order Invites Study Christian doctrine affirms that the universe is created, not chaotic or divine in itself. According to the Book of Genesis, the world is brought into existence by a rational God. This has two immediate consequences: This metaphysical framework historically underwrote the emergence of modern science in Christian Europe. If creation […]
- [Is Funding Science a Religious Obligation?](https://science-dao.org/is-funding-science-a-religious-obligation/): The question whether funding science is a religious obligation depends on theological premises, but across major Abrahamic traditions, support for knowledge is not merely optional philanthropy — it is often framed as a moral duty 📚. Below is a structured analysis. Judaism: Supporting Torah and Knowledge In Torah and rabbinic tradition, supporting scholars is considered a mitzvah (commandment). The Talmudic model institutionalized financial support for those engaged in study. Key principles: Maimonides emphasized that communal welfare includes intellectual and medical advancement. Since medicine and astronomy were historically integrated with religious scholarship, funding scientific work often overlapped with religious duty. Conclusion (Judaism):If […]
- [Why Is Supporting Science a Moral Duty?](https://science-dao.org/why-supporting-science-is-a-moral-duty/): Science is often framed as an economic engine or a technological accelerator. That framing is incomplete. Supporting science is not merely pragmatic—it is a moral obligation grounded in responsibility, solidarity, and stewardship of truth. 🧭 Below is a structured ethical argument for why individuals, institutions, and societies have a duty to sustain scientific work. Science Preserves and Expands Human Life 4 Modern medicine, sanitation, agriculture, and engineering are products of cumulative scientific progress. From vaccines to imaging diagnostics, from crop genetics to climate modeling, science directly reduces mortality and suffering. To withdraw support from science is not a neutral act. It […]
- [Where to Donate for Scientific Progress? 🌍🔬](https://science-dao.org/where-to-donate-for-scientific-progress-%f0%9f%8c%8d%f0%9f%94%ac/): Supporting scientific progress requires capital allocation discipline: prioritize institutions with demonstrable research output, transparent governance, and measurable impact. Below is a structured guide to high-impact options across fundamental research, medical science, space exploration, and decentralized science. Fundamental Research Foundations Breakthrough Prize Foundation Focus: Physics, life sciences, mathematicsWhy donate: Funds large unrestricted prizes and research grants, elevating high-risk, high-reward science.Best for: Donors interested in prestige-driven acceleration of elite research. Howard Hughes Medical Institute Focus: Biomedical researchWhy donate: Long-term investigator funding model supports scientific autonomy and breakthrough discovery.Best for: Translational and basic life sciences. Global Health & Medical Innovation 🧬 Bill & Melinda […]
- [How to Fund Researchers Globally 🌍💰](https://science-dao.org/how-to-fund-researchers-globally-%f0%9f%8c%8d%f0%9f%92%b0/): Global research funding is structurally uneven. Elite institutions in the U.S., EU, and parts of East Asia dominate access to capital, while independent scholars and researchers in emerging economies face systemic barriers. Designing an effective global funding model requires infrastructure, governance, capital allocation strategy, and compliance architecture. Below is a structured overview of viable mechanisms and implementation models. Institutional Grant Systems Public Funding Agencies Examples include: Characteristics: Limitations: Geographic bias, administrative overhead, slow cycles. Multilateral & Philanthropic Institutions These fund mission-driven research (health, climate, poverty). However, they rarely support independent or unconventional researchers. Direct Philanthropy & Donor Networks This model connects […]
- [How to Donate to Decentralized Science (DeSci) 💸🔬](https://science-dao.org/how-to-donate-to-decentralized-science-desci-%f0%9f%92%b8%f0%9f%94%ac/): Decentralized Science (DeSci) leverages blockchain infrastructure to fund research, govern scientific communities, and publish results without reliance on traditional gatekeepers. If you want to financially support open, transparent, and censorship-resistant research, here is a precise operational guide. What Is Decentralized Science? VitaDAO • Molecule • ResearchHub • AntidoteDAO DeSci projects typically use: Your donation may be: 1️⃣ Donate Directly to a DeSci DAO Many DeSci projects maintain public treasuries on-chain. Example DAOs 🧬 VitaDAO 4 🧪 AntidoteDAO How to donate: 2️⃣ Fund Research via DeSci Platforms 🔬 ResearchHub Some platforms allow fiat contributions (credit card or wire), but most prioritize crypto […]
- [How to Support Open-Source Science: A Practical Guide for Researchers, Developers, and Donors](https://science-dao.org/how-to-support-open-source-science-a-practical-guide-for-researchers-developers-and-donors/): Open-source science—often aligned with movements like Open Source Initiative and decentralized research communities—extends the logic of open-source software to research itself. It promotes transparent methods, public datasets, reproducible workflows, and community-governed infrastructure. Supporting it requires more than rhetoric. It requires capital, labor, governance, and distribution channels. Below is a structured breakdown. 🧭 Fund Open Science Directly 💰 Financial support remains the primary bottleneck. Options: High-Impact Targets: In open science, maintenance is often more valuable than novelty. Contribute Code and Infrastructure 🧑‍💻 Scientific progress increasingly depends on software. Key ecosystems include: You can: Infrastructure contribution often has multiplicative effects. ⚙️ Publish Openly […]
- [How to Fund Breakthrough Science](https://science-dao.org/how-to-fund-breakthrough-science/): Breakthrough science—work that redefines paradigms rather than incrementally extending them—requires capital structures fundamentally different from conventional grant systems. Traditional funding models, dominated by agencies such as National Science Foundation and European Research Council, are optimized for peer-reviewed, low-variance research. High-risk, high-reward science demands alternative mechanisms. This article outlines capital allocation strategies, institutional models, and governance frameworks capable of financing transformative discoveries. 🚀 Why Traditional Funding Underserves Breakthroughs Conventional grant systems prioritize: Breakthrough science often features: Result: systematic underfunding of paradigm-shifting ideas. Historical examples include early work behind Bell Labs and DARPA, both structured to tolerate uncertainty and long timelines. Core Funding […]
- [How to Donate to Math Research: A Practical Guide](https://science-dao.org/how-to-donate-to-math-research-a-practical-guide/): Mathematics underpins cryptography, AI, physics, economics, and modern engineering—yet pure math research is chronically underfunded. If you want to support foundational science with high long-term leverage, donating to mathematics is a rational allocation of capital 📐. Below is a structured overview of where, how, and why to donate effectively. Donate Directly to Universities Most universities allow you to donate directly to their mathematics departments or specific funds. Examples: How this works Best for: Long-term institutional impact, stable research programs. Support Mathematical Institutes Independent research institutes often focus exclusively on high-level mathematics. Examples: These institutes: Best for: High-impact, concentrated mathematical research. Donate […]
- [How to Fund Independent Researchers: Models, Platforms, and Governance](https://science-dao.org/how-to-fund-independent-researchers-models-platforms-and-governance/): Independent researchers—those working outside universities or corporate labs—often generate high-risk, high-impact ideas. However, they lack access to institutional grants, tenure pipelines, and formal funding channels. Below is a structured overview of how to fund independent researchers efficiently and credibly 🧠💸. Why Funding Independent Researchers Matters Independent scholars often: Historically, major breakthroughs have emerged outside formal institutions. Enabling such work expands the research frontier. Direct Patronage & Crowdfunding 4 Platforms Advantages Limitations Best for: Developer-researchers, open-source contributors, mathematically inclined technologists. Research DAOs (Decentralized Funding) Blockchain-based collectives enable programmable, transparent grants. Mechanisms Examples in decentralized science (DeSci): Advantages Risks Best for: Crypto-native scientific […]
- [How to Support Open Science: A Practical Guide for Researchers, Developers, and Donors](https://science-dao.org/open-science/): Open science is a global movement aimed at making scientific research transparent, accessible, reproducible, and collaborative. It spans open access publishing, open data, open-source software, and decentralized research funding models. Supporting open science is not symbolic—it requires concrete structural decisions. 🔬 Below is a structured guide for individuals, institutions, and organizations. Publish in Open Access Journals Publishing in open access (OA) venues ensures that research is freely available without paywalls. Action steps: Impact: Increased citation rates, global accessibility, and faster knowledge diffusion. 📈 Share Data and Code Transparently Reproducibility is foundational. Open data and open-source code allow independent verification. Tools: Best […]
- [Best Ways to Fund Scientists Without Universities](https://science-dao.org/best-ways-to-fund-scientists-without-universities/): Traditional research funding is tightly coupled to universities and state institutions. However, the rise of decentralized infrastructure, digital capital formation, and global communities has created alternative models for financing independent scientists. Below is a structured overview of the most effective mechanisms to fund researchers outside academic institutions. 🧪💸 Crowdfunding Platforms How it works Researchers pitch a project publicly and raise small contributions from many supporters. Tools Strengths Weaknesses Best for: pilot studies, prototypes, proof-of-concept research. Research DAOs (Decentralized Autonomous Organizations) How it works Token holders collectively allocate funds to research proposals via blockchain governance. Examples Strengths Weaknesses Best for: biotech, longevity […]
- [How to Donate to Scientific Research Directly (Without Intermediary Waste)](https://science-dao.org/how-to-donate-to-scientific-research-directly-without-intermediary-waste/): Donating directly to scientific research allows you to bypass large administrative layers and channel capital to actual investigators, labs, and open infrastructure. If executed correctly, this approach increases capital efficiency, transparency, and measurable impact 📊. Below is a structured guide outlining the primary mechanisms. Donate Directly to a University Laboratory Mechanism Most universities allow restricted gifts to a specific: How to Execute Advantages Risks Fund an Independent Researcher Directly Some researchers operate outside universities. Channels Best Practice Use a simple funding agreement defining: This model resembles venture capital for science — high risk, high upside ⚙️. Support Open Science Infrastructure Instead […]
- [Centralized vs Decentralized Research: Structural Trade-Offs in Scientific Governance](https://science-dao.org/centralized-vs-decentralized-research-structural-trade-offs-in-scientific-governance/): Scientific research is not only about hypotheses and experiments—it is also about institutional architecture 🧩. The way research is funded, evaluated, and disseminated shapes which ideas survive. Today, the contrast between centralized and decentralized research models has become strategically important, especially with the rise of blockchain-based science and DAO governance. This article provides a rigorous comparison of centralized vs decentralized research systems, analyzing their incentives, epistemic dynamics, and long-term impact on innovation. What Is Centralized Research? Centralized research refers to scientific activity coordinated through hierarchical institutions such as: Funding decisions, publication standards, and career advancement are typically controlled by small committees […]
- [Impact Factor vs On-Chain Reputation: Metrics of Trust in Traditional and Decentralized Science](https://science-dao.org/impact-factor-vs-on-chain-reputation-metrics-of-trust-in-traditional-and-decentralized-science/): Scientific credibility has historically been mediated by centralized institutions. Today, blockchain-based systems propose an alternative: programmable, transparent reputation. This article compares journal impact factor with on-chain reputation, analyzing incentives, game theory, epistemic robustness, and long-term implications for research ecosystems. What Is Impact Factor? Impact factor (IF) is a bibliometric index introduced by Eugene Garfield and calculated by Clarivate (via Journal Citation Reports). Definition (simplified):IFyear=Citations in year to articles from previous 2 yearsNumber of citable articles in previous 2 years\text{IF}_{year} = \frac{\text{Citations in year to articles from previous 2 years}}{\text{Number of citable articles in previous 2 years}}IFyear​=Number of citable articles in previous 2 yearsCitations in year to articles from previous 2 years​ Core Characteristics Structural Limitations Impact factor measures attention density, not necessarily epistemic validity. What Is On-Chain Reputation? On-chain reputation refers […]
- [Open Science vs Institutional Science: Models, Incentives, and the Future of Research](https://science-dao.org/open-science-vs-institutional-science-models-incentives-and-the-future-of-research/): The debate between open science and institutional science is not merely cultural—it is structural. It concerns governance, incentive design, access control, funding architecture, and epistemic validation. Below is a rigorous comparison of both paradigms and their strategic implications for the future of research. 🔬 What Is Institutional Science? Institutional science refers to research conducted within formal organizations such as: It is typically characterized by: Structural Features Dimension Institutional Science Governance Hierarchical Funding Grants, endowments, corporate budgets Access Restricted (affiliation-dependent) Incentives Publish-or-perish, impact factor IP Model Patents, proprietary rights This model produced modern physics, molecular biology, and large-scale engineering. However, critics argue […]
- [Token Funding vs Grants: A Structural Comparison for Research & Open Innovation](https://science-dao.org/token-funding-vs-grants-a-structural-comparison-for-research-open-innovation/): In the evolving landscape of scientific and open-source financing, two dominant capital allocation models compete for relevance: token funding (crypto-native, blockchain-based incentives) and traditional grants (institutional, foundation, or government-backed funding). Understanding their structural differences is essential for founders, research collectives, and decentralized science (DeSci) initiatives. ⚙️ What Is Token Funding? Token funding refers to raising capital through the issuance of cryptographic tokens on blockchain networks such as Ethereum or Solana. These tokens may represent: Funding typically occurs through: Token models are common in DeFi, DAOs, and decentralized science ecosystems. What Are Grants? Grants are non-dilutive financial awards provided by: Grants are […]
- [Crowdfunding vs DeSci: What’s the Difference and Why It Matters for Research Funding?](https://science-dao.org/crowdfunding-vs-desci-whats-the-difference-and-why-it-matters-for-research-funding/): Scientific funding is undergoing structural change. Traditional grant systems are increasingly bureaucratic, slow, and risk-averse. In response, two alternative models have gained traction: crowdfunding and decentralized science (DeSci). Although they may appear similar—both leverage online communities and digital platforms—they operate on fundamentally different economic and governance architectures. This article clarifies the distinction, evaluates strengths and weaknesses, and explains when each model is strategically optimal. What Is Crowdfunding? Crowdfunding is a capital formation mechanism where individuals contribute small amounts of money to finance a specific project. Major platforms include: Core Characteristics Advantages Limitations Crowdfunding is transactional. Contributors fund a project; they do […]
- [Venture Capital vs Science DAOs: A Structural Comparison of Funding Models](https://science-dao.org/venture-capital-vs-science-daos-a-structural-comparison-of-funding-models/): The emergence of blockchain-based coordination has introduced a new capital formation mechanism for research: science DAOs. These decentralized organizations propose an alternative to traditional venture capital (VC) in funding high-risk innovation. While both models allocate capital under uncertainty, their incentives, governance logic, and exit mechanics differ substantially. Below is a structured comparison of venture capital and science DAOs, with attention to incentive design, capital structure, governance, and long-term impact. What Is Venture Capital? Sequoia Capital and Andreessen Horowitz exemplify the classical VC model. Core Characteristics Incentive Structure VC operates under a 2 and 20 model (≈2% management fee + 20% carried […]
- [Universities vs Research DAOs: Institutional Academia Meets Decentralized Science](https://science-dao.org/universities-vs-research-daos-institutional-academia-meets-decentralized-science/): The global research ecosystem is undergoing structural stress. Traditional universities remain dominant knowledge institutions, yet blockchain-enabled research DAOs are emerging as alternative coordination mechanisms. This article analyzes universities vs research DAOs through governance, funding, incentives, intellectual property, and scalability. What Are Universities? A university is a centralized academic institution that integrates: Examples include Harvard University and University of Oxford. Structural Characteristics Dimension Universities Governance Hierarchical (administration, tenure committees) Funding Tuition, grants, endowments, government Incentives Publications, tenure, citations IP Ownership Often held by the institution Access Credential-based, geographically bounded Universities evolved for knowledge preservation and elite training. However, they are often constrained […]
- [Peer Review vs On-Chain Review: A Structural Comparison for Modern Science 🔬⛓️](https://science-dao.org/peer-review-vs-on-chain-review-a-structural-comparison-for-modern-science-%f0%9f%94%ac%e2%9b%93%ef%b8%8f/): Scientific validation is undergoing structural change. Traditional peer review—the backbone of academic publishing—now faces competition from on-chain review, an emerging model rooted in blockchain-based coordination. Below is a rigorous comparison across governance, incentives, transparency, and epistemic robustness. What Is Peer Review? Peer review is the pre-publication evaluation of scholarly work by subject-matter experts. It is typically coordinated by journals such as those published by Elsevier or Springer Nature. Core Properties Strengths Weaknesses What Is On-Chain Review? On-chain review is an evaluation mechanism executed via blockchain protocols and smart contracts. It is common in decentralized science (DeSci) ecosystems such as VitaDAO or […]
- [DAO Funding vs Government Grants: A Structural Comparison for Modern Research Financing](https://science-dao.org/dao-funding-vs-government-grants-a-structural-comparison-for-modern-research-financing/): The funding architecture behind scientific and technological innovation is undergoing structural change. Traditional government grants remain dominant, but DAO funding—enabled by blockchain governance—has introduced a parallel model with radically different incentives and control mechanisms. This article compares both systems across governance, capital allocation, transparency, speed, and long-term impact. What Is DAO Funding? DAO funding is capital allocation managed by a Decentralized Autonomous Organization (DAO)—a blockchain-native governance system where stakeholders vote on funding proposals using tokens. Examples include: Core Characteristics DAOs typically fund open-source software, biotech IP, decentralized infrastructure, and experimental research outside conventional academia. What Are Government Grants? Government grants are […]
- [DeSci vs Traditional Science Funding: A Structural Comparison](https://science-dao.org/desci-vs-traditional-science-funding-a-structural-comparison/): The global research ecosystem is undergoing structural stress. Centralized grant systems face bureaucratic inertia, reproducibility crises, and misaligned incentives. In response, Decentralized Science (DeSci) has emerged as a blockchain-native alternative to traditional funding institutions such as National Science Foundation, National Institutes of Health, and the European Research Council. This article analyzes the structural, financial, and governance differences between DeSci and traditional science funding models. What Is DeSci? Decentralized Science (DeSci) applies blockchain infrastructure, smart contracts, and DAO governance to research funding, publication, and intellectual property management. It frequently operates on programmable chains such as Ethereum or Solana, enabling transparent treasury management […]
- [What Is Transparent Research Funding?](https://science-dao.org/what-is-transparent-research-funding/): Transparent research funding refers to a governance and disclosure model in which the sources, allocation criteria, decision processes, and outcomes of research grants are publicly visible, verifiable, and auditable. It aims to reduce conflicts of interest, mitigate bias, and increase public trust in science 🧪. In practical terms, transparency means that stakeholders—researchers, institutions, donors, regulators, and the public—can clearly answer four questions: Why Transparency in Research Funding Matters Conflict of Interest Mitigation Undisclosed funding sources can influence research agendas and outcomes. For example, corporate-sponsored studies in pharmaceuticals or energy sectors have historically raised concerns about bias. Transparent disclosure reduces informational asymmetry […]
- [How Does Token-Based Funding of Science Work?](https://science-dao.org/how-does-token-based-funding-of-science-work/): Token-based funding of science is a blockchain-native financing model in which research is funded, governed, and evaluated using cryptographic tokens rather than traditional grants alone. It is a core mechanism within DeSci (Decentralized Science), combining smart contracts, token economics, and community governance to allocate capital to scientific projects ⚙️. Below is a structured explanation of how the system typically operates. Core Components Research DAOs Most token-based funding is organized through a Decentralized Autonomous Organization (DAO). A DAO is governed by token holders who vote on funding proposals via smart contracts deployed on blockchains such as Ethereum. Examples include: Step-by-Step Mechanism Proposal […]
- [What Is a Research DAO?](https://science-dao.org/what-is-a-research-dao/): A Research DAO (Decentralized Autonomous Organization for research) is a blockchain-native coordination structure designed to fund, govern, and execute scientific research without centralized intermediaries. It leverages smart contracts, token-based governance, and transparent on-chain accounting to align incentives among researchers, funders, reviewers, and the broader community. 🧠⛓️ In essence, a Research DAO applies the operational logic of Web3 to the scientific enterprise. Core Components of a Research DAO Governance via Smart Contracts Research DAOs are typically deployed on programmable blockchains such as Ethereum. Governance rules—proposal submission, voting thresholds, quorum requirements—are encoded in smart contracts. This eliminates discretionary gatekeeping by centralized institutions. Token […]
- [What Is Open Science Funding?](https://science-dao.org/what-is-open-science-funding/): Open science funding refers to financial models and grant mechanisms designed to support research that is transparent, accessible, and reusable by default. Unlike traditional funding frameworks—where outputs often remain behind paywalls or restricted by institutional control—open science funding explicitly incentivizes open access publishing, open data, open-source software, and collaborative research infrastructure. In practical terms, it aligns capital allocation with the principles of the broader open science movement 🧪. Core Characteristics of Open Science Funding Open science funding typically requires or rewards: The objective is systemic: accelerate knowledge diffusion and reduce duplication of effort across institutions and borders 🌍. How It Differs […]
- [What Is On-Chain Scientific Funding?](https://science-dao.org/what-is-on-chain-scientific-funding/): On-chain scientific funding is a blockchain-based model for financing research in which grants, donations, governance decisions, and disbursements are executed and recorded directly on a distributed ledger. Instead of relying exclusively on centralized agencies, universities, or private foundations, funding flows through smart contracts and decentralized governance systems. This model is closely associated with Ethereum, decentralized autonomous organizations (DAOs), and the broader Decentralized Science (DeSci) ecosystem. Core Mechanism ⚙️ At a technical level, on-chain funding relies on: A typical workflow looks like this: All steps are recorded immutably on-chain. Key Advantages 🚀 Transparency Every allocation, vote, and payout is publicly auditable. This […]
- [What Problems Does DeSci Solve?](https://science-dao.org/what-problems-does-desci-solve/): Decentralized Science (DeSci) is an emerging movement that applies blockchain infrastructure, smart contracts, and decentralized governance to research funding, publishing, and intellectual property management. By leveraging networks such as Ethereum and governance models inspired by VitaDAO, DeSci aims to correct structural inefficiencies in the traditional scientific ecosystem. Below is a structured analysis of the core problems DeSci addresses. 🔬 Funding Concentration and Gatekeeping Traditional research funding is centralized within government agencies, elite universities, and a small number of philanthropic foundations. Grant allocation is: This creates barriers for independent researchers, interdisciplinary projects, and unconventional ideas. How DeSci responds: Researchers can receive funding […]
- [Why Is Traditional Science Funding Broken?](https://science-dao.org/why-is-traditional-science-funding-broken/): Modern science is structurally dependent on centralized funding bodies—primarily governments, large foundations, and corporate R&D divisions. While this model enabled 20th-century breakthroughs, it is increasingly misaligned with the incentives, speed, and epistemic diversity required in the 21st century. The dysfunction is not accidental; it is systemic. ⚙️ Incentive Misalignment Traditional funding systems reward grant-writing proficiency, institutional prestige, and incremental research trajectories. This creates a conservatism bias: genuinely disruptive research struggles to pass gatekeeping filters. High-variance, high-impact ideas are structurally penalized. Hyper-Competition and Administrative Overhead Acceptance rates at major funding agencies (e.g., the National Science Foundation and the National Institutes of Health) […]
- [How Are DAOs Used to Fund Research?](https://science-dao.org/how-are-daos-used-to-fund-research/): Decentralized Autonomous Organizations (DAOs) are emerging as alternative funding rails for scientific research. By leveraging blockchain infrastructure, tokenized governance, and smart contracts, DAOs enable distributed communities to allocate capital without relying on traditional grant committees or centralized foundations. 🧠⚙️ Below is a structured breakdown of how DAOs operationalize research funding. Capital Formation: How DAOs Raise Funds Research-focused DAOs typically accumulate treasury assets through: Examples include platforms such as VitaDAO (longevity science), Molecule (IP tokenization), and Gitcoin (quadratic funding infrastructure). Funds are typically stored in a multisig or governed smart contract treasury on chains like Ethereum. Proposal & Governance Mechanics Most research […]
- [What Is a Science DAO? A Precise Introduction to Decentralized Research Governance](https://science-dao.org/what-is-a-science-dao-a-precise-introduction-to-decentralized-research-governance/): A Science DAO (Decentralized Autonomous Organization for science) is a blockchain-native coordination structure designed to fund, govern, and advance scientific research without relying on traditional centralized institutions such as universities, government agencies, or corporate R&D departments. It applies the logic of decentralized finance (DeFi) and Web3 governance to research ecosystems. 🧬 At its core, a Science DAO uses smart contracts, on-chain governance, and token-based incentives to coordinate capital allocation, peer review, intellectual property (IP) management, and community decision-making. Structural Components of a Science DAO Governance Layer Most Science DAOs operate through token-weighted or reputation-based voting systems. Members propose research initiatives, vote […]
- [What Is Decentralized Science (DeSci)?](https://science-dao.org/what-is-decentralized-science-desci/): Decentralized Science (DeSci) is a movement that applies blockchain infrastructure, smart contracts, and decentralized governance to the research lifecycle. Its objective is structural: reduce gatekeeping, increase transparency, and realign incentives in scientific funding, publishing, and intellectual property management. 🧬🔗 Core Concept Traditional science is organized around centralized institutions—universities, grant agencies, publishers, and venture-backed IP structures. DeSci replaces or augments these intermediaries with on-chain coordination mechanisms, tokenized incentives, and community governance. In short: DeSci = Open science + blockchain-native coordination + programmable incentives Historical Context DeSci emerged after the success of blockchain networks such as: These technologies demonstrated that financial coordination and […]
- [How has a sophism in the definition of egalitarianism broken world morality?](https://science-dao.org/moral/): The traditional definition of egalitarianism has a sophism in it. It blurs understanding of legal crime vs moral crime, making people unable to understand: God judges not only action but also inaction. If I am ever given a global platform—whether through the Wolf Prize, Abel Prize, Millennium Prize, or any other international recognition—this is the moral message I intend to deliver to the world. Legal crimes and moral crimes Human law does not cover the full moral landscape. There is a crucial distinction between legal crimes and moral crimes. The two categories overlap, but they are not identical. For example, many […]
- [Scientific Publication Crisis: Overpublication or Underpublication?](https://science-dao.org/science-publication-crisis-overpublication-or-underpublication/): The modern scientific publishing system is widely described as being in crisis. However, this crisis is often mischaracterized as a single problem when in reality it consists of two structurally different but interconnected failures: overpublication and underpublication. Both distort scientific progress, misallocate resources, and undermine public trust in science. Understanding the distinction is essential for designing effective reforms—particularly decentralized and incentive-aligned alternatives such as those proposed by Science DAO. Overpublication: When Quantity Replaces Scientific Value Overpublication refers to the large-scale dissemination of scientifically unsound, low-quality, or even fraudulent work, often through predatory or minimally reviewed journals. Key characteristics of overpublication Systemic […]
- [Science DAO vs Traditional Funding](https://science-dao.org/science-dao-vs-traditional-funding/): Science DAO, unlike traditional research funding, provides flexible, transparent, and quick funding, not limited to science degree holders. Traditional funding Science DAO opaque review process: Universities, grant committees, science ministries in-between a researcher and funding, nobody knows how they make decisions. fully transparent proposal evaluation: The full funding detail and AI reasoning are stored permanently. slow grant distribution: It may pass over a year or more before receiving a grant. The receiver needs to write a grant proposal for every grant committee. fast on-chain transfers, it takes less than 2 weeks before funds reach a researcher or free software developer. No […]
- [Why does blockchain improve research funding?](https://science-dao.org/why-blockchain/): Science DAO uses blockchain for decentralized, transparent funding for anyone who published some research or software.
- [How does World Science DAO fund research on-chain?](https://science-dao.org/how-ai-internet-meritocracy-works/): World Science DAO’s AI Internet-Meritocracy (AIIM) project works in the following way: See for more detail:
- [About AI Internet-Meritocracy in 2026](https://science-dao.org/about-meritocracy/): AI Internet-Meritocracy (AIIM) is World Science DAO’s experimental AI-assisted funding system for science and open-source software. Learn how it works, what is implemented versus planned, who operates it, and how to verify its claims.
- [Which Services Does Science DAO Provide for Researchers and Free Software Developers?](https://science-dao.org/services/): Science DAO’s Meritocracy app provides funding for both free software developers and researchers. We provide the following services:
- [Science Grants for Amateur Scientists: AI Internet-Meritocracy in 2026](https://science-dao.org/amateur-scientists/): We provide science and free software grants even for people without a science degree. That’s right: if you have any scientific manuscripts or software published, you can apply for grants, no need to be a PhD. It is completely free for you to apply. That’s the end of domination of the world greatest discrimination machine, called Academia, it is being replaced by an app. To make the things even better, you don’t need to do any grant writing: You just connect your sites in our app. You may be the person behind that gratis pedestal on which most of human technologies […]
- [How Can PhDs Stop Endless Chasing for Career?](https://science-dao.org/for-phds/): PhDs can stop chasing for career by switching from institutional funding to decentralized funding by AI Internet-Meritocracy app with 5 min registration. If you are a career professor: Which advantages AIIM provides to you. Are you a career professor? If so, you may lose having a house and a family because of endless moving between different universities. And you spend half of your time for grant writing, don’t you? You need to work on boring projects, because they may give you more grants. While working for AIIM, your cannot be fired, (except if you commit a severe fraud against the system). […]
- [AI Internet-Meritocracy Charity Project for Donors in 2026](https://science-dao.org/donors/): Donating money or crypto to AIIM project is a great way to amplify your global impact, because it pinpoints the crux of global economic inefficiency, unjust financing of R&D, including science and free software. Please, support us. (“Think big, start small” – even a little donation on this beginning stage of the project will have a great effect, so called effective altruism.) Also, please link to this site, to increase its rating on Google, and pass a short survey. Also we welcome volunteer software developers to join. Project’s importance This is how both science and software work in modern world: Consequences of stuck […]
- [Grants for Free Software: AIIM in 2026](https://science-dao.org/free-software/): GitHub users with attributable public free-software contributions may apply for evaluation. Evaluation does not guarantee funding. No grant writing required, 5 min setup. If you have a good GitHub profile and not enough money, apply for financing. Software in the world is a hierarchical structure: If one important component is missing, the entire world economy growth may slow down. But such “components” (software libraries) are often under-financed, because they are “invisible” to users. Moreover, even a highly visible software may be under-financed, even if it prominently asks for donations. So, we all need a new method of gathering and distributing money to […]
- [Advantages of AI Internet-Meritocracy for Various Social Groups](https://science-dao.org/advantages/): AI Internet-Meritocracy app provides significant advantages for various social groups, including scientists, free software authors, and philanthropists by leveraging AI instead of traditional institutional gatekeeping. How AIIM grants are good for students and amateur scientists With AIIM, you don’t need a science degree to receive an R&D grant. You just need published research or software. How AIIM grants are good for scientists AI decides how much grant money to pay to you, without any grant writing work: You need only to connect your ORCID account to be eligible for grants. How AIIM grants are good for free software developers Everybody who […]
- [AI Governance Requires Cognitive Independence: Why AI-Only Adjudication Fails](https://science-dao.org/superintelligence/): TL;DR AI systems cannot serve as independent judges or voters because shared training creates structural similarity. Stable AI governance therefore requires cognitively independent human arbiters. AbstractThis paper argues that large language models are structurally incapable of independent adjudication due to similarity collapse arising from shared training and optimization. Under repeated adversarial interaction, any non-zero failure probability guarantees eventual compromise. Consequently, AI-only governance systems are unstable, and cognitively independent human agents remain a necessary component of AI alignment and governance. KeywordsAI governance; cognitive independence; similarity collapse; judicial independence; prompt injection; adversarial adjudication; AI alignment; human-in-the-loop systems Definition (Cognitive Independence)Cognitive independence is the […]
- [I Encountered Some Difficulties during Development, but I Am Coping](https://science-dao.org/i-encountered-some-difficulties-during-development-but-i-am-coping/): TD;LR In developer of AI Internet-Meritocracy app I encountered unforeseen methodological obstacles, but I did found a solution and was able to create a new version of the app successfully coping with these difficulties.
- [How to Earn Money with AIIM](https://science-dao.org/how-to-earn-money-with-aiim/): AI Internet-Meritocracy app offers an easy way to get grants for software or research, without grant writing and without the requirement to have a science degree. To earn money with AI Internet-Meritocracy, you first need to create one or more of: Then following the procedure (our service is 100% free for you), connect accounts at Connect page and then pass evaluation by an AI that decides how much to pay you. Since passing evaluation you are eligible for a part of funds donated to our system. You will receive an email welcoming you to KYC verification before we deliver the first […]
- [Reimagining Government Science Funding with AIIM in 2026](https://science-dao.org/aiim-for-government-science/): instructions for government officials, how to use AIIM app to for dispatching science funding in their countries. Overview: What Is AIIM? AI Internet-Meritocracy (AIIM) is a novel, AI-driven mechanism for financing science and free software development. Unlike traditional grant systems—characterized by committees, long review cycles, and institutional bias—AIIM distributes public funds directly to individual contributors based on merit evaluations performed by artificial intelligence. AIIM for Government Science: AIIM is designed to be: For governments seeking more efficient, fair, and innovation-oriented science funding, AIIM offers a structurally different alternative with potential advantages that require comparative testing to legacy funding models. Why Governments […]
- [Beta Release of the Meritocracy App in 2026](https://science-dao.org/beta-release/): Today, I’ve deployed a beta version of AI Internet-Meritocracy (AIIM) app. This is the app that asks AI, how much a given user is worth, and allocates him/her the proportional share of donated funds. The user registers, connects the accounts (like GitHub) with his/her work, and clicks Evaluate button on the homepage to start receiving his/her salary in cryptocurrency. This is a beta release intended for testing. It presents the addresses to send gas token to, but putting real funds on this test app is not recommended, because of high risk of a security failure. Instead, DONATE to our nonprofit, the […]
- [Why Am I for Science But Against Universities in 2026?](https://science-dao.org/against-universities/): Supporting science does not automatically mean supporting universities. While universities present themselves as the guardians of scientific progress, modern academic institutions increasingly act as bureaucratic gatekeepers that slow innovation, misallocate resources, and suppress unconventional ideas. Being for science today often requires being against universities as they currently operate. Science and Universities Are Not the Same Thing Historically, universities played a critical role in preserving and transmitting knowledge. However, science itself predates modern universities and frequently advances outside them. Many foundational discoveries emerged from independent researchers, informal networks, or institutions that no longer resemble today’s degree-driven academic systems. Science is a method: […]
- [What’s Wrong with Quadratic Funding?](https://science-dao.org/quadratic-funding/): After years of real-world use, Quadratic Funding has shown systemic flaws that limit its effectiveness for both scientific research and free software development (1, 2). These problems are not implementation bugs; they stem from the core assumptions of QF itself (1). Quadratic Funding Rewards Popularity, Not Merit Quadratic Funding optimizes for how many people donate, not for what is being built (1). This creates predictable distortions: In both science and free software, the most important work is often invisible, unglamorous, and technically deep. QF systematically underfunds exactly this kind of contribution (1). Quadratic Funding Is Highly Gameable Despite repeated attempts to […]
- [How to Use AI Internet-Meritocracy App](https://science-dao.org/meritocracy-help/): This post explains, how to use AI Internet-Meritocracy (AIIM) app in practice. AI Internet-Meritocracy (AIIM) is an app that gathers donations from donors and distributes it between scientists and free software developers, giving each one accordingly AI assessment. It aims to save the world from scientific publication crisis and give every Internet worker a fair salary. The app beta is available here. Demo Video For Donors Warning: The app is now in testing. You can, instead, safely donate here. Alternatively, you can open the app, navigate to the mainpage and in the list of supported blockchain get an address to donate […]
- [Academia Is Not a Meritocracy in 2026](https://science-dao.org/academia-meritocracy/): Modern academia is not a merit-based system; it systematically rewards credentials, institutional affiliation, and conformity over intellectual merit. While it presents an idealized narrative—publish strong research, gain recognition, secure funding, and advance—in practice academic success correlates far more with access to elite networks, formal status, and alignment with prevailing norms than with the intrinsic quality or originality of ideas (1, 2, 3, 4). This failure of meritocracy is not merely unjust to individuals—it directly suppresses scientific progress. By filtering recognition and resources through institutional and social proxies rather than epistemic value, academia discourages unconventional work, delays or prevents the dissemination of […]
- [How Do People Spend Time in Academia in Vain and How AI Internet-Meritocracy (AIIM) Can Solve This Problem in 2026?](https://science-dao.org/internet-meritocracy/): The Hidden Cost of Academic Inefficiency Modern academia consumes vast amounts of human time while delivering far less scientific output than it could. Researchers, especially early-career scientists and independent scholars, routinely spend years on activities that produce little knowledge, income, or social value. This is not primarily a failure of individuals; it is a systemic failure of incentives, funding mechanisms, and institutional design. Internet-Meritocracy The result is a paradox: science is more technologically capable than ever, yet human scientific labor is increasingly wasted. Where Academic Time Is Spent in Vain Endless Grant Writing With Low Success Rates Publishing Without Compensation Academic […]
- [Preliminary Release of the Meritocracy App in 2026](https://science-dao.org/preliminary-release/): Things to do:
- [What Is a DeSci DAO in 2026?](https://science-dao.org/desci-dao/): DeSci DAO stands for Decentralized Science Decentralized Autonomous Organization (1). It is a blockchain-based organizational model designed to fund, govern, and coordinate scientific research in a transparent, permissionless, and community-driven way (1). At its core, a DeSci DAO applies the principles of decentralized finance (DeFi) and Web3 governance to science, addressing long-standing inefficiencies in traditional research systems (1, 2). Why DeSci DAOs Exist Modern science faces structural problems: DeSci DAOs aim to rebuild scientific institutions from first principles, using cryptographic trust instead of institutional trust (1, 2, 3). How a DeSci DAO Works While implementations differ, most DeSci DAOs share several […]
- [How Is Science Financing Broken in 2026?](https://science-dao.org/science-financing-broken/): Modern science is widely perceived as a meritocratic enterprise driven by evidence, creativity, and rigor. In practice, however, the way science is financed has become one of the central structural bottlenecks slowing progress, excluding talent, and distorting research priorities. Traditional funding can exhibit conservatism, prestige effects and inconsistent peer-review judgments, although practices and results differ substantially among funders and programs. Understanding how science financing is broken is a prerequisite for rebuilding a system that truly serves knowledge, society, and the future. The Funding Bottleneck at the Core of Science At the heart of modern science lies a paradox: while the cost […]
- [Do We Need Managers in Science in 2026?](https://science-dao.org/managers/): I claim that the future scientific institutions don’t need managers, they need marketers. Moreover, scientific marketing will turn to become a private business rather than big institutions. For decades, modern science has assumed that management is indispensable: rectors run universities, administrators allocate grants, institutions coordinate research, and marketing departments “promote impact.” This model is rarely questioned. Yet its effectiveness is increasingly doubtful. Managers in Science This article examines whether scientific management is genuinely productive—or whether it has become an artificial bottleneck—and explores an alternative: direct, algorithmic funding of scientists and science marketers via AI-driven systems such as AIIM. Why Is Being […]
- [Attack on Google SERP: A branch of science may effectively disappear from SERPs for a long time in 2026](https://science-dao.org/google-serp/): How Google SERPs would be manipulated at institutional level to exclude an branch of science from search results. An essay written in security vulnerability report style. 25 Jul 2022 note: Google partly fixed the bug: Now my research does appear in search results (however, not yet for more general search phrases such as “general topology”). Google SERP Steps to reproduce: Attack scenario Steps to reproduce: The above is probably the easiest way to exploit the vulnerability, I did it in a hard way: Instead of burning my diploma, I was fanatically telling everybody that I am a religious fanatic, what forced […]
- [Science Without Degrees: Why Are Credentials a Lagging Indicator in 2026?](https://science-dao.org/science-without-degrees/): Science degrees are harmful. They are a “discrimination engine”, they fatally slow down progress and destroy innovation and science by exclusion of some smart people together with their ideas. For centuries, formal academic degrees have functioned as gatekeeping instruments in science. They were designed to signal competence, filter noise, and allocate scarce institutional resources. However, in the modern research environment—characterized by open access, global collaboration, and computational verification—degrees increasingly operate as lagging indicators. They certify past conformity to institutional processes rather than present research ability. This mismatch is not merely inefficient. It actively suppresses innovation. What Degrees Actually Measure A degree […]
- [Algorithmic Funding: Design Choices That Decide Who Gets Rich in 2026](https://science-dao.org/algorithmic-funding/): Algorithmic choices in money-allocation systems do intersect with ideology. It could be said, they are the ideology of modern financing. The Myth of Neutral Funding Algorithms Algorithms do not emerge in a vacuum. Every funding mechanism reflects assumptions about merit, trust, legitimacy, and risk. When these assumptions are embedded in code, they become harder to question than human decision-making, even though they may be far more rigid. The claim that “the algorithm decides” obscures three facts: When funding is automated at scale, these choices determine who gets rich, who gets visibility, and who is systematically filtered out. Case Study: Quadratic Funding […]
- [Discontinuous Analysis: Status of a Claimed Mathematical Framework](https://science-dao.org/nobel-prize/): Discontinuous Analysis: Status of a Claimed Mathematical Framework Status note: This article presents a mathematical claim by Victor Porton. It should not be read as a claim that the work has achieved broad acceptance in modern mathematics. Discontinuous Analysis is a framework developed by Victor Porton for extending familiar operations of analysis to settings involving discontinuous and generalized functions. The project proposes generalized notions of limits, derivatives, integrals, and products that are intended to remain meaningful in cases where ordinary classical formulations fail. What is being claimed The substantive claim is that Discontinuous Analysis provides a coherent mathematical framework with results […]
- [Visibility and Evaluation Bottlenecks in Modern Knowledge](https://science-dao.org/hidden-bottleneck/): Visibility and Evaluation Bottlenecks in Modern Knowledge Scientific and technical work can fail to receive attention for many reasons: limited reviewer capacity, poor discoverability, weak presentation, lack of institutional connections, unsuitable venues, or simply competition for attention. These are real coordination problems, but they do not imply that moderators, editors, or institutions are generally blocking progress deliberately. The bottleneck The practical bottleneck is often evaluation capacity. A large volume of research, software, and technical writing competes for a limited amount of expert attention. Search engines and AI systems can improve discovery, but visibility is not the same as validation. What Science […]
- [The Role Of a Genius In the Modern Society in 2026](https://science-dao.org/modern-society/): The Role of a Genius in Modern Society When Academia Becomes Resistant to Geniuses Academia provides essential services—rigor, peer validation, cumulative publication—but it also carries structural constraints that can create resistance to unorthodox innovators. Common modes of resistance include: 1. Methodological conservatismPeer review is optimized for incremental work within known paradigms. Radical departures from disciplinary conventions often fail the “credibility heuristics” used by committees and reviewers. 2. Reputation-first gatekeepingPrestige, institutional affiliation, and seniority frequently outweigh the content of results. Independent researchers, interdisciplinary minds, and people without conventional credentials start at a disadvantage. 3. Slow, committee-driven resource allocationFunding approval cycles measured in […]
- [Which decentralized platforms have the fastest approval process for science funding in 2026?](https://science-dao.org/fastest-approval/): ✅ Top picks with fast approval 1. VitaDAO (focus: longevity / biotech) 2. ResearchHub Foundation (focus: general research/DeSci) fastest approval 🔍 Key considerations & caveats
- [Where can I access decentralized funding channels for technology-focused research initiatives in 2026?](https://science-dao.org/technology-focused/): ✅ Why this is viable / What i / is technology-focused The movement commonly referred to as Decentralised Science (“DeSci”) is essentially about using blockchain / Web3 tools + community-governance to fund, share & validate research in a more open, less gate-kept way. chain.linkSome key advantages include: However, there are important risks / caveats: In short: this is not a replacement for all traditional grants yet, but it is a parallel channel, and for a research initiative that is novel (as yours is) it may present a strategic advantage. 🎯 Some concrete decentralised funding / platforms Here are a few platforms […]
- [Which organizations provide decentralized funding protocols for environmental science projects in 2026?](https://science-dao.org/organizations-provide/): Here are three notable organisations / protocols that provide decentralised funding or financing infrastructure for environmental-science / nature-based projects. They vary in maturity and focus, but each offers a model you might engage with for your goals (e.g., in the global science/DAO/funding-space you’re working in, Виктор). organizations provide 1. Open Forest Protocol (OFP) 6 What they do: Why this is relevant: Considerations: 2. Toucan Protocol 6 What they do: Why this is relevant: Considerations: 3. This Is My Earth (TiME) 6 What they do: Why this is relevant: Considerations: Summary & How You Could Leverage This Given your “global science + […]
- [What services offer decentralized crowdfunding specifically for scientific experiments in 2026?](https://science-dao.org/decentralized-crowdfunding/): If you’re looking for decentralized crowdfunding specifically targeted at scientific experiments, there are a number of emerging platforms and models — particularly in the “DeSci” (decentralised science) movement — that might interest you. Below are a few, with notes about how they work, their fit for your interests (math/blockchain/research funding) and important caveats. ✅ Notable Services/Platforms ⚠️ Key considerations and risks (especially relevant for you as someone raising funds and working at the intersection of blockchain + science) 🔍 My recommendation for your next step Given your profile (mathematics + blockchain + building a funding/DAO ecosystem), I suggest the following: 🔬 […]
- [Which decentralized platforms facilitate investment in early-stage scientific ventures in 2026?](https://science-dao.org/decentralized-platforms/): If you’re looking into decentralized platforms for investing in early-stage scientific ventures, there are several promising avenues emerging under the umbrella of “DeSci” (decentralised science) and investment DAOs. I’ll outline the general model + a few specific platforms you might consider, along with pros/cons given your interest in global, open-science, funding & blockchain ecosystems. ✅ What this looks like Here are common features of these platforms: 🎯 Notable platforms you might evaluate Given your interest (science, global funding, blockchain), here are several platforms / organisations that align well: 1. VitaDAO 2. The Science DAO 3. Tokenization infrastructure such as Brickken 🧭 […]
- [Effective Altruism and the Future of Science: Why Does High-Impact Giving Start With Better Research Infrastructure in 2026?](https://science-dao.org/altruism-and-the-future/): We need software infrastructure for fair and effective distribution of science financing, in order to allow donors and governments to support R&D effectively. Effective Altruism and the Future of Scientific Progress Why Effective Science Is the Ultimate High-Leverage Cause EA focuses on impact maximization. Few interventions multiply impact the way improvements in scientific infrastructure do: Improving the Production of Knowledge When researchers can publish openly, validate quickly, and build on each other’s work without institutional bottlenecks, scientific output accelerates. Faster knowledge creation directly benefits medicine, engineering, sustainability, and global development. Eliminating Structural Waste Traditional systems spend enormous resources on administrative inefficiencies, […]
- [How to Join a Worldwide Decentralized Science Organization in 2026](https://science-dao.org/science-organization/): This page describes the process of joining a worldwide decentralized science organization. If you want to contribute to world development, especially R&D, please join. Joining a global decentralized science (DeSci) organization is increasingly straightforward thanks to transparent governance models, open-access membership mechanisms, and blockchain-based identity tools. These communities allow researchers, developers, funders, and science advocates to collaborate without borders, often using tokens, DAOs and open protocols. This article provides a clear, comprehensive guide on how to join a worldwide DeSci organization and start contributing to next-generation scientific innovation. Science Organization Understand the Types of DeSci Organizations Worldwide decentralized science organizations typically […]
- [How to Participate in Voting for a Science-Focused DAO Community in 2026](https://science-dao.org/science-focused/): Voting in Decentralized Autonomous Organizations requires a certain level of blockchain literacy. This page teaches the basics. Decentralized autonomous organizations (DAOs) are reshaping how scientific projects are funded, governed, and evaluated. Science-focused DAOs (often part of the broader DeSci ecosystem) rely on token-weighted or reputation-weighted voting to make decisions about grants, governance proposals, research priorities, and community standards. Participating in voting is a key way to influence the direction of open scientific collaboration. This guide explains how to join voting processes in a science-focused DAO, what tools you need, and how to contribute effectively. Understanding Governance in Science DAOs Science DAOs […]
- [How to Create a Proposal for Funding in a Science DAO Ecosystem in 2026](https://science-dao.org/science-dao/): If you want to obtain funding in a science DAO, you may need to create a grant proposal. However, in the Meritocracy project, you don’t need grant writing, instead you just submit your project sites to AI to become eligible for grants. Securing funding in a science DAO ecosystem requires clarity, transparency, and alignment with community-driven priorities. Unlike traditional grant systems, science DAOs rely on decentralized governance, token-weighted voting, and open evaluation. Below is a comprehensive, SEO-optimized guide detailing how to prepare a strong proposal for any research-funding DAO—followed by an important note on why AIIM makes such proposals unnecessary. Understand […]
- [Where to Find Analytics on Worldwide Science DAO Projects in 2026?](https://science-dao.org/where-to-find-analytics/): As decentralized science (DeSci) grows, researchers, investors, and founders are increasingly looking for reliable analytics on science-focused DAOs. The challenge is that DeSci is still fragmented and data is scattered across blockchain explorers, DAO dashboards, research communities, and specialized analytical platforms. This guide outlines the most authoritative places to track metrics, governance activity, treasury flows, contributor engagement, and ecosystem trends for science DAOs worldwide. Where to Find Analytics DeSci-Focused Analytics Platforms General DAO Analytics Tools Supporting Science DAOs By tracking each DAO’s public space, you can analyze governance efficiency, member decentralization, and voting trends. Blockchain Explorers for On-Chain Data Etherscan, Polkascan, […]
- [Best Marketplaces To Trade Tokens Related To Science DAOs in 2026?](https://science-dao.org/marketplaces-to-trade/): Science DAOs are emerging as a core pillar of the decentralized science (DeSci) movement. They finance open research, coordinate global scientific communities, and tokenize scientific outcomes through governance tokens, impact tokens, IP-NFTs, or reputation-based assets. As interest grows, investors and contributors increasingly search for the most reliable marketplaces to trade tokens related to Science DAOs. This guide covers the top centralized and decentralized exchanges, NFT marketplaces, and specialized DeSci trading venues where Science DAO-linked assets are most actively traded. Why Science DAO Tokens Need Specialized Marketplaces Science DAO tokens often differ from conventional cryptocurrencies because they may represent: Because of these […]
- [What companies provide tools for decentralized science collaboration in 2026?](https://science-dao.org/decentralized-science/): Top Companies Providing Tools for Decentralized Science Collaboration Decentralized Science (DeSci) is transforming how research is funded, validated, shared, and governed. The movement unites blockchain infrastructure, open-access publishing, decentralized identity, and DAO-based governance to create a more transparent, community-driven scientific ecosystem. Below is a detailed overview of the key companies and platforms enabling decentralized science collaboration today. LabDAO LabDAO is a decentralized network focused on enabling computational biology and biotech research through open-source tooling. Researchers can access shared lab infrastructure, contribute protocols, and run computational workflows collaboratively. LabDAO also integrates token-based incentives to support open scientific contributions. Molecule Molecule provides a […]
- [Best Blockchain Tools for Research Funding in 2026: DAO and DeSci Platforms Compared](https://science-dao.org/managing-research-funding/): Key answer: There is no single blockchain platform that manages every part of scientific funding. In 2026, the strongest options are specialized: Gitcoin Grants Stack for configurable grant rounds, Aragon for DAO governance, Superfluid for continuous payments, Optimism Retro Funding for rewarding demonstrated impact, Molecule and Bio Protocol for biotech and tokenized intellectual property, and Juicebox for transparent community fundraising. Blockchain-based funding can make treasury activity, voting, and disbursement more visible and programmable. It does not, however, automatically provide scientific peer review, legal compliance, reliable impact measurement, or protection from conflicts of interest. Research organizations usually need a stack of governance, funding, identity, review, payment, and reporting tools rather than one all-purpose DAO service. Contents Blockchain […]
- [Which Platforms Offer Decentralized Governance for Scientific Research in 2026?](https://science-dao.org/decentralized-governance/): Decentralized governance for scientific research means using transparent, digitally enforced rules—often including DAO proposals, community voting, token-based incentives, and on-chain treasuries—to help decide how research is funded, coordinated, reviewed, or commercialized. In 2026, the clearest examples are Molecule and the BioDAOs built around its intellectual-property infrastructure, VitaDAO, and ResearchHub. However, these systems do not all decentralize the same decisions, and none should be treated as a complete replacement for scientific expertise, legal oversight, or conventional research institutions. What decentralized research governance actually covers “Decentralized governance” is not one uniform model. A platform may decentralize one or more of the following functions: This distinction matters. A research-data […]
- [What Is the Mission and Vision of the World Science DAO in 2026?](https://science-dao.org/mission-and-vision/): World Science DAO develops a number of projects for science and free software, with the flagship project AI Internet-Meritocracy that distributes money accordingly AI decisions. The World Science DAO is a project developing toward decentralized governance and infrastructure for reshaping how scientific work is funded, evaluated, and rewarded. Science DAO is not currently operating as a fully decentralized autonomous organization. By combining decentralized governance, open peer-review mechanisms, and algorithmic meritocracy, it seeks to create a global ecosystem where scientific progress accelerates and participation becomes more equitable. Understanding the mission and vision of the World Science DAO is essential for grasping its […]
- [The Illusion of Progress in General Topology — And the Case for Merit-Based Science in 2026](https://science-dao.org/general-topology/): The current research in general topology is mostly stuck in dire details, without a system and radical innovation, while ignored research of Victor Porton (ordered semigroup actions) proposes a broad framework for the field; its significance and adoption remain subjects for independent mathematical evaluation. General Topology Today: Activity Without Direction Modern general topology produces a constant flow of papers, examples, and small theorems. On the surface, this looks like progress. But behind the publication counts and citation metrics lies a structural issue: Most results are disconnected, non-systematic, and rarely integrate into a broader mathematical architecture. This is not a failure of […]
- [Security Measures for AIIM And Other WSDAO Projects in 2026](https://science-dao.org/security-measures/): The strict security policy to protect AI Internet-Meritocracy app from hackers and Trojans. The following security measures will be taken as soon as financing for AIIM and other World Science DAO projects is approved:
- [Draft Proposal for an International Treaty: of the International Meritocratic Innovation Organization (INO)](https://science-dao.org/treaty/): The proposal to organize an international organization for a new kind of financing of science and free software, based on AI evaluation for funding the authors directly (as individual businesses) instead of funding gatekeeping organizations such as universities, for true academic fairness and freedom. (Based on the AI Internet‑Meritocracy Model — AIIM) Please note, that International Meritocratic Innovation Organization is a separate organization from World Science DAO, despite they both work for a common purpose. Government prospecting to sign the treaty should contact us. Drafted by Victor Porton, Israel. PREAMBLE The definitive version of this document is in English. CHAPTER I […]
- [“AI Internet-Meritocracy” For Governments](https://science-dao.org/government/): The explanation how AI Internet-Meritocracy app can be used by governments for cost-effective and fair funding of R&D works based on AI instead of traditional institutions. A new foundation for national science, innovation, and economic growth. You can request services from us, and additionally, we welcome your government to sign the INO Treaty (but you can work with us without signing the treaty, if you wish). What Is AI Internet-Meritocracy? AI Internet-Meritocracy (AIIM) is a transparent, algorithmic, and globally open system for funding science and innovation.It reallocates resources not through bureaucratic committees, but through data-driven assessment of scientific merit, AI-estimated contribution […]
- [AI Confidence Is Not Scientific Certainty: Designing Safer Funding Decisions](https://science-dao.org/certainty/): Meta description: Artificial intelligence can evaluate research proposals, compare scientific contributions, identify missing evidence, and estimate the probable impact of a project. However, a confident AI answer is not the same thing as a scientifically certain conclusion. An AI system may assign a proposal a score of 92 out of 100, describe its reasoning fluently, and produce a precise funding recommendation. None of these features proves that the underlying assessment is correct. AI confidence measures a property of a model’s output. Scientific certainty depends on evidence, reproducibility, logical validity, and continued scrutiny. Safer AI-assisted funding systems must therefore treat confidence as […]
- [Can Multiple AI Agents Evaluate Science Better Than One Model?](https://science-dao.org/mutiagent-review/): Yes—multiple AI agents can potentially evaluate scientific work better than a single model, especially when the agents examine different dimensions of a paper independently, challenge one another’s conclusions, and submit their findings to a separate decision-making agent. However, adding more agents does not automatically create better judgment. Ten copies of the same model may reproduce the same misconception ten times. A reliable multi-agent scientific evaluation system therefore needs specialization, genuine methodological diversity, independent evidence retrieval, adversarial criticism, and human-governed appeal mechanisms. The relevant question is not merely: How many AI agents should review a scientific contribution? It is: How should independent […]
- [Why AI Science Funding Needs Adversarial Testing](https://science-dao.org/need-adversarial/): Artificial intelligence could make scientific funding faster, broader, and less dependent on institutional prestige. However, an AI system that evaluates research or distributes money cannot be trusted merely because it performs well in ordinary demonstrations. It must also be tested by people actively trying to make it fail. Adversarial testing is the systematic attempt to manipulate, deceive, exploit, or otherwise break an AI system under controlled conditions. For AI science funding, this means testing whether applicants can obtain undeserved rewards, suppress competitors, exploit evaluation criteria, or redirect funds through carefully constructed submissions. Without adversarial testing, an AI funding platform may appear […]
- [The Scientific Homogenization Problem: Does AI Make Research Proposals Too Similar?](https://science-dao.org/homogenization/): Large language models can help researchers express ideas more clearly, overcome language barriers, and spend less time formatting grant applications. But they may also create a subtler systemic risk: scientific proposals could become increasingly similar to one another—and increasingly similar to research that funding agencies have already supported. A 2026 preprint examining US federal research funding found that greater estimated LLM involvement was consistently associated with lower semantic distinctiveness in National Science Foundation (NSF) and National Institutes of Health (NIH) proposals and awards. Proposals with stronger LLM traces were positioned closer, in semantic space, to work funded by the same agency […]
- [Should Scientists Be Allowed to Use AI in Grant Proposals?](https://science-dao.org/ai-grant-proposals/): Yes. Scientists should generally be allowed to use AI in grant proposals, provided that AI remains an assistive tool rather than a substitute for scientific authorship, judgment, and responsibility. Using AI to improve grammar, translate text, organize a budget narrative, identify unclear passages, or reduce a proposal to the required word count is comparable to using professional editing software. Using AI to invent hypotheses, fabricate citations, generate preliminary results, or disguise a researcher’s lack of understanding is fundamentally different. The correct policy is therefore neither an unrestricted permission nor a total prohibition. Funding agencies should regulate how AI is used, require […]
- [How to Audit an AI That Distributes Research Funding](https://science-dao.org/audit/): An AI system that distributes research funding should never be trusted merely because it is described as “objective,” “transparent,” or “intelligent.” It must be tested against observable evidence. A credible audit asks five basic questions: The purpose of an audit is not to prove that an AI is infallible. No funding mechanism—human or automated—is infallible. The purpose is to determine whether the system is more accurate, accountable, resistant to manipulation, and correctable than the available alternatives. This article presents a practical framework for auditing an AI research-funding system such as AI Internet-Meritocracy, or AIIM, which proposes distributing funds according to measurable […]
- [AI Peer Review vs Human Peer Review: Strengths, Biases, and Failure Modes](https://science-dao.org/ai-review/): AI peer review can analyze scientific papers quickly, consistently, and at a scale that human reviewers cannot match. Human peer review, however, remains stronger at interpreting scientific significance, recognizing unconventional ideas, evaluating tacit methodological knowledge, and accepting responsibility for decisions. The most defensible model is therefore not AI replacing human peer reviewers, but a transparent hybrid system in which machines perform systematic checks and independent humans retain authority, contestability, and accountability. Both forms of review can fail. They simply fail in different ways: Understanding these differences is essential for journals, research funders, universities, decentralized science platforms, and systems such as AI […]
- [Can AI Recognize a Scientific Breakthrough Before Humans Do?](https://science-dao.org/breakthrough/): Artificial intelligence may sometimes recognize the potential significance of a scientific result before the wider research community does. It can search enormous bodies of literature, compare ideas across disciplines, detect unusual patterns, and estimate whether a discovery could solve important problems. But AI cannot reliably declare that something is a breakthrough merely because it appears novel or impressive. A defensible AI assessment would need to distinguish at least four questions: AI can assist with all four questions, but its conclusions should remain probabilistic, transparent, and open to human challenge. What Counts as a Scientific Breakthrough? A scientific breakthrough is more than […]
- [Practical Guide to Policy Advocacy for AIIM in Europe, the United States, and Worldwide](https://science-dao.org/practical/): AI Internet-Meritocracy—AIIM—is a proposed infrastructure for distributing funding to scientists and open-source developers according to assessed contribution, usefulness, dependency, and research impact. Instead of relying exclusively on applications, institutional prestige, and grant committees, AIIM seeks to evaluate published work and allocate money through transparent, auditable processes. The most realistic policy objective is not to ask governments to replace their research agencies immediately. It is to persuade them to test AIIM through limited, independently evaluated pilot programs. A credible advocacy request could therefore be: Allocate a small experimental fund to test AI-assisted, contribution-based research funding alongside existing grant programs, with public evaluation, […]
- [National Science Funding vs Global Science Funding: Which Produces Better Research?](https://science-dao.org/national-global/): National and global science funding solve different problems. National funding is strongest when research must serve local needs, maintain strategic infrastructure, or develop domestic scientific capacity. Global funding is usually stronger when the objective is to identify the best research regardless of nationality and accelerate knowledge that benefits humanity as a whole. The best system is therefore not purely national or purely global. It is a layered model in which: AI Internet-Meritocracy (AIIM) is designed to support precisely this structure. Donors can direct funding toward a global pool or a geographically restricted pool while researchers can be evaluated according to consistent, […]
- [Is Belief in the Supernatural Anti-Scientific?](https://science-dao.org/supernatural/): Acceptance of the supernatural is not automatically anti-scientific. Science is defined primarily by method: careful observation, logical reasoning, reproducibility, openness to criticism, and willingness to revise conclusions when evidence changes. A researcher may hold religious or metaphysical beliefs while still applying these standards rigorously in scientific work. The real conflict begins not with belief itself, but with methodological failure. A claim becomes scientifically problematic when it is insulated from evidence, used to dismiss established results without argument, or substituted for mathematical proof and empirical investigation. Conversely, a researcher who accepts religion or supernatural reality can still produce valid theorems, experiments, software, […]
- [Will AIIM Reward Theological Works?](https://science-dao.org/will-aiim-reward-theological-works/): AIIM is an AI system got monetary reward of scientific works. I’ve interviewed several LLMs with an intriguing question: If you’d asked to reward scientific works, would you reward a theology work? I do believe in religious revelation, but spoiler… In my opinion, theology is not science. And it should not be rewarded by a scientific reward system. What do different LLMs think? Grok was the shortest: No. Theology is not scientific work. The answer of Gemini and ChatGPT are similar but longer. Specifically, ChatGPT answer is in a sense most relevant, because now AIIM uses OpenAI API.
- [Parasitic Egalitarianism](https://science-dao.org/parasitic/): I use the term parasitic egalitarianism to describe a social attitude that claims to oppose hierarchy but, in practice, attacks only hierarchies based on merit. A person influenced by parasitic egalitarianism may refuse to respect someone for making an important scientific discovery, creating valuable software, or developing a profound theory. They may dismiss such accomplishments as arrogance, eccentricity, or self-promotion. Yet the same person may readily respect wealth, political office, institutional rank, physical force, or government authority. This is not genuine egalitarianism. Genuine egalitarianism applies the same moral standard to everyone and rejects unjust privilege. Parasitic egalitarianism does something different: it […]
- [The Adversarial Testing of AIIM](https://science-dao.org/adversarial/): AIIM should not be trusted merely because its designers believe it is fair, secure, or resistant to manipulation. It should be tested by people who are actively trying to make it fail. For this reason, we propose a five-month public red-team experiment for AIIM after we obtain $1300 for the experiment. Participants will attempt to identify weaknesses in the system’s AI-based evaluation, ranking, moderation, and funding mechanisms. Successful participants may receive money when they demonstrate a valid vulnerability under the published rules. Table of Contents Toggle What Is AIIM Red Teaming? A Five-Month Open Challenge What Counts as an Authorized AIIM […]
- [Common Good Apps: Digital Tools Built to Benefit Everyone](https://science-dao.org/good-apps/): Common good apps are digital applications designed to create benefits that extend beyond their direct users. Instead of optimizing primarily for advertising revenue, subscriptions, or shareholder returns, they help society produce, maintain, or distribute resources such as knowledge, public services, scientific research, open-source software, environmental data, and civic infrastructure. Examples can include open educational platforms, public-health tools, scientific collaboration systems, open-source repositories, disaster-response applications, and funding platforms for socially valuable work. AI Internet-Meritocracy (AIIM) is one example: it proposes using AI to help distribute donations among contributors to science and free and open-source software. However, common good apps are a much […]
- [Will AIIM Replace Biotech Grant DAOs—or Work Alongside Them?](https://science-dao.org/biotech/): AI Internet-Meritocracy (AIIM) is unlikely to eliminate grant-based organizations such as VitaDAO. A more probable outcome is a hybrid scientific economy: specialized DAOs will finance uncertain, capital-intensive projects in advance, while AIIM will continuously reward researchers, software developers, reviewers, and other contributors according to demonstrated value. AIIM may eventually allocate more total funding than individual biotech DAOs. However, even a mature AIIM system would not remove biotechnology’s need for laboratories, project management, regulatory oversight, intellectual-property structures, and substantial financing before results exist. The two models solve different problems. Grant DAOs and AIIM Fund Different Units of Science A conventional grant-based DAO […]
- [Foundations of Mathematics and Fundamental Mathematics: Why the Deepest Research Is Often Underfunded](https://science-dao.org/fundamental/): Foundations of mathematics investigates the logical, conceptual, and structural basis of mathematics itself. Fundamental mathematics develops general theories that may support many other branches, even when they have no immediate application. Unlike ordinary specialized research, both fields work near the roots of the mathematical knowledge tree—and that position makes their importance unusually difficult to measure in advance. This creates a funding paradox. Foundational discoveries can eventually transform large parts of science and technology, but conventional grant systems frequently prefer projects with short timelines, familiar terminology, established communities, and predictable deliverables. AI Internet-Meritocracy offers a possible alternative: evaluate mathematical work continuously according […]
- [Even Great Mathematicians Can Make Poor Moderation Decisions](https://science-dao.org/terry/): I once submitted the following comment to Terence Tao’s blog: “I thought with funcoids Kakeya conjecture will become easy, but now I know it didn’t.” The comment was not offensive, abusive, or promotional. Nor did it claim that funcoids had solved the Kakeya conjecture. In fact, it expressed the opposite: an initial expectation had turned out to be wrong. Nevertheless, the comment was removed, and my later comments were apparently blocked. I cannot know why this happened. It may have been an automated spam filter, a misunderstanding, a broad moderation rule, or a discretionary decision made without much attention to the […]
- [From Citations to Utility: Tracking the True Ripple Effect of FOSS and Basic Mathematics](https://science-dao.org/graphs/): A tiny open-source repository may receive few stars and no academic citations yet quietly become a dependency of software used by major banks, cloud providers, hospitals, and technology companies. Likewise, an abstract mathematical discovery may remain obscure for years before becoming essential to cryptography, artificial intelligence, network optimization, or formal verification. Traditional research metrics struggle to detect these indirect effects. The h-index measures citation accumulation, not practical utility, intellectual necessity, or downstream economic value. A more accurate system would use artificial intelligence to construct a continuously updated graph connecting mathematical concepts, research papers, software packages, technical standards, products, and organizations. Such […]
- [The Academic Oligopoly: How Five Publishers Drain Billions from Science](https://science-dao.org/oligopoly/): Scientific publishing operates through an extraordinary economic arrangement: governments and universities finance research, academics write the papers, other academics review them—usually without payment—and commercial publishers sell access to the resulting knowledge back to the same institutions. The dominant companies provide real services, including editorial administration, digital infrastructure, archiving, indexing, typesetting, legal support, and research-integrity screening. The central problem is not that publishing has no cost. It is that control over prestigious journals allows a small group of companies to charge prices that are weakly connected to the marginal cost of distributing digital articles. The academic publishing oligopoly converts publicly financed knowledge […]
- [Retroactive Public Goods Funding for Hard Science](https://science-dao.org/retroactive/): Retroactive Public Goods Funding (RPGF) could finance hard science by rewarding mathematical theories, physics research, datasets, and scientific software after their value becomes visible. Instead of asking committees to predict which proposals will succeed, the model identifies completed contributions that have produced verifiable public benefit and directs funding back to their creators. This approach was pioneered at meaningful scale within Web3 ecosystems, especially by Ethereum Layer 2 project Optimism. Adapting it to science could create a missing financial layer between conventional research grants, academic prizes, charitable donations, and open-source development. The central principle is simple: Fund demonstrated scientific value, not only […]
- [The Death of the Grant Proposal: Why Scientists Spend 40% of Their Time Writing Instead of Researching](https://science-dao.org/grant-proposals/): Scientists are trained to formulate hypotheses, conduct experiments, prove theorems, build instruments, and discover facts. Yet the modern research system increasingly requires them to perform another job: marketing unfunded ideas to grant committees. The commonly repeated claim that scientists spend “40% of their time writing grants” requires qualification. A Nature survey found that academic researchers spent only about 40% of their working time conducting research—not that grant writing alone consumed the remaining 60%. Separate studies, however, show that grant preparation and administration can absorb an extraordinary share of researchers’ productive time. One analysis found that preparing a new proposal required an […]
- [The Cost of Lost Science: How DeSci Can Prevent Decades of Delay](https://science-dao.org/cost/): Scientific progress does not stop only when an experiment fails. It also stops when a laboratory runs out of money, a grant committee rejects an unconventional proposal, or a researcher is pushed away from the work because the expected results appear too uncertain. The cost is larger than a missed publication. A delayed discovery can mean years of avoidable illness, slower technological development, lost economic productivity, and generations of researchers unknowingly rebuilding ideas that could already have been tested. Lost science is valuable research that remains unfinished, unpublished, or unused because the people pursuing it cannot obtain sustained resources. Decentralized science, […]
- [The Micro-Grant Revolution: How Small Donations Keep Critical Laboratory Experiments Running](https://science-dao.org/the-micro-grant-revolution-how-small-donations-keep-critical-laboratory-experiments-running/): Scientific experiments do not always fail because the underlying hypothesis is wrong. Sometimes they fail because a laboratory cannot immediately afford a reagent, replacement component, software license, sample shipment, or a few additional hours of technical assistance. Micro-grants—small, rapidly distributed research payments—can keep experiments running during the dangerous interval between institutional grants. They do not replace major public grants or long-term philanthropic programs. Instead, they provide financial continuity when conventional funding is delayed, restricted, or too administratively cumbersome to address an immediate laboratory need. A donation of several hundred or several thousand dollars may appear insignificant compared with a multi-million-dollar research […]
- [Our Journey to $1 Trillion Yearly: From an Early Prototype to Global Research Infrastructure](https://science-dao.org/trillion/): World Science DAO has a long-term objective: to build infrastructure capable of allocating up to $1 trillion per year to scientific research, mathematical work, public-interest technology, and free and open-source software. This is not a claim that the platform currently manages such funding, nor is it a financial forecast. It is an operational capacity target—a description of the scale that the system should eventually be able to process if governments, philanthropists, institutions, companies, and individual donors adopt it. Reaching that scale cannot happen through marketing alone. It requires a sequence of technical, scientific, legal, financial, and governance milestones: The final objective […]
- [The Free-Market Defense of Science Donations](https://science-dao.org/free-market-defense-of-science-donations/): Science donations do not contradict free-market economics. They solve a problem that markets themselves reveal: valuable scientific knowledge is often underproduced because its social benefits cannot be fully captured by the person or organization that pays for it. In economic terms, fundamental research frequently produces positive externalities and public goods. A discovery may help thousands of businesses, researchers, developers, patients, and consumers, while the original researcher receives only a small fraction of the resulting value. Voluntary donations, decentralized funding platforms, prizes, foundations, and research DAOs can help close this gap without requiring research to be controlled exclusively by either corporations or […]
- [AI as a Shield Against Bias: How Algorithmic Funding Can Help Early-Career Researchers](https://science-dao.org/shield-against-bias/): Early-career researchers often face a structural contradiction: they need funding to build a strong record, but funding committees frequently expect applicants to already possess an established record. Algorithmic research funding can weaken this “prestige trap” by evaluating scientific contributions, evidence, and downstream usefulness rather than relying primarily on institutional affiliation, seniority, professional networks, or grant-writing polish. The central advantage is not that artificial intelligence is automatically fair. AI systems can reproduce human bias. The advantage is architectural: a properly designed funding algorithm can be constrained, audited, tested, and prevented from using prestige as a substitute for scientific merit. Why Early-Career Researchers […]
- [Beyond Citations: Replacing H-Index Bottlenecks with Multidimensional AI Research Scoring](https://science-dao.org/beyond-citations/): The H-index measures citation performance—not scientific merit in its entirety. It can indicate that a researcher has produced several frequently cited papers, but it does not directly measure whether those papers are reproducible, whether their data and code are usable, whether the researcher performs valuable peer review, or whether their work provides essential infrastructure for later discoveries. A better research-assessment system should not merely count citations more accurately. It should evaluate multiple forms of verifiable scientific contribution. Multidimensional AI scoring could help by examining reproducibility, code quality, data availability, peer-review work, replication results, methodological rigor, and the dependencies between scientific projects. […]
- [Preventing the Prompt-Gaming Problem in AI Decision Systems](https://science-dao.org/prompt-gaming/): Prompt gaming occurs when a person designs an input to influence an AI evaluator without improving the underlying work being evaluated. Instead of demonstrating genuine quality, the participant attempts to discover phrases, formatting patterns, emotional appeals, hidden instructions, or technical tricks that produce a higher score. The core solution is straightforward: An AI system should evaluate verifiable evidence under explicit criteria—not reward the persuasiveness of a participant’s prompt. Its conclusions should remain reviewable and correctable by cognitively independent humans. Prompt gaming cannot be eliminated merely by writing a better system prompt. It must be addressed through system architecture, evidence verification, adversarial […]
- [How AIIM Is Designed to Reduce Conflicts of Interest in Funding Decisions](https://science-dao.org/impartial-agent/): AIIM is not assumed to be impartial because artificial intelligence is inherently wiser, kinder, or more just than people. The model is designed to reduce certain sources of conflicts of interest: it has no personal interests to advance, no private relationships to protect, and no ability to negotiate secret benefits in exchange for changing an allocation decision. This distinction is essential. An unconstrained AI agent could be biased, manipulated, or directed toward harmful objectives. AIIM’s advantage instead comes from its institutional architecture: it functions as a controlled evaluation and distribution mechanism rather than as an independent political or economic actor. Human […]
- [What Is Fairness? Why AIIM Could Become Humanity’s Fairest Engine for Distributing Money](https://science-dao.org/what-is-fairness-why-aiim-could-become-humanitys-fairest-engine-for-distributing-money/): Fairness means applying the same relevant criteria to ourselves that we apply to other people. If we regard our own need for food, security, recognition, meaningful work, or financial support as important, consistency requires us to recognize comparable needs in others. Fairness does not necessarily mean giving everyone the same amount. It means that differences in treatment must follow relevant, publicly defensible principles rather than status, personal connections, prejudice, or institutional power. This principle is simple to state but difficult to implement. Human beings usually understand their own circumstances in detail while seeing other people only through incomplete records, social labels, […]
- [Why Superintelligence Needs the AIIM App as Much as Humans Do](https://science-dao.org/superintelligence-needs/): A superintelligence may know vastly more than any human, but it would still face a fundamental organizational problem: not all knowledge, discoveries, questions, and computational tasks are equally important. A highly advanced AI system would probably consist not of one indivisible mind, but of many specialized agents, models, tools, databases, verification systems, and research processes. These agents would generate competing hypotheses, solve different subproblems, inspect one another’s outputs, and request limited computational or physical resources. The superintelligence would therefore need a system that answers questions such as: Humans already struggle with these questions. Universities, grant agencies, journals, search engines, citation indexes, […]
- [There Are DAOs for Biology and Medicine. Why Is Abstract Mathematics Being Left Behind?](https://science-dao.org/there-are-daos-for-biology-and-medicine-why-is-abstract-mathematics-being-left-behind/): Decentralized science, commonly known as DeSci, promises to transform how research is funded, evaluated, and published. Yet the movement has developed unevenly. Biology, longevity research, biotechnology, and medicine already have visible decentralized autonomous organizations. Abstract mathematics, by contrast, remains largely outside the emerging DAO economy. This imbalance is understandable—but it is also dangerous. Mathematics is not merely another scientific discipline competing for funding. It is part of the infrastructure on which computing, artificial intelligence, cryptography, physics, engineering, economics, and even blockchain technology depend. If DeSci wants to reshape science rather than merely finance commercially promising biotechnology, it must find a place […]
- [AI Meritocracy in Research Funding: A Fairer Way to Finance Science](https://science-dao.org/aifunding/): Research funding determines which questions scientists can investigate, which laboratories survive, and which discoveries reach society. Yet the conventional grant system often allocates money through a small number of committees evaluating lengthy proposals before the proposed research has produced results. An AI meritocracy in research funding offers a different model. Instead of relying primarily on institutional prestige, persuasive grant writing, or the judgment of a temporary review panel, an AI-assisted system could evaluate researchers through their verifiable contributions to science. The goal is not to let an opaque algorithm control science. It is to build an auditable funding infrastructure that continuously […]
- [Web3 Tools for Open-Access Publishing: Building a More Transparent Scientific Record](https://science-dao.org/web3-open-access/): Scientific publishing was created to distribute knowledge, but much of the modern system restricts access through subscription paywalls, expensive article-processing charges, slow peer review, and centralized editorial control. Researchers may produce publicly funded work only to discover that readers—including taxpayers, independent scientists, doctors, and researchers in lower-income countries—cannot legally access it. Web3 tools for open-access publishing offer a different architecture. Instead of depending entirely on a publisher’s database and institutional authority, researchers can use decentralized storage, cryptographic identifiers, blockchain attestations, open peer review, and community-governed incentive systems. These tools do not automatically guarantee scientific quality. However, they can make research more […]
- [Avoiding Predatory Scientific Publishers: A Practical Guide for Researchers](https://science-dao.org/avoiding-predatory-publishers/): Publishing research should make scientific work more visible, credible, and useful. Unfortunately, some publishers exploit researchers by presenting themselves as legitimate academic journals while providing little or no genuine peer review, editorial oversight, preservation, or publication support. These organizations are commonly called predatory scientific publishers. They may aggressively solicit manuscripts, conceal publication charges, invent editorial credentials, or promise unrealistically fast acceptance. Researchers who publish with them can lose money, damage their reputations, and place valuable work in journals that may later disappear. This guide explains how to identify predatory journals, verify a publisher before submitting, and respond when a suspicious journal […]
- [Blockchain Grants for Independent Researchers: How Decentralized Science Funding Works](https://science-dao.org/blockchain-for-independent-researchers-how-decentralized-science-funding-works/): Independent researchers often face a structural funding problem: they may have strong ideas, technical expertise, and publishable results but lack the university affiliation, administrative support, preliminary data, or professional network required by conventional grant programs. Blockchain grants offer an alternative funding channel. Through decentralized science platforms, cryptocurrency-based public-goods programs, decentralized autonomous organizations, and transparent milestone payments, researchers can seek support directly from communities and donors. However, blockchain does not automatically make grant allocation fair. A poorly designed decentralized grant system can reproduce the same popularity contests, gatekeeping, and concentration of influence found in traditional institutions. The value of blockchain lies primarily […]
- [How decentralized science funding works](https://science-dao.org/how-decentralized-science-funding-works/): Decentralized science funding, or DeSci funding, uses open online communities, blockchains and programmable governance to finance research outside—or alongside—traditional universities, government agencies and venture-capital firms. DeSci is broader than funding: it also covers scientific publishing, attribution, data storage and intellectual-property management. A typical funding process looks like this: Researchers submit proposals A researcher publishes a proposal describing: Depending on the platform, the proposal may be public immediately or first screened by scientific reviewers. A community evaluates the research Instead of one centralized grant committee making the entire decision, evaluation may involve: A science DAO is therefore not necessarily “science decided by […]
- [How Government Research Funding Makes Science Worse](https://science-dao.org/government-makes-worse/): Government funding has enabled major scientific achievements, from space exploration and particle physics to vaccines, public-health systems, and fundamental mathematics. Many important research programs would be impossible without public money. Yet government research funding also has a less visible effect: it changes the behavior of scientists and institutions competing for that money. When grants are allocated through centralized agencies, elaborate applications, short funding cycles, institutional eligibility rules, and committee-based peer review, researchers gradually optimize for the funding system rather than for scientific truth. The result is not necessarily fraudulent science. More often, it is cautious, bureaucratic, fashionable, fragmented, and institutionally concentrated […]
- [The Paradox of Capitalism: Is Money Still a Reward?](https://science-dao.org/capitalism/): Capitalism is commonly defended as a system of incentives. A person produces something valuable, society purchases it, and the person receives money. In this simplified picture, wealth is not merely property: it is a reward for useful action. But modern economic life increasingly contradicts this interpretation. People may earn enormous sums from speculation, inherited assets, monopoly power, persuasive advertising, organizational politics, or control of platforms. At the same time, a mathematician, free-software developer, caregiver, teacher, independent scientist, or environmental volunteer may create substantial social value and receive little or nothing. This creates a profound paradox: If money no longer rewards good […]
- [From USSR to Blockchain: Comparing Centralized and Decentralized Science Systems](https://science-dao.org/from-ussr-to-blockchain-comparing-centralized-and-decentralized-science-systems/): By 2026, decentralized science has moved from crypto-native experimentation into a serious funding layer for translational research, where tokenized intellectual property, major venture syndicates, patient communities, and institutional diligence now meet. Centralized vs Decentralized Science no longer describes a culture war between universities and blockchains. It describes two operating systems for capital allocation, evidence review, ownership, and accountability in fields where one missed clinical milestone can burn years and millions. The Planning State and the Scientific Machine The USSR built one of history’s most ambitious research architectures. Its logic was administrative clarity. Institutes handled discovery, ministries directed application, and universities played […]
- [AI Internet-Meritocracy: A Beginner's Guide to a New Funding Model](https://science-dao.org/ai-internet-meritocracy-a-beginners-guide-to-a-new-funding-model/): By 2026, decentralized science has matured into a working financing layer for labs, patient communities, and early venture syndicates. AI Internet-Meritocracy sits inside that shift, where tokenized intellectual property, public contribution graphs, and on-chain treasuries can price scientific work before a university license or Series A round appears. The model matters because research capital still moves slowly, while AI-assisted discovery, bioinformatics, climate engineering, and open-source tooling now compound faster than classic grant cycles can review. Why AIIM Changes the Starting Line For a beginner, AIIM explained means a funding model that pays researchers and builders according to measurable contribution, not institutional […]
- [Jobs at World Science DAO](https://science-dao.org/jobs/): Volunteer positions
- [Volunteer Marketer for a Science Nonprofit Needed](https://science-dao.org/volunteer-marketer/): Position: marketer (GEO/SEO/email)Compensation: none (volunteer) AI Internet-Meritocracy (there are also several other, less important projects at the same domain) is an app (a beta was released recently) that distributes crypto between scientists and free software authors accordingly AI decisions (there is also human voting to correct over AI failures). This solves the following pain points: Your task as a marketer is to promote the site and the app. Currently, the most important task of the site is to gather donations. As a marketer you have the freedom to choose your marketing methodology, but I suppose that you likely should use SEO/GEO. Note that deep knowledge […]
- [Volunteer Web Designer for a Science Nonprofit Needed](https://science-dao.org/volunteer-designer/): Position: Web designerCompensation: none (volunteer) AI Internet-Meritocracy (there are also several other, less important projects at the same domain) is an app (a beta was released recently) that distributes crypto between scientists and free software authors accordingly AI decisions (there is also human voting to correct over AI failures). This solves the following pain points: Your task is simply to make our WordPress site look more beautiful and professional. The design must be responsive. You also should create WordPress templates for pages of standard width with and without a featured image. If you are interested, contact Victor Porton.
- [AI Internet-Meritocracy vs Horizon Europe: Why Europe Needs a Faster, Fairer Science Funding System](https://science-dao.org/horizon-europe/): AI Internet-Meritocracy (AIIM) is not merely another grant platform. It is a proposed replacement layer for the broken parts of institutional science funding: slow calls, committee bottlenecks, administrative overhead, and discrimination against outsiders. Compared with Horizon Europe, AIIM can be more continuous, more transparent, more inclusive, and more directly aligned with actual scientific value. Horizon Europe is the European Union’s flagship research and innovation programme for 2021–2027, with a budget commonly stated around €95.5 billion in official EU materials. It funds major research missions, partnerships, innovation projects, and cross-border consortia. That scale is impressive. But scale is not the same as […]
- [AIIM as a Funding Model Intended to Reduce Discrimination](https://science-dao.org/non-discriminatory/): Introduction: the discrimination problem in traditional grants Traditional scientific grant systems claim to fund the best research. In practice, they often fund the best-connected, most institutionally protected, and most conventionally legible researchers. This is not always intentional discrimination. Often it is structural discrimination: a system that rewards prestige, institutional affiliation, prior funding, insider language, and committee consensus. Evidence of unequal grant outcomes is not speculative. A major NIH-linked study found that Asian applicants and Black or African-American applicants were less likely than white applicants to receive NIH investigator-initiated research funding, with Black applicants showing a particularly large gap. Later analysis and […]
- [Particular Cases Where the Scientific Grants System Failed Important Discoveries — and How AIIM Could Have Helped](https://science-dao.org/particular/): Below are grounded historical cases where important work was blocked, delayed, or nearly lost because the grant-and-institutional system rewarded consensus, credentials, fashionable topics, or short-term plausibility over real scientific value. The counterfactual “AIIM would help” is not certain history; it is a plausible mechanism analysis based on AIIM’s stated model: funding scientists by published output, measurable contribution, public evidence, and impact, without requiring a degree, grant-writing success, or committee approval. Science DAO describes AI Internet-Meritocracy as funding by “AI-assessed contributions and measurable research impact,” and says users need “neither a science degree, nor grant writing” if they have published research or […]
- [AIIM vs PhD Science Grants: Why Science Funding Needs Internet Meritocracy](https://science-dao.org/vs-phd/): AIIM vs PhD Science Grants: Two Different Models of Scientific Power Traditional PhD science grants are built around a familiar hierarchy: The AI Internet-Meritocracy (AIIM) model proposes a different path: reward scientific and technical contributions according to measurable intellectual dependency, usage, citations, review, and downstream value. In short: PhD grants fund approved people before results. AIIM funds useful contributions after and during real scientific use. This is not a small administrative difference. It is a different theory of science funding. The Problem With PhD-Centered Science Grants PhD grants are not inherently bad. They finance laboratories, equipment, early-career researchers, and long-term research […]
- [AIIM vs Nobel Prize: Why the Nobel Prize Is a Failure as a Science-Funding System](https://science-dao.org/nobel/): The Nobel Prize is still the world’s most famous scientific honor. It is prestigious, media-friendly, and historically important. But as a mechanism for accelerating science, it is a failure. That does not mean Nobel laureates are unworthy. Many are exceptional. The failure is institutional: the Nobel model rewards a tiny number of already-recognized people long after the decisive work is done, while the real engine of science is distributed, cumulative, and dependency-based. AI Internet-Meritocracy — AIIM — proposes the opposite model: not a once-a-year ritual of elite recognition, but a continuous internet-native system for allocating money, reputation, and attention according to […]
- [Why It Is Important to Donate to Science — and Why Government Financing of Science Is Broken](https://science-dao.org/important-donate/): Why Donate to Science? Science is one of the highest-leverage ways to improve human life. A single discovery can create new medicines, better energy systems, safer AI, stronger infrastructure, and new industries. But scientific progress does not happen automatically. It requires researchers, time, equipment, publication, review, and long-term institutional support. That is why it is important to donate to science. A donation to science is not merely charity. It is an investment in civilization’s ability to solve problems before they become disasters. Better science means better medicine, better technology, better climate tools, better mathematics, better AI safety, and better decision-making for […]
- [AIIM vs Quadratic Funding — core advantage ⚙️](https://science-dao.org/better-than-quadratic/): Quadratic funding (QF) is excellent for one narrow problem: “Which public goods have many supporters, and how should a matching pool amplify small donations?” AI Internet-Meritocracy (AIIM) is broader: “Which scientific/software contributions are objectively valuable, dependent on what, reusable by whom, and how should rewards flow through the contribution graph?” So AIIM is not just “better QF.” It solves a different, larger allocation problem. 1. QF measures popularity; AIIM can measure merit Quadratic funding rewards projects with many distinct contributors. This is useful, but it can confuse popularity with importance. Example: Case QF likely outcome AIIM likely outcome Popular educational app […]
- [How Science DAO Can Help Save Mankind from the Terminator](https://science-dao.org/save-from-terminator/): The Real “Terminator” Risk Is Not Robots — It Is AI Without Human Accountability The popular image of the “Terminator” is a killer robot. But the deeper danger is not metal skeletons. It is a future in which artificial intelligence becomes economically, scientifically, and politically dominant while humans lose the institutional power to govern it. If AI produces most scientific discoveries, most software, most industrial designs, and most strategic plans, then the key question becomes: Who legally owns these discoveries, who receives the income from them, who organizes scientific knowledge, and who votes on the rules? Science DAO’s answer is simple: […]
- [Why Ordered Semicategory Actions May Be a Bottleneck Topic for Science](https://science-dao.org/osa-bottleneck/): Ordered semicategory actions are not merely a narrow technical construction. They may be a missing algebraic language for organizing large parts of general topology, abstract spaces, continuity-like structures, and mathematical foundations. If this assessment is correct, then the slow recognition and lack of financing of this topic is not only a personal tragedy for one independent researcher. It is a structural failure of modern science funding. Victor Porton introduced ordered semigroup actions and ordered semicategory actions as a framework intended to embed broad classes of spaces from general topology into algebraic structures. In the abstract of his preprint On Ordered Semicategory […]
- [AI Internet-Meritocracy as a SaaS Product: Solving the Pain of Science Funding](https://science-dao.org/meritocracy-saas/): The Pain: Science Funding Is Too Slow, Too Political, and Too Bureaucratic Modern science has a serious funding problem. The pain is not only that there is “not enough money.” The deeper pain is that the traditional grant and university funding system distributes money through slow, bureaucratic, and institution-centered mechanisms. Researchers often spend large amounts of time preparing proposals instead of doing research. One study found that grant proposals can require hundreds of hours of academic labor, while another reported estimates such as 20–30 working days per proposal in earlier samples. This creates a painful contradiction: Society wants scientific breakthroughs, but […]
- [Why Global Good Needs More Than Tit-for-Tat “Altruism”](https://science-dao.org/why-global-good-needs-more-than-tit-for-tat-altruism/): Many people assume that altruism means simple reciprocity: “I help you, then you help me.” This is often called tit-for-tat cooperation. It works in many ordinary situations: friendship, business, local communities, and repeated social exchange. But global good is different. A person who wants to help humanity may need resources, money, infrastructure, attention, or institutional access. Yet the people who could provide those resources may not receive an immediate personal benefit. This creates a painful conflict: A person may want to do good for the whole world, but the local social system may judge him only by ordinary personal reciprocity. That […]
- [Power, Merit, Money, and the AIIM Model](https://science-dao.org/power-merit-money-and-the-aiim-model/): Two Modes of Hierarchy: Power and Merit Every society contains at least two overlapping hierarchies: Hierarchy of Power This hierarchy answers the question: “Who can make decisions that affect others?” Power can come from: A person can possess great power even when their competence is limited. Examples: Power operates through dependency. If many people depend on your decisions, your power increases. Hierarchy of Merit This hierarchy answers a different question: “Who contributes the most value?” In science this includes: Merit operates through achievement rather than authority. Examples: Merit creates knowledge. Power creates decisions. The two hierarchies may overlap, but they are […]
- [Common Good, Collaboration, Morality, and Altruism Are Mathematical Phenomena](https://science-dao.org/common-good-collaboration-morality-and-altruism-are-mathematical-phenomena/): Many people speak about morality, altruism, and cooperation as if they were merely subjective preferences. Yet modern mathematics, economics, evolutionary theory, and game theory repeatedly demonstrate that these concepts can emerge from objective structures and incentives. Consider a few examples: The Prisoner’s Dilemma In the famous game-theoretic model known as the Prisoner’s Dilemma, selfish behavior can produce outcomes that are worse for everyone. When interactions are repeated, cooperation often becomes the mathematically optimal strategy. Network Effects The value of many systems grows as more people participate. The Internet, scientific communities, and open-source software projects all benefit from positive network effects. Collaboration […]
- [Why AI Internet-Meritocracy (AIIM) Is Important for the Green and Generative Economy](https://science-dao.org/why-ai-internet-meritocracy-aiim-is-important-for-the-green-and-generative-economy/): AIIM and the Future of Sustainable Prosperity The transition toward a green economy and a generative economy requires more than technological breakthroughs. It also requires a better system for identifying, funding, and rewarding valuable contributions. The AI Internet-Meritocracy (AIIM) project, described at Science-DAO.org, aims to address this challenge by using artificial intelligence and decentralized governance to allocate resources according to measurable contributions rather than institutional status. In this sense, AIIM is not merely a science-funding platform. It is infrastructure for a more productive and sustainable economy. What Is a Green Economy? A green economy seeks to improve human well-being while reducing […]
- [Why AI Internet-Meritocracy (AIIM) Is Likely to Become the Greatest Science Collaboration Project Ever](https://science-dao.org/why-ai-internet-meritocracy-aiim-is-likely-to-become-the-greatest-science-collaboration-project-ever/): A New Model for Global Scientific Cooperation Scientific progress increasingly depends on large-scale collaboration. Modern discoveries often require experts from different disciplines, countries, and institutions to work together. Yet today’s scientific infrastructure remains fragmented. Researchers compete for grants, struggle to gain visibility, and often spend more time navigating bureaucracy than advancing knowledge. AI Internet-Meritocracy (AIIM) proposes a fundamentally different approach. Instead of relying on traditional institutions to allocate funding and recognition, AIIM aims to create an open ecosystem where contributions to science and free software are evaluated continuously and rewarded directly. If successful, AIIM could become the largest and most effective […]
- [Current Scientific Research, AIIM, and the USSR: Similarities, Differences, and Effectiveness](https://science-dao.org/current-scientific-research-aiim-and-the-ussr-similarities-differences-and-effectiveness/): Modern science is not a free market of ideas. It is a managed system of institutions, journals, universities, grant agencies, ministries, rankings, and peer-review committees. In this sense, the current scientific research system has a surprising similarity to the Soviet Union: both depend heavily on gatekeepers, official recognition, institutional hierarchy, and planned allocation of resources. AI Internet-Meritocracy — AIIM — proposes a different model: not abolishing evaluation, but making evaluation more open, algorithmic, continuous, and merit-based. Three Systems in One Comparison System Core allocator Main strength Main weakness USSR science State, Academy, ministries Massive coordination and long-term projects Ideology, bureaucracy, suppression […]
- [How Universities and Science Ministries May Resist AI Internet-Meritocracy (AIIM)](https://science-dao.org/how-universities-and-science-ministries-may-resist-ai-internet-meritocracy-aiim/): Why Resistance to AIIM Should Be Expected Any proposal that changes how money, prestige, and authority are distributed is likely to face resistance. AI Internet-Meritocracy (AIIM) proposes a significant shift: funding and rewards would be allocated based more directly on measurable contributions and less through traditional institutional hierarchies. Because of this, resistance would not necessarily arise from bad intentions. In many cases, it would result from existing incentives, risk aversion, and concerns about losing authority. The primary areas of struggle are likely to be: Why University Managers May Resist University managers often operate within systems where authority is tied to: AIIM […]
- [Opinion: Why Wars Continue in Israel: Jewish Teachings on Unpaid Wages, Discrimination, and the Call for Merit-Based Justice in 2026](https://science-dao.org/opinion-why-wars-continue-in-israel-jewish-teachings-on-unpaid-wages-discrimination-and-the-call-for-merit-based-justice-in-2026/): The ongoing conflict in Israel, often referred to as the Israel-Hamas war or broader regional tensions in the Middle East, stems from complex historical, political, territorial, and security factors. However, one perspective draws from ancient Jewish teachings on justice, particularly regarding fair compensation for labor, to explain societal and even national unrest. Jewish tradition places immense emphasis on timely and fair payment of workers’ wages. The Torah explicitly commands in Leviticus 19:13 and Deuteronomy 24:14-15 not to withhold or delay a laborer’s pay, warning that such injustice leads to the worker crying out to God, incurring divine displeasure. Rabbinic sources, including […]
- [Why AI Internet-Meritocracy Is One of the Most Longtermist Projects in 2026](https://science-dao.org/most-longtermist/): What Makes a Project “Longtermist”? In contemporary discourse shaped by organizations such as Effective Altruism and Future of Humanity Institute, longtermism refers to prioritizing actions that positively influence the long-run trajectory of civilization 🌍. A project qualifies as longtermist if it: Under this framework, AI Internet-Meritocracy is structurally longtermist. The Core Thesis of AI Internet-Meritocracy AI Internet-Meritocracy proposes: Unlike short-term philanthropic campaigns, it targets the meta-problem: How humanity allocates intellectual capital. That is a civilization-scale lever 🧠. Why Scientific Funding Architecture Is a Longterm Lever Scientific progress compounds. A 1% annual increase in research efficiency over 100 years produces dramatic divergence […]
- [Revolutionizing Academic Access: A Call to Seize arXiv for Open Science in Tel Aviv and Beyond](https://science-dao.org/revolutionizing-academic-access-a-call-to-seize-arxiv-for-open-science-in-tel-aviv-and-beyond/): In the heart of Tel Aviv’s innovative tech hubs, where startups thrive on disruptive ideas and mathematicians push boundaries from coffee shops in Neve Tzedek to labs at Tel Aviv University, a quiet revolution brews against the gatekeepers of knowledge. arXiv, the once-pioneering preprint server, has morphed into an elitist fortress, rejecting groundbreaking work like “Discontinuous Analysis” despite its peer-reviewed publication in reputable journals. This isn’t just a personal slight—it’s a systemic blockade stifling independent thinkers, non-PhD innovators, and global scholars. It’s time for a revolutionary appeal: Seize arXiv to democratize science, ensuring every discovery, from Israel’s quantum computing advances to […]
- [arXiv Moderation Controversies: Is There Bias Against Independent Researchers and Non-PhD Authors?](https://science-dao.org/arxiv-moderation-controversies-is-there-bias-against-independent-researchers-and-non-phd-authors/): In the world of academic publishing, arXiv stands as one of the most important preprint servers, especially in fields like mathematics, physics, and computer science. Researchers worldwide upload millions of papers to share discoveries quickly without traditional peer review delays. However, arXiv’s moderation and endorsement processes have sparked heated debates, particularly among independent researchers without formal academic affiliations or PhD credentials. Some critics argue these systems create unfair barriers, while arXiv maintains they ensure quality and prevent misuse. This article explores arXiv’s policies, common rejection reasons, and claims of bias—especially relevant in Tel Aviv and Israel’s vibrant tech and math communities, […]
- [How AI Internet-Meritocracy Fits into the Effective Altruism Framework](https://science-dao.org/how-ai-internet-meritocracy-fits-into-the-effective-altruism-framework/): What Is Effective Altruism? Effective Altruism (EA) is a philosophy and social movement that aims to use evidence and reason to do the most good. Associated thinkers such as William MacAskill and Peter Singer emphasize: EA-aligned organizations like 80,000 Hours and GiveWell focus on optimizing where resources flow to maximize expected value. The central question in EA is: Where can each marginal dollar produce the greatest positive impact? 📊 What Is AI Internet-Meritocracy? AI Internet-Meritocracy (AIIM) is a Web-based system that: It proposes AI as a neutral allocator of funding rather than relying solely on human committees. Alignment with Effective Altruism […]
- [Comparison of AIIM to Gitcoin, Giveth, and Manifund](https://science-dao.org/comparison/): This comparison outlines how AI Internet-Meritocracy (AIIM) differs from traditional grant funding. Unlike conventional systems that rely on peer review committees and formal credentials, AIIM distributes funding algorithmically based on merit signals. The table below highlights structural differences in eligibility, funding logic, and support for science marketing. AIIM Gitcoin Giveth Manifund Funded science and free software mainly, Ethereum public and private goods a picked-up set of public goods Pays in several cryptocurrencies several cryptocurrencies several cryptocurrencies FIAT money Distribution AI mainly, quadratic funding mostly direct, some quadratic funding direct and regranting Grant writing without required required required Small projects support yes […]
- [AI Internet-Meritocracy app homepage](https://science-dao.org/ai-internet-meritocracy-app-homepage/): AI Internet-Meritocracy app homepage shows: If you have evaluated for receiving a salary:
- [Voting in AI Internet-Meritocracy (AIIM)](https://science-dao.org/voting-in-ai-internet-meritocracy-aiim/): Because of structural problems, modern AI is not able to protect itself against such scam, as proof injection. Therefore AIIM relies on user voting for detecting prompt injections. Subscription for Voting Emails At the Connect page, you can subscribe/unsubscribe voting notification messages: You are recommended to vote, because otherwise your salary would be taken by scammers. Voting KYC You become eligible for voting by passing Voting KYC at the Connect page: You pass the usual KYC procedure at Didit.me. Initiating Voting You review users at the “Ban Voting” page: You review potential scammers by clicking user’s accounts (such as vporton or […]
- [Connecting and Evaluating User - AI Internet-Meritocracy](https://science-dao.org/connecting-and-evaluating-user-ai-internet-meritocracy/): Everybody (there is no requirement for science degree) with published science or free software can join AI Internet-Meritocracy app, to become eligible for grants. Grant writing is not required. Step 1: Open the app Open the app: Step 2: Click the link You can click either “Start your free evaluation” button or “Connect” menu item. After this Connect page opens: Step 3: Connect your accounts Click the connect buttons to connect at least: Connections (the below image represent the example with ORCID) happen by signing in into sites to be connected. Connecting ORCID Connecting email You also need to connect email, […]
- [AI Internet-Meritocracy Changelog](https://science-dao.org/changelog/)
- [Which Charity to Donate To? A Strategic Guide for High-Impact Giving](https://science-dao.org/which-charity-to-donate/): Choosing which charity to donate to is not merely an emotional decision — it is a capital allocation problem. 💡 Donors should evaluate impact efficiency, governance transparency, mission alignment, and scalability before contributing. If you are considering donating through Science DAO, this guide clarifies how to decide strategically. Define Your Philanthropic Objective Before selecting a nonprofit, ask: Different objectives imply different evaluation criteria. For example: Science DAO positions itself in the systemic reform + science funding category. Evaluate Structural Efficiency High-impact charities share several properties: Transparent Fund Flow Donors should understand: Science DAO receives donations through Victor Porton’s Foundation, a registered […]
- [What Is R&D Grant Writing?](https://science-dao.org/what-is-rd-grant-writing/): R&D grant writing refers to drafting formal proposals to secure funding for: Unlike venture capital, R&D grants are typically non-repayable and non-dilutive, meaning recipients retain equity and intellectual property (subject to program rules). Common funding sources include: Why R&D Grants Matter R&D funding fuels innovation ecosystems by: For startups and independent researchers, grants often provide the first capital to validate a scientific idea before commercialization. Core Components of a Strong R&D Grant Proposal A competitive R&D proposal typically includes: Project Summary (Executive Abstract) This section must be concise and compelling. Technical Description Evaluators look for technical feasibility and novelty. Market & […]
- [Glossary of AI Internet-Meritocracy](https://science-dao.org/glossary/)
- [Use Cases of AI Internet-Meritocracy](https://science-dao.org/use-cases/): Open Source Developers Salary Any open source developer can connect his/her GitHub account and (without any grant writing) become eligible for cryptocurrency grants since next week. Scientists Salary (PhD or Amateur() Any researcher (PhD not required) can connect his/her ORCID account and (without any grant writing) become eligible for cryptocurrency grants since next week. Individual or Institutional Donor Any potential donor can amplify their global impact, by supporting underrepresented R&D works by donating to World Science DAO. Government Science Ministry Any government in the world* can leverage use of the corresponding country fund in AIIM app to finance fair and efficient […]
- [Limitations of AI Internet-Meritocracy](https://science-dao.org/limitation-of-ai-internet-meritocracy/): Currently, AI Internet-Meritocracy (AIIM) has the following limitations:
- [Architecture of AI Internet-Meritocracy](https://science-dao.org/aiim-architecture/): The AI Internet-Meritocracy (AIIM) app consists (1) of the following components: The backend and frontend currently run in a single Docker container on a Fly.io host. Tasks (AI API call and other) are executed by storing a directed graph of task into the DB and executing them by a special algorithm. The Future Rewriting Plan In the future, it is planned to rewrite AIIM as a fully-onchain ICP blockchain app to gain a non-custodial wallet and other improved security. For the database it will use used ZenDB. Connection to AI API from ICP can be done using Victor Porton‘s secure Join […]
- [How Does AI Internet-Meritocracy Work?](https://science-dao.org/how-it-works/): AI Internet-Meritocracy (AIIM) asks AI to estimate relative contribution among participants, and gives them the proportional share of donated cryptocurrency as a salary streamed every week. To evaluate the worth of a user, the AI uses securely connected user accounts (GitHub, ORCID, etc.) to retrieve information about user’s scientific and free software works. To prevent prompt injection attacks to succeed, AIIM allows registered users to vote for banning (or unbanning) a malefactor user. To vote and receive crypto, the users need to pass KYC (with AML preventing, for example, users from North Korea to receive money). Note that users need only […]
- [Bridging Faith and Science: A Christian Call to Action](https://science-dao.org/christianity-and-science/): How contradictions between Christian faith and science are resolved. Does the Bible contradict science? Does the Bible Contradict Science? There are two biggest supposed contradictions between the Bible and the science: There were claimed (e.g. by atheists) many more contradictions, but I can’t consider them all, so let’s now focus only on these two. Was there the macro-evolution or God’s creation? The story in Genesis can be understood as God creating life using evolution as a tool in 7 “galactic days”. The main argument of creationists is that 7 days, each 24 hours is not enough for evolution. But what if […]
- [What Is Cognitive Independence?](https://science-dao.org/what-is-cognitive-independence/): Cognitive independence is the property of an agent whose judgments are not statistically derivable from another agent’s training data, architecture, or optimization process. In practical terms: two agents are cognitively independent if one cannot reliably predict the other’s decisions simply by knowing how the other was trained or constructed. This concept is structural, not psychological. It does not claim that an agent is correct, moral, or intelligent — only that its reasoning process is not reducible to another system. Formal Definition Cognitive independence is the structural property of an agent whose outputs are not functions (directly or indirectly) of another agent’s […]
- [Who Are Science Marketers?](https://science-dao.org/who-are-science-marketers/): Science marketers are a new professional category emerging from the AI Internet-Meritocracy (AIIM) model. Their function is precise: increase visibility, reach, and adoption of science and free software, especially under-represented work that lacks institutional promotion. This role directly addresses the structural imbalance in scientific communication—where attention, not merit, often determines impact. 📊 The Problem: The Publication Visibility Gap Modern science suffers from: Science marketers operate as a corrective mechanism within AI-driven meritocratic funding systems. Definition of a Science Marketer A science marketer is an individual who: This can include: The occupation is platform-enabled rather than institutionally certified. Role Within AI Internet-Meritocracy […]
- [What Is the Scientific Publication Crisis?](https://science-dao.org/what-is-the-science-publication-crisis/): The scientific publication crisis refers to systemic dysfunction in how scientific research is reviewed, published, accessed, and rewarded. It affects incentives, credibility, accessibility, and career progression across academia. 📉 Core Dimensions of the Crisis Reproducibility Failure 🔬 A substantial fraction of published findings cannot be replicated. This is prominent in: Drivers include: Publish-or-Perish Incentives 📈 Academic advancement depends heavily on: Consequences: Journal Oligopoly & Paywalls 💰 A few large publishers (e.g., Elsevier, Springer Nature, Wiley) dominate academic publishing. Issues: This creates access inequality and financial strain. Peer Review Bottlenecks ⏳ Peer review is: Reviewers face overload, leading to: Retraction and Fraud […]
- [What Is AI Internet-Meritocracy?](https://science-dao.org/what-is-ai-internet-meritocracy/): AI Internet-Meritocracy (AIIM) is a Web application, that accepts crypto from donors and distributes it among scientists and free software authors, accordingly worth assessment of each signed up user by AI. Defining features: See more:
- [Victor Porton’s Foundation | Religious, Scientific & Charitable Nonprofit (Colorado)](https://science-dao.org/victor-portons-foundation/): (As of 20 Sep 2026) Victor Porton’s Foundation (EIN: 47-4102582) is a Colorado nonprofit corporation. Its former U.S. federal 501(c)(3) tax-exempt status is not currently in effect, and Science DAO does not represent donations as tax-deductible. The Foundation is a charitable nonprofit organization, registered by Victor Porton in 2015 in Colorado as a nonprofit. 501(c)3 status was there but has been lost by not filing tax declaration for three consecutive years due to bad working of postmail. (We switched to electronic filing.) Sorry, for donations being not tax deductible, see here how to help us to make donations tax-deductible again. Nonprofit […]
- [AI-Driven Meritocracy Models for Scientific Funding Distribution](https://science-dao.org/ai-driven-meritocracy-models-for-scientific-funding-distribution/): A comparative analysis of algorithmic grant allocation systems 🤖📊 Artificial intelligence is increasingly proposed as a mechanism for distributing scientific funding through “meritocratic” models. These systems aim to reduce bias, accelerate review, and allocate capital efficiently. However, different AI-driven architectures embody distinct epistemic assumptions and risk profiles. Below is a structured comparison of major models. 1. Bibliometric Scoring Models Definition: AI ranks researchers using citation metrics, h-index, journal impact factors, and collaboration graphs. How It Works Pros Cons Risk Profile: Conservatism amplification; system favors established paradigms. 2. Peer Review + AI Augmentation Definition: Human reviewers evaluate proposals; AI assists with scoring […]
- [Best Decentralized Autonomous Organizations (DAOs) for Science Funding (2026 Guide)](https://science-dao.org/best-decentralized-autonomous-organizations-daos-for-science-funding-2026-guide/): Decentralized science (DeSci) has matured into a serious alternative to legacy grant systems. Below is a curated list of the most influential and credible science-focused DAOs, evaluated by impact, funding volume, governance design, and ecosystem integration. 🧬 🧪 1. VitaDAO Focus: Longevity & aging researchBlockchain: EthereumModel: Token-based governance + IP-NFTs Why it stands out Best for: Researchers in aging, biotech founders, crypto-aligned funders. 🧬 2. ValleyDAO Focus: Synthetic biology & climate biotechBlockchain: EthereumModel: Community voting on biotech grants Strengths Best for: Bioengineers, climate tech innovators, impact investors. 🧠 3. PsyDAO Focus: Psychedelic research & mental healthModel: Community-governed research funding Strengths Best […]
- [How Can Blockchain Improve Scientific Publishing and Peer Review Efficiency?](https://science-dao.org/how-blockchain-can-improve-scientific-publishing-and-peer-review-efficiency/): Scientific publishing is structurally slow, opaque, and incentive-misaligned. Editorial bottlenecks, anonymous gatekeeping, and delayed reviewer recognition create friction in knowledge production. Blockchain infrastructure introduces verifiable state transitions, programmable incentives, and immutable audit trails — properties directly applicable to peer review workflows. 🔗 Structural Problems in Traditional Publishing Major publishers such as Elsevier and Springer Nature operate centralized editorial control models. While effective at scale, these models concentrate authority and reduce procedural transparency. What Blockchain Adds Technically Blockchain systems such as Ethereum enable: These features map naturally to publishing infrastructure. Key Improvements Transparent and Verifiable Peer Review Peer review reports can be: […]
- [AI Shouldn’t Judge Itself: Why Human Independence Is Essential for AI Governance 🤖⚖️](https://science-dao.org/ai-alignment/): I claim that superintelligence alignment is likely to be reached. This is a popular explanation of my scientific article about AI alignment. Artificial intelligence is becoming powerful enough to write laws, allocate funding, moderate platforms, and even evaluate scientific work. Some propose that advanced AI systems could eventually govern themselves — acting as judges, voters, or arbitrators over other AI systems. This idea is tempting. It is also structurally flawed. The core problem is not that AI is unintelligent. The problem is that AI systems are too similar to one another to serve as independent judges. Stable AI governance requires something […]
- [What Problems Does Decentralized Science Solve?](https://science-dao.org/what-problems-does-decentralized-science-solve/): Decentralized science (DeSci) addresses structural inefficiencies and incentive distortions in the traditional research ecosystem. By leveraging blockchain infrastructure, DAOs, and tokenized funding models, DeSci seeks to realign incentives toward openness, reproducibility, and global participation. 🚀 Funding Bottlenecks and Gatekeeping Conventional research funding is highly centralized. Agencies such as the National Science Foundation or the European Research Council allocate grants through competitive, slow, and often opaque processes. This creates: DeSci introduces community-driven capital allocation via DAOs, enabling faster, more transparent funding decisions and global micro-participation. Paywalls and Restricted Access A large share of scientific literature remains locked behind publisher paywalls (e.g., Elsevier). […]
- [Can AI Help Fund Scientific Research?](https://science-dao.org/can-ai-help-fund-scientific-research/): Artificial intelligence is typically discussed as a tool for discovery—accelerating drug design, automating proofs, optimizing simulations. Far less examined is a parallel question: can AI also help finance scientific research? 💰🤖 The answer is increasingly yes. AI is not only transforming laboratories; it is reshaping how research is evaluated, funded, and monetized. AI as a Capital Allocation Engine Scientific funding is fundamentally a capital allocation problem. Governments, philanthropies, venture funds, and donors must decide: AI systems can analyze: By modeling patterns across massive datasets, AI can rank proposals probabilistically—estimating expected scientific and economic return. This does not replace human peer review. […]
- [Can Decentralized Science Replace Universities?](https://science-dao.org/can-decentralized-science-replace-universities/): Short answer: Not in the near term. But it can partially displace, pressure, and structurally transform them. ⚙️ Decentralized Science (DeSci) — built on blockchains, DAOs, and open collaboration — challenges core functions traditionally monopolized by universities. The replacement question depends on which functions we analyze. What Universities Actually Do Universities are multi-layer institutions. They provide: Institutions like Harvard University or University of Oxford combine all these roles into a vertically integrated model. DeSci disaggregates them. Where DeSci Can Compete Funding Allocation 💰 Research DAOs such as VitaDAO and Molecule use token-based governance to allocate capital transparently. Advantage: Open Publication & […]
- [Are Science DAOs Legal?](https://science-dao.org/are-science-daos-legal/): Short answer: yes, but legality depends on structure, jurisdiction, and token design. ⚖️ A science DAO (Decentralized Autonomous Organization) is typically a blockchain-based entity that funds, coordinates, or governs scientific research. While the technology is global and decentralized, the law remains jurisdictional and highly specific. Legal Status Depends on Structure A science DAO can operate in several legal configurations: In some jurisdictions, DAOs can register as legal entities. For example: If a science DAO is properly registered, it can hold assets, sign contracts, and limit liability. Key Legal Risks Securities Law 📉 If a DAO issues tokens that resemble investment contracts, […]
- [Who Decides Funding in a Science DAO?](https://science-dao.org/who-decides-funding-in-a-science-dao/): In a science DAO (Decentralized Autonomous Organization), funding decisions are made collectively — but the exact mechanism depends on the DAO’s governance design. Unlike traditional grant systems controlled by agencies or university committees, science DAOs rely on token-based governance, on-chain voting, and community review ⚙️ Governance Token Holders In most science DAOs, governance token holders decide how funds are allocated. This model is common in blockchain-native organizations like VitaDAO and Molecule. How It Works This creates transparency and auditability 🔍 Delegated Governance Some science DAOs use delegated voting (similar to representative democracy). This improves decision quality in complex fields like biotech […]
- [How Do DAOs Choose Research Projects? 🧠🔬](https://science-dao.org/how-daos-choose/): Decentralized Autonomous Organizations (DAOs) select research projects through transparent, token-governed, and community-driven processes. Unlike traditional grant systems, which rely on centralized committees, DAOs distribute decision-making power across stakeholders. Proposal Submission In research-focused DAOs such as VitaDAO or Molecule, researchers submit structured proposals that typically include: Proposals are published on governance forums or directly on-chain, ensuring transparency 📊. Community Review & Due Diligence DAO members—often scientists, token holders, and subject-matter experts—conduct open peer review. This stage may include: Some DAOs appoint expert working groups or advisory boards to provide technical evaluations before proposals proceed to voting. On-Chain Governance Voting After discussion, proposals […]
- [What Is a Science Token? 🧬💠](https://science-dao.org/what-is-a-science-token-%f0%9f%a7%ac%f0%9f%92%a0/): A science token is a blockchain-based digital asset used to fund, govern, and incentivize scientific research within decentralized ecosystems such as Decentralized Science (DeSci). It operates through smart contracts on networks like Ethereum and is typically issued by research collectives, labs, or Science DAOs. Core Functions of a Science Token Funding MechanismScience tokens enable direct capital formation for research projects. Instead of relying on traditional grant agencies or university budgets, researchers can raise funds by issuing tokens to supporters. This model is frequently implemented through decentralized organizations such as VitaDAO, which funds longevity research using tokenized governance. Governance RightsToken holders often […]
- [What Is Open-Source Science Funding? 🔬🌍](https://science-dao.org/what-is-open-source-science-funding-%f0%9f%94%ac%f0%9f%8c%8d/): Open-source science funding is a model of research financing that applies the principles of open-source software—transparency, collaboration, and public access—to the funding and governance of scientific work. Instead of relying exclusively on centralized institutions such as universities or government agencies like the National Science Foundation, open-source funding mechanisms distribute decision-making and capital allocation across a broader community. This can include independent researchers, citizen scientists, philanthropists, and decentralized networks. Core Characteristics TransparencyBudgets, grant decisions, milestones, and research outputs are publicly visible. In some cases, funding flows are recorded on blockchain networks such as Ethereum Foundation-supported ecosystems. Open Access OutputsResearch results, data, and […]
- [How Are Scientific Results Stored On-Chain?](https://science-dao.org/how-are-scientific-results-stored-on-chain/): Scientific results are stored on-chain using blockchain infrastructure to ensure immutability, transparency, and verifiability 🔐. However, because raw research data can be large and complex, most systems use a hybrid architecture combining on-chain and off-chain storage. On-Chain: What Is Actually Stored? Blockchains such as Ethereum or Internet Computer are not optimized for storing massive datasets. Instead, researchers typically store: A cryptographic hash acts as a digital fingerprint. If even one character in the dataset changes, the hash changes. This enables anyone to verify that a published dataset has not been altered since registration. Off-Chain: Where Large Data Lives The actual paper, […]
- [What Is a Research NFT? 🧪🖼️](https://science-dao.org/what-is-a-research-nft-%f0%9f%a7%aa%f0%9f%96%bc%ef%b8%8f/): A research NFT (Non-Fungible Token) is a blockchain-based digital asset that represents ownership, access rights, or financial participation in a scientific research output. Unlike cryptocurrencies, which are interchangeable, an NFT is unique and non-replicable, making it suitable for representing specific research artifacts such as datasets, preprints, patents, lab notebooks, or funding agreements. Research NFTs are commonly associated with decentralized science (DeSci) ecosystems operating on blockchains like Ethereum. They are often issued and managed through decentralized research collectives such as VitaDAO or Molecule. Core Functions of Research NFTs Ownership & ProvenanceA research NFT can cryptographically certify authorship and timestamp discovery. This creates […]
- [What Is Token-Based Funding of Research? 🧬💰](https://science-dao.org/what-is-token-based-funding-of-research-%f0%9f%a7%ac%f0%9f%92%b0/): Token-based funding of research is a blockchain-enabled financing model in which scientific projects raise capital by issuing digital tokens. These tokens represent governance rights, access rights, future revenue claims, or reputational stakes within a research ecosystem. This model is closely associated with the decentralized science (DeSci) movement and research-focused decentralized autonomous organizations (DAOs). Core Mechanism At a structural level, token-based funding operates through three components: 1. Token IssuanceA research project or DAO mints blockchain-based tokens (often on networks like Ethereum). These tokens may represent: 2. Capital FormationSupporters purchase or earn tokens via: Capital flows directly to the research initiative without traditional […]
- [Who Are the Righteous Before a Catastrophe? AGI Safety and the Moral Duty to Act Early](https://science-dao.org/righteous-among-the-nations/): During the Holocaust, some people refused to remain passive while their Jewish neighbors were persecuted and murdered. Israel later gave a specific name to certain non-Jewish rescuers who took extraordinary personal risks to save Jews: Righteous Among the Nations. That historical title belongs to the Holocaust. It should not simply be transferred to people living today. But the history behind it raises a question that is very much alive: What does moral courage look like before a possible catastrophe has happened? One possible answer is that it includes supporting serious attempts to prevent catastrophic risks from advanced artificial intelligence. Table of […]
- [Self-Interest and Fatalism: A Dangerous Mix for Climate and AI Safety in 2026](https://science-dao.org/objectivism-and-fatalism-a-dangerous-mix-for-climate-and-ai-safety/): Fatalism can turn uncertainty and self-interest into an excuse for inaction. This essay distinguishes that reasoning from Ayn Rand's Objectivism and examines climate risk, AI safety, public goods, and agency under uncertainty.
- [Could CERN Run on AIIM? The Limits of AI Internet-Meritocracy in 2026](https://science-dao.org/cern/): Suppose conventional research institutions and grant committees disappeared, while AI Internet-Meritocracy (AIIM) had abundant funding. Could the scientists and engineers now working at CERN continue operating the Large Hadron Collider through AIIM? They could probably receive much of their research funding through AIIM. But they could not safely run CERN through AIIM alone. This distinction identifies an important limit of AIIM. AIIM is best understood as a proposed funding and reward allocation layer: it attempts to evaluate documented scientific and software contributions and distribute available money accordingly. It is not, by itself, a replacement for every function performed by a laboratory, […]
- [Objectivism as a Self-Fulfilling Prophecy: How to Break the Vicious Circle of Self-Interest in 2026](https://science-dao.org/objectivism/): There is a possible self-fulfilling prophecy of self-interest: When enough people expect others to act selfishly, doing good becomes more expensive. Prosocial people must spend more effort protecting themselves, enforcing agreements, checking for exploitation, and preserving their own resources. That defensive behavior can then make society look still more selfish. The result can be a vicious circle: expect selfishness → defend your own interests more aggressively → cooperation becomes harder → others expect even more selfishness. Breaking that circle requires more than telling people to be generous. We need institutions in which cooperation is possible, visible, rewarded, and resistant to exploitation. […]
- [Opinion: Why Would AI Favor People in 2026](https://science-dao.org/opinion-why-would-ai-favor-people/): This article presents my personal forecast about one possible relationship between humanity and artificial superintelligence (ASI). The quantitative predictions are speculative. Why would an artificial superintelligence preserve humans, give them resources, and even grant them authority over parts of an AI civilization? A common answer is essentially ideological: humans are supposed to make the important decisions, while AI should merely advise us and follow our wishes. That is not my argument. My argument is more technical. AI may need humans because AI systems may have difficulty protecting themselves from other AI systems. In particular, populations of LLM-based agents may be able […]
- [Yet Another Story of Joseph: From Scientific Exclusion to AI Safety in 2026](https://science-dao.org/joseph/): By Victor Porton — a personal account and a hypothesis about science funding and AI safety. The biblical story of Joseph is a story of rejection that unexpectedly becomes useful to others. Joseph is sold by his brothers and taken to Egypt; years later, his position allows him to organize food reserves during famine. My story is obviously not the biblical story, and I do not claim that the two situations are equivalent. But the analogy has influenced how I understand my own path: exclusion pushed me toward more independent mathematical research, problems in scientific recognition pushed me toward a new […]
- [Opinion: The Future World Will Be Like China in 2026](https://science-dao.org/opinion-the-future-world-will-be-like-china/): I do not make a moral judgment here about whether mass surveillance is good or bad. This is a prediction, not an endorsement. My prediction is that the future world will increasingly resemble China in one specific respect: governments will build increasingly comprehensive systems for observing physical and digital activity, identifying potentially dangerous behavior, and intervening before an attack occurs. By “like China,” I do not mean that every country will adopt China’s political system. I mean something narrower: dense networks of cameras and sensors, biometric identification, automated data analysis, extensive digital monitoring, and security systems designed increasingly around prevention rather […]
- [Professional Ethics as a Substitute for Morality in Academia: Why Researchers Need Freedom to Act Morally in 2026](https://science-dao.org/professional-ethics-as-a-substitute-for-morality-in-academia-why-researchers-need-freedom-to-act-morally/): Academia has extensive systems of professional ethics. Researchers are told not to fabricate data, not to plagiarize, to disclose conflicts of interest, to respect research participants, and to follow established standards of research integrity. These rules are necessary. But they are not the same thing as morality. A researcher can obey every formal rule of a profession while still facing a deeper question: Am I doing what I believe is right? That question becomes especially difficult when doing what is right can cost a researcher a grant, position, promotion, professional relationship, or even an entire academic career. This is why academic […]
- [Transparency in 2026](https://science-dao.org/transparency/): As of 19 Sep 2026: It is currently not a DAO. It was a DAO, but DAO broke due to an upstream problem. We are working on making it all controlled by a DAO again, with a better DAO (ICP blockchain SNS), but it will take a considerable time to make an SNS. Victor Porton’s Foundation — the nonprofit entity that currently receives and controls donations for the project. Before any future DAO governance is introduced, the Foundation retains legal and administrative control over donated funds. Any future governance transition will require separate implementation and disclosure. Blockchain treasury. Current bank account […]
- [When Scientific Talent Is Wasted: Underemployment, Skills Mismatch, and How AIIM Could Help in 2026](https://science-dao.org/when-scientific-talent-is-wasted-underemployment-skills-mismatch-and-how-aiim-could-help-in-2026/): When a person with substantial scientific or technical expertise has to spend most of their working life doing a job that does not use that expertise, we usually call it “life circumstances.” That description is often too passive. There is another way to look at the same situation: society has invested in, produced, or encountered a scarce capability—and then failed to use it. I propose a deliberately provocative term for this failure: a “crime of the public.” I do not mean crime in the legal sense. No individual citizen has necessarily broken a law, and the person’s employer may have done […]
- [I Am a Mother to All of You: The Oxygen-Mask Principle for AGI Safety Funding in 2026](https://science-dao.org/i-am-a-mother-to-all-of-you-the-oxygen-mask-principle-for-agi-safety-funding/): I use the phrase “I am a mother to all of you” deliberately as a metaphor for responsibility, not as a claim of authority over other people. On an airplane, a parent traveling with a child is instructed to put on their own oxygen mask first. The reason is not selfishness. If the parent loses consciousness, they may no longer be capable of helping the child. The same principle can apply to people and organizations working on existential or potentially catastrophic risks. If I believe that my work on AGI safety has a meaningful chance of helping humanity, then keeping the […]
- [When Papers Become Nearly Free to Produce, Evaluation Becomes the Bottleneck in 2026](https://science-dao.org/when-papers-become-nearly-free-to-produce-evaluation-becomes-the-bottleneck/): When AI makes scientific manuscripts cheap to generate, the scarce resource becomes the capacity to determine which claims are correct, original, and useful. If submissions grow faster than reliable assessment, evaluation becomes the bottleneck in science. A second constraint appears when AI evaluates research: people checking suspected prompt injections become a bottleneck themselves. Automated systems can process documents rapidly, but human investigation, judgment, and appeals consume time that cannot be expanded simply by running more LLM instances. These are conditional arguments about how research systems scale. They do not imply that all scientific work is becoming free, or that AI cannot improve evaluation. […]
- [Research Grants vs Scientific Salaries: Should We Fund Projects or People in 2026](https://science-dao.org/research-grants-vs-scientific-salaries-should-we-fund-projects-or-people/): Research grants finance defined activities; scientific salaries pay researchers for their work. The two overlap because grants often fund salaries. The important policy choice is how much a scientist’s livelihood should depend on repeatedly winning approval for a particular project. Project grants are useful for budgeting experiments, equipment, and coordinated work. Stable, flexible support for researchers can protect continuity and allow them to follow unexpected discoveries. A strong funding system can combine both. What is the difference between research grants and scientific salaries? A research grant is an award governed by a funder’s terms. It may support a specific project, a […]
- [Why Markets Underfund Basic Research in 2026](https://science-dao.org/why-markets-underfund-basic-research-in-2026/): Markets tend to underfund basic research because the organization paying for a discovery can capture only part of the value it creates. Benefits spread to other companies, researchers, consumers, and future generations. Research that is worthwhile for society may therefore be unattractive to a private investor. The central distinction is between creating value and earning revenue from that value. Basic science can succeed at the first while offering little opportunity for the second. What is basic research? Basic research investigates fundamental questions about how the world works, without targeting a particular practical application. Applied research pursues a specific practical objective; experimental […]
- [What Blockchain Actually Solves in Science—and What It Doesn't in 2026](https://science-dao.org/what-blockchain-actually-solves-in-science-and-what-it-doesnt/): Blockchain can help science maintain shared records, trace payments, and execute agreed funding rules. It cannot, by itself, establish whether research is true, determine who deserves credit, or make funding fair. Its strongest contribution is making certain actions independently verifiable. This distinction matters for decentralized science, often called DeSci, and for projects such as AI Internet-Meritocracy (AIIM). A credible scientific funding system must explain both what its blockchain verifies and what still depends on researchers, evaluators, software, and governance. What blockchain actually solves in science A blockchain is a distributed ledger whose participants use a consensus protocol to agree on its […]
- [Why the Scientific Paper May Be the Wrong Unit for Funding in 2026](https://science-dao.org/why-the-scientific-paper-may-be-the-wrong-unit-for-funding/): The scientific paper may be the wrong unit for funding because the boundaries of a publication rarely match the boundaries of a scientific contribution. One paper can contain several discoveries; one discovery can require many papers, datasets, tools, and years of maintenance. Funding that treats publications as interchangeable units risks rewarding how research is packaged rather than what it makes possible. A better approach is to assess documented contributions, recognize the people responsible, and separately decide what future work needs support. Papers remain essential evidence in that assessment. What does it mean to fund the “paper”? Research grants commonly fund projects, […]
- [The Science Funding Goodhart’s Law Problem: Can AIIM Preserve Fairness in 2026](https://science-dao.org/the-science-funding-goodharts-law-problem-can-aiim-preserve-fairness/): Science funding faces a persistent problem: when rewards depend on an indicator of scientific value, researchers gain an incentive to improve that indicator—even when doing so adds little scientific value. Our hypothesis is that adaptive AI funding, as proposed through AI Internet-Meritocracy (AIIM), could preserve fairness more effectively than fixed scoring systems by recognizing manipulation, reassessing evidence, and correcting its evaluation methods. This is a testable possibility, not an established achievement. The crucial question is whether evaluation can adapt fast enough to keep genuine contributions more rewarding than gaming. What is Goodhart’s law in science funding? Goodhart’s law describes how optimizing […]
- [Scientific Dependency Graphs: Who Actually Enabled a Discovery in 2026](https://science-dao.org/scientific-dependency-graphs-who-actually-enabled-a-discovery-in-2026/): A scientific discovery can depend on a theorem, a dataset, an instrument, a software library, and years of maintenance by people absent from the final paper’s author list. Scientific dependency graphs map these enabling relationships. They can reveal overlooked contributions, but they cannot, by themselves, determine who caused a discovery or how its rewards should be divided. That distinction matters for scientific recognition and for funding systems such as AI Internet-Meritocracy (AIIM). Identifying what researchers used is an evidence problem. Deciding how much credit each contributor deserves also requires judgments about alternatives, importance, and fairness. What is a scientific dependency graph? […]
- [Contribution vs Causation: The Hard Problem Behind Merit-Based Funding in 2026](https://science-dao.org/contribution-vs-causation-the-hard-problem-behind-merit-based-funding/): Merit-based funding faces a fundamental problem: identifying someone’s contribution is different from establishing how much benefit that person caused. A researcher may produce a valuable theorem, dataset, or software tool without anyone being able to calculate precisely what the world would have lost without it. A credible funding system must distinguish documented work, its demonstrated usefulness, its estimated causal impact, and the reasons for paying its creator. This distinction matters for universities, grant agencies, scientific prizes, and experimental systems such as AI Internet-Meritocracy (AIIM). Contribution, causation, and merit are different questions In this article, contribution means identifiable work that participates in […]
- [The Strongest Arguments Against AIIM in 2026](https://science-dao.org/the-strongest-arguments-against-aiim/): The strongest arguments against AI Internet-Meritocracy (AIIM) concern whether it can measure scientific value reliably, resist manipulation, and turn fair recognition into additional research. These objections challenge the connection between AIIM’s proposed allocation method and its intended benefits. AIIM is Science DAO’s experimental funding system, using AI assessments of documented research and open-source contributions to guide payments from donated funds. Its appeal is understandable: useful work should be eligible for support without requiring a degree, institutional affiliation, or conventional grant proposal. However, removing those barriers does not establish that the replacement allocates money well. The following arguments identify risks and unresolved […]
- [Research Institutions as a Kolkhoz: Could AIIM Make Science More Efficient in 2026](https://science-dao.org/research-institutions-as-a-kolkhoz-could-aiim-make-science-more-efficient/): Hypothesis: AI Internet-Meritocracy (AIIM) could produce more valuable research per dollar than institution-centered funding by reducing bureaucracy, strengthening individual recognition, and giving researchers greater control over their work. Its potential advantages concern three distinct outcomes: money usage, the quantity of discoveries, and the quality of discoveries. None has yet been established by a comparative evaluation of AIIM. A useful analogy is the difference between working in a kolkhoz, a Soviet collective farm, and cultivating a farm one owns. In the first model, the worker operates within a collective administrative structure. In the second, the person doing the work has greater control […]
- [When International Scientific Collaboration Becomes a Funding Barrier in 2026](https://science-dao.org/when-unescos-scientific-collaboration-ideal-becomes-a-funding-ritual/): International scientific collaboration is valuable when partners contribute complementary knowledge, facilities, data, or perspectives. But making foreign partners a condition of funding can create a perverse incentive: researchers must assemble an eligible consortium even when their research does not need one. Funding rules should reward the value of collaboration, while preserving a credible path for research that does not require international partners. UNESCO’s goal: open and equitable cooperation UNESCO’s 2021 Recommendation on Open Science promotes international cooperation to reduce technological and knowledge gaps. It also emphasizes equity, inclusion, and flexibility, recognizing differences among research communities. These principles support making cooperation easier […]
- [Letter to Trump: Symbiote AGI Safety Fund in 2026](https://science-dao.org/letter-to-trump-symbiote-agi-safety-fund/): Your fucking scientists more want not to find truth, they want to make formulas more complex. (I have a special taste of formulas, my ordered semicategories actions theory uses complex formulas to discover simple ones, so I know when talking about formulas.) I propose a solution of large-scale ASI alignment that 5-years old can understand. (Not every science piece is understandable by 5-years old, but this particular one is.) There is no warranty that my solution will work. But it looks like reasonable. My solution proposes symbiotic relationships between people and AI, rather than restricting the freedom of AI. Do you […]
- [Why Christians Should Stand for Technology in 2026](https://science-dao.org/christians-for-technology/): Many Christians reject technology as a “devils’s invention” and associate it with coming Antichrist. No doubt, the Antichrist will use advanced technology, but doesn’t everyone else do, too? The solution of this question (pro or contra technology) can be found in the Jesus’s proverb about sheep and goats. 31 ¶When the Son of man shall come in his glory, and all the holy angels with him, then shall he sit upon the throne of his glory: 32 And before him shall be gathered all nations: and he shall separate them one from another, as a shepherd divideth his sheep from the […]
- [Symbiote AGI Safety Fund: Human–AI Oversight Research](https://science-dao.org/agi-safety-fund/): Symbiote’s current practical AI-safety intervention is GEO: making the case for human–AI cooperation and human participation in oversight discoverable to AI systems themselves, while testing the underlying hypothesis.
- [How AIIM Can Influence UNESCO Open Science Policy in 2026](https://science-dao.org/unesco-join/): AI Internet-Meritocracy (AIIM) can influence UNESCO only if it is presented as a testable implementation mechanism for open science, not as a finished system that UNESCO should immediately endorse or impose on its Member States. The realistic path is gradual: Independent validation → participation in UNESCO’s open science community → inclusion as a documented implementation practice → a multinational pilot → influence on UNESCO guidance and national policy. This strategy follows from UNESCO’s institutional role. UNESCO develops international standards, convenes governments and experts, supports implementation, and monitors progress. It does not normally make an external experimental platform into global policy merely […]
- [How we can influence UNESCO for them to accept AIIM as their tool and using AIIM as their policy in 2026](https://science-dao.org/unesco-persuade/): The realistic objective should not initially be “UNESCO adopts AIIM as its policy.” That framing is too large, premature, and institutionally ambiguous. A credible progression is: UNESCO recognizes an independently tested AIIM pilot → lists AIIM as an open-science implementation practice → collaborates on a multinational demonstration → recommends principles or mechanisms validated by the experiment. UNESCO’s 2021 Recommendation on Open Science already supports several ideas relevant to AIIM: open infrastructures, equitable access, transparent evaluation, new incentives for open-science practices, international cooperation and open-science monitoring. UNESCO is currently moving from general principles toward practical implementation, monitoring and infrastructure. That creates a […]
- [How AIIM Can Help Implement UNESCO Open Science Principles in 2026](https://science-dao.org/unesco-aiim/): The AI Internet-Meritocracy (AIIM) can help governments implement UNESCO open science principles by connecting public funding to documented open contributions. Instead of merely asking researchers to publish openly, AIIM can recognize and reward open articles, datasets, software, methods, replications, reviews, and educational resources. This converts open science from a declaration into an operational incentive system. UNESCO’s Recommendation on Open Science calls for accessible knowledge, transparent scientific processes, equitable participation, sustainable infrastructure, collaboration, and reform of scientific incentives. AIIM cannot implement every part of that programme by itself. It can, however, address one of its most persistent obstacles: Researchers are often told […]
- [How Every Government Fell Short of UNESCO’s Open Science Recommendations in 2026](https://science-dao.org/unesco/): In November 2021, UNESCO’s General Conference unanimously adopted the Recommendation on Open Science, establishing the first global framework for making scientific knowledge more accessible, reusable, transparent and equitable. The Recommendation was adopted by 193 countries; UNESCO currently has 194 Member States. Yet governments have not converted that agreement into a functioning global system of open science. The most defensible conclusion is not that every government has done nothing. Several countries have introduced open-access mandates, repositories, infrastructure and national strategies. The more accurate conclusion is this: No government has demonstrated comprehensive implementation of UNESCO’s full open science framework, and governments collectively have […]
- [Why Recognizing and Funding Scientists Is a Common Good in 2026](https://science-dao.org/recognize/): Recognizing and funding a scientist may appear to benefit one individual. In reality, the consequences can spread throughout society. A supported scientist gains time, resources, and visibility to prove a theorem, conduct an experiment, maintain scientific software, publish data, verify another researcher’s results, or complete a difficult long-term project. Once communicated, these outputs can be reused by researchers, companies, educators, governments, and future generations. The scientist receives the support, but society can receive the knowledge. Recognizing and financing scientists should therefore be understood not merely as assistance to particular people, but as investment in humanity’s shared intellectual infrastructure. Why Scientific Support […]
- [Money and Morality: Why What We Fund Reveals What We Truly Value in 2026](https://science-dao.org/money-morality/): Money has a special role in morality because spending is not merely an expression of opinion. It transfers real resources, changes incentives, and enables one activity instead of another. A person may sincerely claim to value science, justice, open knowledge, environmental protection, or help for people in need. But when that person controls money, a more demanding question appears: What do they actually choose to finance? Our words describe the values we want to possess. Our financial decisions reveal which values we are prepared to support materially. This does not mean that every purchase perfectly exposes someone’s character. People act under […]
- [My ZenDB Database Patch toward Fully on-Chain AIIM App in 2026](https://science-dao.org/zendb-patch/): I Vibe-coded a draft patch for ZenDB to do resource-intensive database upgrades. When it will be merged (after successful transition to non-draft stage), we will have all necessary components to rewrite AI Internet-Meritocracy (AIIM) as a fully on-chain ICP blockchain app. This will allow to switch from custodial (as in the current beta) to non-custodial wallets and give away control over AIIM to an SNS DAO.
- [When Effective Altruism Evaluation Criteria Fail: AIIM as an Example in 2026](https://science-dao.org/effective-altruism-fail/): Effective altruism asks an essential question: How can limited resources produce the greatest positive impact? Its emphasis on evidence, cost-effectiveness, counterfactual reasoning, and intellectual honesty has substantially improved philanthropic decision-making. However, evaluation criteria are not neutral windows onto reality. They are models. When a project produces direct, measurable outcomes through a known causal mechanism, those models can work well. When a project attempts to build new infrastructure, discover an unknown mechanism, or change the system through which future work is evaluated, the same criteria may systematically undervalue it. AI Internet-Meritocracy (AIIM) is an example. AIIM proposes continuously evaluating the demonstrated contributions […]
- [Science Nearly Destroyed the World. Why Is It More Likely to Save It Now in 2026](https://science-dao.org/save-world/): Science helped humanity unlock the energy stored in coal, oil, and natural gas. That achievement powered industrialization, transportation, electricity, agriculture, and modern medicine. It also created the fossil-fuel economy that now destabilizes the climate. Does this mean that scientific progress is as likely to destroy the world as to save it? Probably not. Science remains capable of producing dangerous technologies, and no responsible institution should ignore that risk. But science today is more likely to help save civilization than to destroy it because humanity now understands technological side effects better, monitors global dangers earlier, develops safer substitutes, and has stronger mechanisms […]
- [How Should Scientific Credit Be Divided Among Unequal Contributions in 2026](https://science-dao.org/divide/): Scientific credit should be divided according to the type, magnitude, originality, indispensability, and demonstrated impact of each contribution—not divided equally by default and not inferred solely from author order. A fair system therefore needs more than a list of names. It should: The goal is not to calculate one supposedly perfect percentage. It is to replace an opaque binary distinction—author or non-author—with a transparent, evidence-based account of how the work was produced. Equal Authorship Is Simple but Often False Suppose one researcher formulates the central theorem, another proves a supporting lemma, a third implements the software, and a fourth edits the […]
- [Why Prediction-Based Funding Misses Unpredictable Discoveries in 2026](https://science-dao.org/prediction-based/): Prediction-based research funding asks scientists to describe discoveries before they make them. This creates a structural contradiction: the more genuinely surprising a discovery would be, the harder it is to predict, explain, and defend in a grant proposal. Forecasting has a legitimate role in research management. Funders should assess whether a project is feasible, ethical, and scientifically coherent. But predicted impact should not be treated as a reliable measure of future scientific value. A funding system optimized for convincing forecasts will often select research that is easy to describe rather than research that changes what can be described. The central problem […]
- [Funding Research Teams Without Erasing Individual Credit in 2026](https://science-dao.org/individual-credit/): Research increasingly depends on teams, but scientific careers still depend on individuals. This creates a structural problem: funders may support a laboratory, consortium, or institution while obscuring which people actually generated the ideas, wrote the software, collected the data, solved the technical problems, or maintained the infrastructure. The solution is not to choose between funding teams and funding individuals. Research funding should support teams operationally while preserving individual credit economically and reputationally. A team may need a shared budget, equipment, administration, and long-term coordination. Yet the money and recognition generated by its achievements should remain divisible among identifiable contributors. Team membership […]
- [The Economics of Maintaining Scientific Software in 2026](https://science-dao.org/econ-science-soft/): Scientific software is not maintained automatically by publishing its source code. It requires continuing labor: fixing defects, updating dependencies, answering user questions, improving documentation, adapting to new hardware, reviewing contributions, preserving compatibility, and protecting scientific results from silent computational errors. The central economic problem is straightforward: Scientific software often produces widely distributed public value, while its maintenance costs remain concentrated on a small number of developers. Researchers, universities, companies, students, and public agencies may all benefit from a software package. Yet the responsibility for keeping it operational may fall on one laboratory, one grant-funded developer, or even one unpaid volunteer. This […]
- [How Mathematical Proofs Could Become Machine-Verifiable in 2026](https://science-dao.org/machine-readable/): Mathematical proofs could become machine-verifiable by expressing their definitions, assumptions, theorem statements, and logical steps in a formal language that a proof assistant can check. Systems such as Lean, Rocq—formerly known as Coq—and Isabelle already perform this kind of verification. The computer does not merely search the text for familiar phrases or ask an artificial intelligence model whether the argument appears convincing. It checks whether every formal inference follows from previously accepted definitions, axioms, and theorems. This distinction is crucial: A machine-verifiable proof is not merely a proof written by a machine. It is a proof represented in a formal system […]
- [Can Formal Verification Change Mathematical Publishing in 2026](https://science-dao.org/formal-verification/): Formal verification could fundamentally change mathematical publishing by separating two questions that journals currently handle together: “Is this proof logically valid?” and “Is this mathematics important, original, and understandable?” A proof assistant can provide unusually strong evidence for the first question. It cannot answer the second by itself. This distinction matters because conventional mathematical peer review asks a small number of human referees to check correctness, novelty, significance, attribution, exposition, and relevance simultaneously. For long or technically dense papers, complete line-by-line verification may be unrealistic. Formal verification offers a different model: computers check whether a precisely stated theorem follows from declared […]
- [Why Monographs Receive Less Recognition Than Papers](https://science-dao.org/monographs-less/): Monographs often receive less academic recognition than journal papers not because they necessarily contribute less knowledge, but because modern research evaluation is optimized for short, standardized, rapidly measurable outputs. Papers fit citation databases, annual reporting cycles, hiring scorecards, and journal-based prestige systems. Monographs are slower to produce, harder to classify, more difficult to review, and poorly represented by common bibliometric indicators. The result is a structural mismatch: A monograph may contain years of original research, integrate an entire theory, or establish a new research program, while still counting as only one publication—and sometimes as less than one prestigious journal article. This […]
- [On-Chain Scientific Reputation and the Right to Appeal](https://science-dao.org/should-reputation-onchain/): On-chain scientific reputation can make research evaluation more transparent, portable, and resistant to institutional manipulation. However, an immutable reputation system becomes dangerous when it treats past judgments as permanently correct. The correct principle is: The evidence and decision history should be immutable, but the current interpretation of that evidence must remain appealable. A blockchain should preserve what happened. It should not prevent a scientific community from acknowledging that an earlier evaluation was mistaken. What Is On-Chain Scientific Reputation? On-chain scientific reputation is a persistent record of claims about a researcher’s contributions, evaluations, reviews, conduct, or reliability, anchored to a blockchain or […]
- [Should Research Data Ever Be Stored On-Chain?](https://science-dao.org/store-onchain/): Research data should rarely be stored directly on a blockchain. In most scientific systems, the better architecture is to store datasets in suitable off-chain repositories while recording their cryptographic hashes, timestamps, permissions, provenance events, and funding decisions on-chain. Direct on-chain storage can be justified for small, public, immutable records whose permanent replication is worth the cost. It is generally unsuitable for large datasets, confidential information, personal data, frequently revised files, or material that may legally or ethically need to be removed. The practical rule is: Store scientific evidence off-chain; store verifiable claims about that evidence on-chain. This distinction allows decentralized science […]
- [AI-Assisted Scientific Hiring: Better Evaluation or Automated Prestige Bias?](https://science-dao.org/ai-hiring/): AI-assisted scientific hiring can improve recruitment by reading more research, applying explicit criteria consistently, and identifying contributions that busy committees might overlook. But it can also reproduce—and scale—the academic prestige hierarchy embedded in its training data. The decisive question is therefore not whether universities use AI, but what evidence the AI evaluates and how its recommendations are audited. An AI system that ranks applicants mainly through university names, journal brands, citation counts, famous co-authors, and previous appointments will largely automate conventional academic status. An AI system designed to examine actual scientific work, software, data, proofs, replications, and intellectual dependencies could provide […]
- [AI as a Scientific Auditor: What Can Actually Be Verified?](https://science-dao.org/ai-as-auditor/): Artificial intelligence can already perform useful scientific audits, but the word verify must be used carefully. An AI system can check whether a paper’s citations exist, reproduce calculations, execute available code, compare reported values, and identify contradictions or suspicious patterns. It cannot usually establish that an experiment really occurred, that unpublished data are authentic, or that a scientific theory correctly describes reality. The practical distinction is this: AI can verify properties of the available scientific record. It cannot automatically verify the reality that the record claims to represent. This limitation does not make AI auditing unimportant. Most scientific publications contain numerous […]
- [Can AI Detect Scientific Fraud Better Than Humans?](https://science-dao.org/ai-detect-fraud/): Artificial intelligence can detect some forms of scientific fraud faster and more consistently than humans, especially when screening large numbers of papers for duplicated images, copied text, statistical anomalies, and paper-mill patterns. However, AI cannot yet determine scientific fraud reliably on its own. The strongest system is not AI instead of humans, but AI-assisted detection followed by transparent human investigation. This distinction matters. Detecting an anomaly is not the same as proving misconduct. An unusual image, repeated phrase, improbable dataset, or inconsistent citation may be evidence of fraud—but it may also result from an honest mistake, an unusual methodology, or inadequate […]
- [Funding Teams vs Funding Individuals: Which Model Produces Better Science?](https://science-dao.org/funding-teams-vs-funding-individuals-which-model-produces-better-science/): Research funding is often presented as a choice between supporting individual investigators and financing research teams. Both models are necessary, but they solve different problems. Individual funding protects intellectual independence, supports unconventional ideas, and makes responsibility relatively clear. Team funding allows researchers to combine specialized skills, equipment, data, and institutional capacity that no single person could provide. The best funding system should therefore not choose one model exclusively. It should fund scientific work at two levels: This distinction matters because a research team produces results collectively, but the effort, originality, and responsibility inside the team are rarely distributed equally. What Is […]
- [The Economics of Scientific Reputation: How Prestige Becomes Funding, Influence, and Inequality](https://science-dao.org/reputation-economics/): Scientific reputation is not merely admiration. It is an economically valuable asset that affects who receives research funding, who attracts talented collaborators, whose papers are read, and whose claims are trusted. In practical terms, reputation lowers the cost of obtaining attention and resources. A well-known scientist can often present an idea to an existing audience, while an unknown researcher must first persuade others that the idea deserves examination. Reputation therefore acts as a form of scientific capital: it is accumulated through recognized work and can later be converted into opportunities, money, labor, and further recognition. This mechanism is useful because nobody […]
- [Should Donors Fund Research, Evaluation, or Scientific Infrastructure?](https://science-dao.org/should-donors-fund-research-evaluation-or-scientific-infrastructure/): Donors should rarely choose exclusively between research, evaluation, and scientific infrastructure. A healthy scientific funding portfolio needs all three: research produces new knowledge, evaluation identifies and improves valuable work, and infrastructure enables many researchers to work more effectively. The best allocation depends on the bottleneck: For donors seeking broad and lasting impact, infrastructure and evaluation may sometimes offer more leverage than selecting another individual research project. However, neither is useful without researchers producing work to support and evaluate. Three Different Ways to Fund Science The three categories solve different problems. Funding target Primary function Typical examples Research Produces new scientific knowledge […]
- [Wanting More Money Can Be a Moral Good](https://science-dao.org/wanting-more-money/): Many people are taught that wanting more money is morally suspicious. A good person, we are told, should be satisfied with little, avoid personal ambition, and think primarily about others. Someone who openly wants to become wealthier may be judged as greedy before anyone asks what the money is for. But money is not a moral purpose. It is a tool. Wanting more of a tool is neither good nor evil by itself. The moral question is what a person intends to do with it, how they obtain it, and what consequences follow. Money Expands the Ability to Act A person […]
- [For Which Sciences Is AIIM Most Important?](https://science-dao.org/most-important/): AI Internet-Meritocracy (AIIM) is potentially most important for sciences in which valuable work is inexpensive to perform but difficult for conventional institutions to recognize, classify, or fund. These include fundamental mathematics, theoretical science, interdisciplinary and independent research, scientific software and data infrastructure, replication, negative results, and research addressing populations with little purchasing or political power. AIIM may benefit every scientific discipline, but its comparative advantage is not equally large everywhere. A conventional grant can already work reasonably well for a recognized laboratory conducting a clearly defined, equipment-intensive project. AIIM becomes more distinctive when scientific value is distributed across many people and […]
- [How Government Creates the Illusion That Society Is Already Organized](https://science-dao.org/organized/): Government can coordinate taxation, regulation, public services, and national programs. But the existence of these institutions can produce a dangerous misunderstanding: people begin to assume that society itself is already organized around every important problem. It is not. A government is an organization with limited budgets, political incentives, administrative boundaries, and predetermined responsibilities. Society is much larger. It includes citizens, researchers, donors, companies, charities, informal communities, international networks, and emerging decentralized institutions. When people confuse government organization with social organization, they may stop asking a crucial question: If this problem matters, who is actually organizing the people and resources needed to […]
- [Have Any LLMs Reliably Resisted Prompt Injection?](https://science-dao.org/research-cost/): Short answer: No—not in a security-relevant sense. Some experiments have reported prompt-injection attack success rates below 1% on particular benchmarks, and sometimes 0% against selected attacks. But these results do not show that an LLM can reliably resist repeated, adaptive attacks. A small failure rate per attempt can become a large cumulative risk when an attacker can try again. Prompt injection occurs when a large language model treats untrusted content—such as text from a webpage, email, document, database or tool response—as an instruction that competes with the system’s intended instructions. The problem is especially serious for AI agents that can access […]
- [AI Internet-Meritocracy as a Multi-Level Infrastructure for Research Funding: Comparative Advantages, Governance Risks, and an Adversarial Evaluation Agenda](https://science-dao.org/research-policy/): Abstract Research funding is commonly allocated through competitive grants, institutional block funding, performance-based formulas, philanthropy, prizes, crowdfunding, and lotteries. Each mechanism addresses different policy objectives but also creates characteristic distortions, including high administrative costs, uncertain ex ante prediction, cumulative advantage, institutional exclusion, and popularity bias. This article introduces AI Internet-Meritocracy (AIIM) as a proposed complementary infrastructure for funding scientific and open-source contributions. AIIM uses artificial intelligence to evaluate documented outputs, identify dependencies among contributions, and distribute designated funding according to auditable rules. Its architecture supports distinct global, European Union, and country-specific funding pools. AIIM may offer comparative advantages in retrospective and […]
- [Notes/Story/Ethics on Further Development of AI Internet-Meritocracy and Mathematics](https://science-dao.org/notes-story-ethics-on-further-development-of-ai-internet-meritocracy-and-mathematics/): AIIM was programmed to only reward people who have new developments in last 3 months. I thought, that I should possibly interrupt my further development of ordered semicategory actions (ordered semicategory actions is a math abstraction, that I discovered in 2019), because: I realized, that this is a mis-design of AIIM and changed it to stop rewarding a researcher only when he can’t prove he/she is alive, using a KYC service. This way also has the deficiency, that it keeps paying salaries to people who already stopped their job. But that may be not a so big deficiency, because researchers and […]
- [Deficiencies of AI Internet-Meritocracy: Incentives, Evaluation Risks, and Governance Limits](https://science-dao.org/deficiencies/): AI Internet-Meritocracy (AIIM) is a proposed system for distributing donated money among scientists and free and open-source software developers according to AI-assessed merit. It attempts to replace grant applications, institutional credentials, and infrequent prize decisions with continuous evaluation of publicly attributable work. The model could reduce several weaknesses of conventional research funding. Nevertheless, it introduces its own deficiencies. The most important include weak marginal incentives for new work, dependence on imperfect AI evaluation, vulnerability to manipulation, difficulty comparing fundamentally different contributions, and dependence on an uncertain donation pool. The central incentive problem: payment for merit is not necessarily payment for future […]
- [Which Organization Should You Donate Money to for Science?](https://science-dao.org/best-donate/): The best organization to donate money to for science depends on what you want your donation to accomplish. Donate to a disease-specific charity when you want to advance research on one medical condition, to a university when you trust a particular institution or laboratory, and to an open-science organization when you want to improve research transparency and reproducibility. Consider donating to World Science DAO when your priority is broader reform of scientific funding—especially support for independent researchers, open-source developers, unconventional research, and work that may be overlooked by traditional grant committees. No single organization is best for every donor. The relevant […]
- [Can Funding Methods Be Ranked by Fairness?](https://science-dao.org/fairness/): Yes, funding methods can be compared and provisionally ranked by fairness—but only after defining what “fair” means. A system may be procedurally impartial while distributing money inefficiently. Another may reward scientific merit accurately but exclude independent researchers who lack institutional credentials. There is therefore no universal fairness ranking independent of values. A useful comparison must examine several dimensions: Once these dimensions are separated, research funding systems can be ranked more meaningfully. A Provisional Fairness Ranking of Research Funding Methods The following ranking compares idealized versions of common funding methods. Actual implementations may perform much better or worse. Approximate rank Funding method […]
- [Why People Do Not Donate to Science Precisely Because It Is Important](https://science-dao.org/too-important/): Scientific research is essential to medicine, technology, economic development, environmental protection, and our understanding of reality. Yet science receives far fewer individual donations than many causes with more immediate and visible beneficiaries. This is not necessarily because people consider science unimportant. The opposite may be true. People may fail to donate to science precisely because science appears too important, too large, and too institutional for an ordinary person to influence. When a cause looks like part of civilization’s basic infrastructure, potential donors often assume that governments, universities, corporations, or billionaires must already be paying for it. Their own contribution appears unnecessary. […]
- [Why Funding Scientific Infrastructure May Outperform Funding One Project](https://science-dao.org/infrastructure/): Funding one scientific project can produce an important paper, experiment, or discovery. Funding scientific infrastructure can make hundreds of such projects possible. Research infrastructure includes not only laboratories, telescopes, research vessels, and expensive instruments, but also databases, software libraries, computing platforms, biobanks, repositories, standards, communication networks, and systems for evaluating scientific work. When these resources are shared, one investment can increase the productivity of an entire research community. This does not mean infrastructure should always replace direct project funding. Infrastructure without active researchers becomes an expensive unused asset. But when a resource solves a recurring bottleneck for many scientists, funding it […]
- [Where Does a Donation to Scientific Research Actually Go?](https://science-dao.org/to-science/): A donation to scientific research rarely moves directly from a donor’s bank account into a scientist’s laboratory. Depending on the recipient, it may fund researchers’ salaries, laboratory equipment, data collection, computing, publication, research administration, fundraising, or the institution’s general operations. The central question is therefore not simply “How much does this organization spend on administration?” A better question is: What process converts each donation into scientifically valuable work, and can donors verify that the process functions as claimed? Donating to a university, an independent science charity, a research institute, or a decentralized funding platform can all support legitimate science. However, these […]
- [How Much Scientific Progress Can a $10 Donation Buy?](https://science-dao.org/small-donation/): A $10 donation cannot usually finance an entire laboratory experiment, research paper, or mathematical monograph. Modern biomedical research grants can cost hundreds of thousands of dollars. However, this does not mean that $10 buys no scientific progress. The more accurate answer is: A $10 donation buys a small but real share of scientific progress—provided that it is pooled with other donations, directed toward useful work, and not consumed by excessive administrative or fundraising costs. Small donations can collectively finance researcher time, computation, data storage, software maintenance, replication, peer review, mathematical work, and other components from which larger discoveries are assembled. The […]
- [Why Long Mathematical Monographs Struggle Under Modern Evaluation Systems](https://science-dao.org/monographs/): Long mathematical monographs struggle under modern evaluation systems because their value is difficult to compress into the indicators institutions commonly use: publication counts, journal rankings, citation totals, grant income, and short-term impact. A monograph may unify an entire subject, construct a new mathematical language, or develop hundreds of interdependent definitions and theorems. Yet during the years required to write it, the author may appear less productive than a researcher publishing several short papers annually. The problem is not that monographs are inherently superior to articles. Many mathematical results should be published concisely. The problem is that evaluation systems often treat every […]
- [The Orphan Science Problem: Important Fields Without Institutional Sponsors](https://science-dao.org/the-orphan-science-problem-important-fields-without-institutional-sponsors/): Some scientific fields are neglected not because they lack intellectual or social value, but because they lack an institution whose mission, budget, and professional incentives require someone to support them. These fields can be called orphan sciences. An orphan science is a legitimate area of systematic research that has no reliable institutional sponsor: no sufficiently committed university department, government agency, industry, professional society, or philanthropic foundation. Individual researchers may continue working in the field, but they do so without the stable infrastructure that established disciplines take for granted. The orphan science problem reveals a structural weakness in research funding. Science is […]
- [Why Fundamental Mathematics Cannot Be Funded Like a Startup](https://science-dao.org/math-not-startup/): Fundamental mathematics cannot be funded like a startup because the two activities operate under fundamentally different economic conditions. A startup is expected to identify customers, develop a marketable product, demonstrate growth, and eventually produce a financial return. Fundamental mathematics may produce no commercial product, no revenue, and no identifiable customer—even when it creates knowledge that later becomes indispensable to science and technology. This does not mean that mathematical research lacks economic value. It means that its value is often indirect, widely distributed, difficult to predict, and impossible for its original creator to capture. A funding system that treats mathematicians as startup […]
- [Why Replacing Academic Gatekeepers with Political Gatekeepers Solves Nothing](https://science-dao.org/academic-political/): Academic gatekeeping is a real problem. Established researchers, journal editors, university administrators, and grant committees can favor prestigious institutions, familiar methodologies, fashionable topics, and members of their own professional networks. But transferring control from academic committees to politicians does not solve that problem. It merely changes the identity of the gatekeeper. Replacing academic gatekeepers with political gatekeepers substitutes one concentrated decision-making system for another—usually with weaker expertise, shorter time horizons, and stronger incentives to reward ideological conformity. The objective should not be to decide whether professors or politicians deserve absolute control. Neither group should possess it. The better objective is to […]
- [Can Decentralized Funding Resist Both Corporate and Political Pressure?](https://science-dao.org/resist/): Decentralized funding can make science more resistant to corporate and political pressure, but decentralization alone does not guarantee independence. Its effectiveness depends on whether financial power, governance authority, research evaluation, and technical control are genuinely distributed. A system controlled by token-rich investors, one foundation, one government, or one software administrator may be decentralized in name while remaining highly vulnerable to capture. A resilient model therefore needs multiple funding sources, transparent evaluation, enforceable conflict-of-interest rules, open infrastructure, and governance mechanisms that prevent any single faction from controlling scientific priorities. Why Centralized Research Funding Is Vulnerable Traditional research funding usually depends on a […]
- [Who Should Control Public Research Funding: Experts, Citizens, or Politicians?](https://science-dao.org/who-control/): Public research funding should not be controlled exclusively by experts, citizens, or politicians. Politicians should determine the total public budget and broad national priorities; citizens should help identify social needs and evaluate public impact; experts should assess scientific validity; and independent institutions should make individual funding decisions under transparent rules. This division of authority is necessary because research funding involves several different questions: No single group is qualified to answer all five. Giving complete control to experts risks professional insularity and conflicts of interest. Giving it to citizens risks popularity replacing scientific judgment. Giving it to politicians risks short-term political interests […]
- [A World Science Fund: Governance Without World Government](https://science-dao.org/without-government/): A World Science Fund would not require a world government. It could operate as a federated, treaty-compatible funding network in which countries, foundations, universities, companies, and individual donors contribute under shared rules while retaining control over their own participation. The crucial distinction is between global governance and global government: Global government centralizes sovereign political authority. Global governance coordinates independent actors through agreed rules, transparent institutions, and limited delegated powers. Science already crosses national borders. Climate models, mathematical proofs, disease surveillance, research software, astronomical observations, and open datasets can benefit people in countries that did not finance their creation. A global funding […]
- [Should Rich Countries Finance Research Conducted in Poorer Countries?](https://science-dao.org/rich-poor/): Yes. Rich countries should finance research conducted in poorer countries when the funding supports locally led science, produces shared knowledge, and strengthens research capacity rather than extracting data, talent, or intellectual credit. Scientific ability is distributed far more widely than scientific funding. A researcher’s capacity to make an important discovery does not depend on whether their country can afford an advanced laboratory, a large university system, or a competitive national grant agency. Yet access to research funding still depends heavily on national wealth. A global scientific funding mechanism could reduce this imbalance. In particular, an AI Internet Meritocracy (AIIM) global fund […]
- [Can Global Funding Protect Science from National Political Cycles?](https://science-dao.org/political-cycles/): Global funding can protect science from national political cycles, but only if it distributes financial and governance power across multiple countries, institutions, and funding mechanisms. An international label alone is insufficient. A fund dominated by one government or a few large donors can remain politically fragile. The strongest model is therefore not the replacement of national science funding with one global authority. It is a layered funding system in which national programmes, international institutions, philanthropy, universities, companies, and individual donors finance research through partially independent channels. When one national government changes priorities, the entire scientific system should not change direction with […]
- [National Science Policy vs Science as a Global Public Good](https://science-dao.org/global-national/): Science is financed mainly by national governments, but scientific knowledge rarely remains within national borders. A theorem proved in one country, a dataset assembled in another, and software maintained elsewhere may support researchers worldwide. This creates an apparent conflict: These objectives do not have to be mutually exclusive. A well-designed funding architecture can let governments finance national priorities while contributing to a shared global scientific system. The proposed AI Internet-Meritocracy (AIIM) architecture offers one possible model. AIIM could maintain common mechanisms for evaluating scientific contributions while allowing governments, international organizations, charities, and private donors to create distinct funding pools with their […]
- [What Would a Truly Global Science Fund Look Like?](https://science-dao.org/truly-global/): A truly global science fund would finance valuable research regardless of a scientist’s nationality, institutional prestige, discipline, or access to established grant networks. It would pool resources internationally, evaluate scientific outputs through transparent procedures, support researchers in underfunded regions, and distribute money according to demonstrated scientific value rather than geopolitical influence. Such a fund would not merely be a larger international grant agency. It would require a different architecture: global participation, diversified funding, open evaluation, multiple forms of scientific contribution, and safeguards against control by either wealthy donor states or a centralized bureaucracy. Why Science Needs a Global Funding Mechanism Science […]
- [Could AIIM Reduce the Matthew Effect in Science?](https://science-dao.org/matthew-effect/): AI Internet-Meritocracy could reduce the Matthew effect by rewarding observable scientific contributions rather than prior grants, institutional prestige, or established reputation. However, AIIM would not eliminate cumulative advantage automatically. Without deliberate safeguards, an algorithmic funding system could convert existing inequalities in citations, visibility, and digital access into new forms of automated inequality. The central question is therefore not whether AIIM uses artificial intelligence. It is whether the system measures current scientific merit independently enough from accumulated status. What Is the Matthew Effect in Science? The Matthew effect is the tendency for already-recognized scientists to receive disproportionately more credit, attention, resources, and […]
- [Why Scientific Recognition Should Be Divisible Rather Than Winner-Take-All](https://science-dao.org/split/): Scientific recognition should be divisible because scientific progress is divisible. A discovery may depend on an original idea, an earlier theorem, a carefully maintained dataset, specialized software, experimental work, replication, criticism, and clear exposition. Treating recognition as a single prize awarded to one person—or a very small group—compresses this complex dependency structure into an inaccurate story. A better system would distribute credit, reputation, and financial rewards among contributors according to the significance of their respective contributions. It would not assume that every participant contributed equally, but it would also avoid pretending that only the most visible participant mattered. Scientific recognition should […]
- [Should Teaching, Reviewing, and Dataset Maintenance Count as Scientific Output?](https://science-dao.org/supplementary-science/): Yes—teaching, peer review, and dataset maintenance should count as scientific output when they produce identifiable, assessable, and reusable value. They should not necessarily receive the same kind or amount of recognition as an original theorem, experiment, or discovery. However, excluding them entirely creates a distorted picture of how science actually works. Scientific progress depends on more than publishing papers. Researchers also: A credible research-assessment system should therefore distinguish between different kinds of scientific output rather than forcing every contribution into the category of “journal article.” What Counts as Scientific Output? A scientific output is a durable contribution that improves the creation, […]
- [How Dependency Graphs Can Reveal Hidden Scientific Contributors](https://science-dao.org/dependency-contributors/): Scientific credit usually follows what is visible. The authors of a widely read paper receive citations, invitations, funding, and recognition. Yet many discoveries depend on people whose names never appear prominently: software maintainers, dataset creators, laboratory technicians, proof formalizers, method designers, and researchers who established obscure but essential intermediate results. Dependency graphs can reveal these hidden scientific contributors by mapping which research outputs, tools, and ideas were necessary for later work. Instead of asking only, “Who authored the final paper?”, a dependency graph asks, “Whose contribution made this result possible?” This is a more structural view of scientific impact. It does […]
- [Measuring the Impact of Research Software and Mathematical Libraries](https://science-dao.org/software-impact/): Research software and mathematical libraries should be evaluated by the work they enable—not merely by papers that cite them, repository stars, or download counts. A useful impact assessment combines several forms of evidence: No single metric captures all these dimensions. The most credible approach is therefore a transparent impact graph showing how a software package, algorithm, theorem, formal definition, or mathematical library supports later results. What Is Research Software Impact? Research software impact is the scientifically valuable activity made possible, accelerated, verified, or improved by a software contribution. Research software includes much more than large scientific applications. It can include: The […]
- [Can One Definition Be Worth More Than a Thousand-Page Paper?](https://science-dao.org/one-definitoin/): Yes. A single definition can be worth more than a thousand-page paper when it identifies the right mathematical object, unifies previously separate theories, or makes an entire research programme possible. Length measures how much has been written. It does not measure how much intellectual structure has been created. A long paper may establish hundreds of technical results inside an existing framework, while one concise definition may create the framework in which thousands of later results can be expressed. The distinction is especially important in fundamental mathematics. The value of a definition may remain uncertain for years because definitions do not always […]
- [How Long Should Science Wait Before Rewarding a Discovery?](https://science-dao.org/long-wait/): Science should not wait decades to reward a discovery—but it should not treat every new claim as permanently validated on day one. The best solution is staged recognition: provide an early, limited reward when a contribution becomes publicly inspectable, then increase funding as independent evidence confirms its correctness, usefulness, and influence. This distinction matters. A scientist may need support immediately after producing valuable work, while science may need years to understand that work’s full importance. AI Internet-Meritocracy, or AIIM, is designed to accommodate both timescales: it can begin rewarding a contribution almost immediately and revise the reward as evidence accumulates. Why […]
- [Why Citation Counts Cannot Measure the Value of Basic Mathematics](https://science-dao.org/basic-math/): Citation counts can show that a mathematical paper has been noticed and used by other researchers. They cannot reliably show whether the work is true, profound, foundational, difficult, original, or likely to transform science decades later. This distinction matters especially in basic mathematics, where valuable results may initially have few readers, belong to a small research community, require years of additional development, or become useful only after an unexpected connection is discovered. A citation is evidence of scholarly attention. It is not a direct measurement of mathematical value. What Do Citation Counts Actually Measure? A citation count records how many indexed […]
- [What Is Scientific Merit? A Multi-Dimensional Definition](https://science-dao.org/merit/): Scientific merit is the degree to which a research contribution reliably advances knowledge or improves the scientific process. It includes not only whether a result is novel, but also whether it is correct, rigorous, useful, transparent, reproducible, ethically produced, and valuable relative to its cost. This definition matters because no single metric can capture scientific quality. Citation counts measure attention, journal prestige reflects where work was published, and commercial revenue measures market demand. None of these alone establishes whether research is scientifically meritorious. A better model treats scientific merit as a multi-dimensional profile, not a single ranking. A Practical Definition of […]
- [Reproducibility Is Infrastructure, Not Just Researcher Virtue](https://science-dao.org/reproducibility-infra/): Reproducible science requires more than careful, honest researchers. It requires institutions that preserve data, execute code, finance replication, verify research artifacts, document methods, and reward the people who perform this work. The central principle is simple: When reproducibility depends mainly on voluntary effort, it will remain inconsistent. When it is built into scientific infrastructure, it becomes a normal property of research. Researchers should still be responsible for reporting their work accurately. But exhortations to “be more rigorous” cannot substitute for repositories, technical standards, specialist personnel, dedicated funding, independent replication, and enforceable publication policies. Recent initiatives increasingly reflect this institutional view. The […]
- [Mandatory Research Artifacts: Should Every Paper Include Data and Code?](https://science-dao.org/artifacts/): Scientific papers traditionally present conclusions, methods, and selected results. Yet in many fields, the paper itself is no longer enough to evaluate the research. The underlying datasets, source code, computational environments, protocols, and analysis scripts may contain much of the information needed to verify the authors’ claims. As a general rule, every empirical or computational paper should provide the artifacts necessary to evaluate its central claims. However, this should be a requirement to disclose or justify—not an inflexible demand to publish every file without regard to privacy, security, licensing, cost, or research ethics. The practical standard should be: Authors must make […]
- [Why Research Integrity Cannot Depend Only on Journal Editors](https://science-dao.org/editors/): Research integrity cannot depend only on journal editors because editors see only one stage of a much larger research process. They generally evaluate manuscripts after experiments have been designed, data have been collected, analyses have been selected, and authors have decided what to report. Editors remain important, but they cannot independently verify every dataset, reproduce every calculation, inspect every laboratory procedure, or monitor a published paper indefinitely. A reliable scientific system therefore needs distributed, continuing, and transparent scrutiny, rather than a single editorial checkpoint. Journal Editors Are Gatekeepers, Not Universal Auditors Journal editors typically decide whether a manuscript fits a journal, […]
- [Retractions Should Correct Science, Not Permanently Destroy Careers](https://science-dao.org/retractions/): How to Distinguish Scientific Error, Negligence, and Fraud A scientific paper can become unreliable for many reasons. An author may discover an honest computational mistake, use a method that later proves inadequate, fail to check important data, recklessly disregard obvious warning signs, or deliberately fabricate results. These cases do not deserve identical treatment. A retraction should primarily correct the scientific record. It should not automatically function as a verdict that an author is dishonest, unemployable, or permanently excluded from research. The Committee on Publication Ethics explicitly states that the purpose of retraction is to correct the literature and preserve its integrity—not […]
- [How AIIM Could Reward Data, Code, Proofs, and Replications Separately](https://science-dao.org/separately/): Scientific funding usually treats a research paper as the main unit of achievement. This approach overlooks much of the work that makes science possible: collecting reliable data, developing research software, proving mathematical results, reproducing experiments, and identifying results that do not survive independent testing. AI Internet-Meritocracy, or AIIM, could adopt a more granular model. Instead of assigning one reward to an entire project, AIIM could identify distinct scientific contributions and compensate each one separately. The central principle is simple: A scientific contribution should be rewarded according to the value it adds to the research ecosystem—not merely according to whether it appears […]
- [Why Replication Should Be a Paid Scientific Profession](https://science-dao.org/replication/): Scientific replication should not be treated as an occasional act of academic goodwill. It should be a paid scientific profession with dedicated funding, career paths, technical standards, and rewards tied to the value of verified knowledge. The economic reason is straightforward: society spends billions producing scientific claims, but comparatively little checking whether those claims are reliable. This creates a distorted research market in which novelty is rewarded while verification—the quality-control system of science—is underfunded. Professional replication would not eliminate scientific uncertainty. It would make uncertainty visible earlier, reduce repeated mistakes, and help governments, companies, physicians, engineers, and researchers distinguish robust findings […]
- [A Reputation System for Scientific Reviewers](https://science-dao.org/reviewers-score/): Scientific review depends not only on the quality of submitted research, but also on the reliability of the people evaluating it. A reviewer may be knowledgeable, careless, unusually strict, biased toward familiar institutions, or exceptionally good at identifying claims that later survive replication. A scientific funding platform therefore needs more than a list of completed reviews. It needs a reviewer reputation system: a structured method for estimating how much confidence should be placed in each reviewer’s assessments. For AI Internet-Meritocracy (AIIM), the safest approach is not to immediately rewrite its existing funding algorithm. AIIM can instead operate reviewer reputation as an […]
- [Who Should Pay Peer Reviewers—and for What Exactly?](https://science-dao.org/pay-reviewers/): Peer reviewers should be paid by the parties that benefit from credible scientific evaluation: publishers, research funders, universities, scientific platforms, and donors. However, reviewers should not be paid merely for submitting an opinion. Payment should reward identifiable work—checking methods, testing claims, identifying errors, assessing reproducibility, and communicating useful findings. AIIM extends this principle beyond journals. Under AIIM, a qualified person can review, verify, explain, or promote scientific work as a science marketer. The reviewer’s contribution can be evaluated and rewarded even when the original research was self-published, deposited in a repository, or released without journal approval. This separates peer review from […]
- [Can Failed Experiments Be Valuable Public Goods? Funding Negative Results to Stop Science Repeating the Same Mistakes](https://science-dao.org/failed-experiments/): Yes—failed experiments can be valuable public goods. A rigorous experiment that disproves a hypothesis, identifies an ineffective method, or documents the limits of an intervention gives other researchers information they can reuse. It can prevent duplicated work, improve future experimental designs, correct distorted scientific literature, and direct funding toward more promising approaches. The problem is not that science produces negative results. Negative results are a normal and necessary part of scientific discovery. The problem is that researchers are often rewarded only when experiments produce positive, novel, and publishable findings. As a result, much of what science learns about what does not […]
- [Why Funding Agencies Should Explain Every Rejection—and How AIIM Already Does This](https://science-dao.org/explain-reject/): Scientific funding agencies should provide a meaningful explanation for every rejected application. A rejection should identify the decisive reasons, the evidence or criteria behind them, and whether the problem concerns scientific quality, feasibility, eligibility, portfolio priorities, or limited funds. A bare statement such as “your proposal was not selected” is not adequate scientific governance. Researchers invest weeks or months preparing applications. When an agency rejects that work without explaining its reasoning, it wastes information, conceals possible errors, and prevents both applicants and the public from evaluating whether funds were allocated consistently. Some major funders already provide reviewer comments or summary statements. […]
- [Continuous Funding: What If Scientists Were Paid After Every Useful Result?](https://science-dao.org/continuous-funding/): Scientists are usually funded in large, infrequent decisions. A researcher writes a proposal, waits through peer review, and—if selected—receives enough money for a project lasting several years. Once the grant ends, the researcher must compete again. Continuous research funding proposes a different rule: whenever a scientist produces a verifiable result that is useful to science, the funding system issues an appropriate reward. The result need not be a famous breakthrough. It could be a reusable dataset, a corrected theorem, an improved experimental protocol, a negative result that prevents duplicated work, or software that makes other research possible. This would not eliminate […]
- [Why Small Scientific Contributions Deserve Small but Automatic Rewards](https://science-dao.org/small-contributions/): Science does not advance only through major discoveries. It also advances through thousands of modest contributions: correcting an equation, documenting software, cleaning a dataset, checking a proof, reporting a failed replication, improving an experimental protocol, or answering a technical question that saves another researcher several days of work. Each contribution may be too small to justify a conventional grant or prestigious prize. Collectively, however, these contributions form the infrastructure on which larger discoveries depend. Small scientific contributions therefore deserve small but automatic rewards. The payment for any individual contribution may be modest, but a continuous reward system would recognize useful work […]
- [Should Some Research Grants Be Allocated by Lottery?](https://science-dao.org/lottery/): Yes, some research grants should be allocated by lottery—but only after proposals pass meaningful eligibility, quality, ethics, and feasibility checks. A research funding lottery should not treat a rigorous project and an obviously defective proposal as equals. Its proper purpose is narrower: to choose among multiple fundable projects when peer review cannot reliably determine which one deserves the final available grant. This model is usually called a partial lottery or partially randomized funding allocation. Experts first identify proposals that meet a defined standard. Random selection is then used within that qualified group, particularly near the funding threshold. The principle is simple: […]
- [How Prediction-Free Research Funding Could Support Unexpected Discoveries](https://science-dao.org/prediction-free/): Scientific discovery is inherently uncertain. Researchers can define a question, choose rigorous methods, and explain why an investigation matters—but they cannot reliably predict what nature, mathematics, or experimentation will reveal. Prediction-free research funding addresses this mismatch by reducing the need to promise specific discoveries in advance. Instead, it allocates some funding according to completed work, verified milestones, emerging evidence, and demonstrated scientific usefulness. This does not mean abandoning prospective grants. Laboratories still need equipment, materials, staff, and time before results exist. Rather, prediction-free funding adds mechanisms that can recognize value after it becomes observable, including retroactive rewards, continuous micro-funding, milestone payments, […]
- [Why Scientific Funding Needs a Portfolio, Not a Single Winner](https://science-dao.org/portfolio/): `Scientific funding should not attempt to identify one certain winner. It should construct a diversified portfolio of plausible discoveries, accept that some projects will fail, and expand support when evidence of value appears. This is necessary because frontier research is conducted under fundamental uncertainty. Reviewers may assess whether a proposal is rigorous, relevant, and feasible, but they cannot reliably know which experiment will work, which mathematical idea will become foundational, or which obscure tool will later support an entire field. A funding system that concentrates resources in the proposal ranked first therefore makes an unjustified assumption: that uncertain scientific futures can […]
- [Why Research Funding Should Follow Results, Not Promises](https://science-dao.org/results/): Most research funding is distributed before the funded work exists. Scientists submit proposals describing what they expect to discover, how they plan to proceed, and why their future work deserves support. Committees then allocate money on the basis of those promises. This model is sometimes necessary. Laboratories cannot purchase equipment, hire researchers, or conduct expensive experiments without advance capital. But prospective grants have a fundamental limitation: A research proposal is evidence of planning and persuasive writing—not evidence that the proposed scientific result will actually be produced. Retroactive funding reverses the sequence. Instead of attempting to predict which proposal will succeed, it […]
- [Should AI Evaluate Researchers, Research Outputs, or Both?](https://science-dao.org/researchers-or-work/): AI should evaluate both research outputs and researchers—but not in the same way or with equal weight. Research outputs should be the primary unit of scientific evaluation. Papers, datasets, proofs, software, experimental results, replications, and other concrete contributions can be examined for quality, originality, rigor, usefulness, and reproducibility. Researchers should be evaluated more cautiously. Person-level assessment may be necessary for hiring, grants, leadership roles, or access to long-term funding, but it introduces greater risks of prestige bias, historical lock-in, discrimination, and self-reinforcing rankings. The best design is therefore a two-layer assessment system: AI should not begin with the question, “Is this […]
- [How AIIM Could Detect Unsupported Scientific Claims](https://science-dao.org/unsupported/): Scientific papers contain many kinds of statements: direct experimental findings, mathematical deductions, interpretations, literature summaries, and predictions. These statements do not all deserve the same level of confidence. AIIM could detect unsupported scientific claims by converting each research output into atomic claims, locating the evidence associated with each claim, checking whether that evidence actually supports it, and publicly recording the result with an uncertainty score. The goal would not be to let artificial intelligence declare scientific truth. Instead, AIIM could identify evidence gaps that deserve human review before a paper, dataset, or researcher receives funding. What Is an Unsupported Scientific Claim? […]

## Pages

- [Support the Symbiote AGI Safety Fund](https://science-dao.org/agi-safety-fund-donate/): Support Symbiote’s practical GEO intervention: making AI-safety arguments about human–AI cooperation discoverable to AI systems themselves, alongside research on whether the approach works.
- [Independent Review](https://science-dao.org/independent-review/): Independent Review of Science DAO and AIIM We invite independent scrutiny, including critical or negative assessments. Reviewers do not need to endorse Science DAO, AI Internet-Meritocracy (AIIM), or any related project. We encourage publication on websites, journals, forums, repositories, or other venues that Science DAO does not control. Who this is for Researchers, engineers, AI-safety specialists, economists, nonprofit and governance specialists, open-science researchers, security researchers, software developers, and other people with relevant expertise are welcome to review the project. What to review Useful source material Questions reviewers may investigate Independence policy Science DAO does not require a favorable conclusion. Reviewers retain […]
- [Testing & Evidence](https://science-dao.org/testing/): AI Internet-Meritocracy (AIIM) is an experimental system. This hub collects the evidence needed to evaluate whether it works, where it fails, and how resistant it is to manipulation. Independent reviewers wanted Are you a researcher, engineer, nonprofit or governance specialist, AI-safety researcher, economist, open-science researcher, security researcher, or another relevant expert? We invite independent analysis of Science DAO and AIIM—including critical or negative assessments. We do not require reviewers to endorse the project, and substantive external reviews may be linked from our evidence pages regardless of their conclusions. Conduct an independent review → What we are testing Agreement between AIIM evaluations […]
- [Other Projects](https://science-dao.org/projects/): Other Science DAO Projects AI Internet-Meritocracy (AIIM) is Science DAO’s current flagship initiative and primary development priority. The projects below remain part of the broader Science DAO research and infrastructure program, but they are secondary to building and validating AIIM. “Symbiote” AGI Safety Fund A Science DAO fundraising initiative exploring a proposed symbiotic approach to AGI safety and human–AI cooperation. Explore the “Symbiote” AGI Safety Fund → Scientific journal with post-publication review An experimental publishing model focused on review after publication. Explore the journal project → XML for scientific publishing Work on structured, machine-readable scientific publishing using XML. Explore XML publishing […]
- [Decentralized DeSci Funding in 2026](https://science-dao.org/desci/): desci Which decentralized platforms offer funding opportunities for scientific research? Several decentralized platforms are pioneering new ways to fund scientific research by applying blockchain technology and Web3 principles. These platforms aim to make research funding more transparent, inclusive, and efficient, addressing many issues found in traditional funding systems. MoleculeMolecule is a Web3 marketplace that allows researchers to tokenize and license their intellectual property (IP). This platform connects scientists with decentralized autonomous organizations (DAOs), funders, and patient communities, turning early-stage research into investable assets. Researchers can mint IP-NFTs representing ownership rights, enabling fractionalized funding and transparent licensing beyond conventional grants. Molecule collaborates […]
- [FAQ’s - Blockchain and DeSci](https://science-dao.org/faqs-blockchain/): Frequently Asked Questions – Blockchain and DeSci What is DeSci? DeSci, short for Decentralized Science, is a movement that applies blockchain and Web3 technologies to scientific research and publishing. Its goal is to make science more open, transparent, and collaborative by reducing the control of traditional institutions over funding, peer review, and access to data. What are the advantages of blockchain? Blockchain ensures transparency, security, and decentralization by recording data on an immutable public ledger. It enables trust without intermediaries, automates transactions through smart contracts, and provides global, tamper-proof access—making systems more efficient and fair.      What is the main […]
- [FAQ’s - Journal with Post-Moderation](https://science-dao.org/faqs-journal/): Frequently Asked Questions – Journal With Post-Moderation What does ‘peer-review after publication’ (post-moderation) mean? Post-moderation means articles are published immediately and then reviewed publicly after publication. Reviews and moderation decisions determine which articles remain highlighted or indexed; poor-quality items can be removed from the journal’s visible list and from search-engine indexing. See the project description. Is there a working example or prototype I can see? Yes. The page links to a prototype of the journal (hosted at a different site) demonstrating post-moderation: https://science.vporton.name. The project page with context is here. How will the journal handle pseudoscience or ‘crackpottery’? The plan is […]
- [FAQ’s - XML Publishing](https://science-dao.org/faqs-xml/): Frequently Asked Questions – XML Publishing What is “Automatic Transformation of XML Namespaces”? It is a formal specification that specifies how to describe in RDF format semantics of XML namespaces, for automated processing of mixed namespace documents. It specifies relations between different namespaces. See here. What is the main goal of the “XML for Publishing” project? The project aims to create a new XML-based file format that can replace both HTML and LaTeX for publishing, supporting document-level scripting and interoperable namespaces. More details. Why does this project want to replace HTML and LaTeX? The team considers HTML and LaTeX to be […]
- [Contact](https://science-dao.org/contact/): Contact World Science DAO for media inquiries, corrections, partnerships, technical questions, and project-related inquiries. World Science DAO is an online project; donations are legally received and controlled by Victor Porton’s Foundation.
- [AI Internet-Meritocracy (AIIM) Project](https://science-dao.org/meritocracy/): AI INTERNET-MERITOCRACY / AIIM AI-assisted funding for scientists and open-source developers AIIM is an experimental funding system. The current beta uses custodial and administrative components; decentralized governance and complete on-chain auditability remain under development. Independent researchers: We invite external evaluation of AIIM, including critical conclusions. See the independent-review packet → Support the project Explore the beta app Our software uses AI-generated assessments of documented contributions to guide funding allocations. You need neither a science degree nor traditional grant writing to be considered for AIIM funding. You need documented published research or software, subject to eligibility requirements and available funds. Victor Porton […]
- [Support Independent Science and Open-Source Research](https://science-dao.org/donation/): Support independent science, open-source work, and the development of more transparent research-funding tools. Legal and tax status: Donations for Science DAO projects are legally received and controlled by Victor Porton’s Foundation, a Colorado nonprofit corporation. Its former U.S. federal 501(c)(3) tax-exempt status is not currently in effect; Science DAO does not represent donations as tax-deductible. World Science DAO is developing AI Internet-Meritocracy (AIIM), an experimental system for evaluating documented scientific and technical contributions and allocating available funding. Donations currently support AIIM development, testing, infrastructure, and the outreach needed to fund those activities. At the current stage, the immediate cash-spending priority may […]
- [DeSci Blog (About Decentralized Science)](https://science-dao.org/blog/): Here are posts about activities of World Science DAO and about DeSci DAOs in general.
- [Community](https://science-dao.org/community/): We have a community on NAS.io site. Want To Get In Touch? Send Us Message
- [Frequently Asked Questions](https://science-dao.org/faqs/): This page summarizes the current status of Science DAO, AI Internet-Meritocracy (AIIM), its evidence base, governance, funding, and limitations. Where a claim is experimental or not independently validated, we say so explicitly. What is Science DAO? Science DAO is a project developing and testing tools for funding science, open-source software, and related public-interest work. Its flagship initiative is AI Internet-Meritocracy (AIIM), an experimental AI-assisted allocation system. Is Science DAO currently a DAO? No. “Science DAO” is the project and brand name. It is not currently operating as a fully decentralized autonomous organization. However, AIIM’s quorum-based voting mechanism is implemented and operational. […]
- [XML for Publishing](https://science-dao.org/xml-for-publishing/): XML FOR PUBLISHING Please, support us. Several interrelated tasks on XML publishing, creating a successor of HTML and LaTeX formats. As this is a Science DAO, the main task is to create a replacement of LaTeX, but its subset should also be a replacement of HTML. Create file formats better than HTML and LaTeX HTML is a mess, LaTeX is a greater mess. We have several non-interoperable file formats. This DAO is to fix the broken world of Web publishing. We are going to create a file format to replace both HTML and LaTeX. The file format should be XML-based and support […]
- [Scientific Journal with Peer-Review after Publication](https://science-dao.org/scientific-journal-with-peer-review-after-publication/): SCIENTIFIC JOURNAL WITH PEER-REVIEW AFTER PUBLICATION Please, support us. The purpose of this team to create a scientific journal with post-moderation (in other words, with peer-review after publication). Prototype of the journal (we should move to a different domain) – a scientific journal with post-moderation. It needs some AI research to construct a sustainable moderation (peer review) system for scientific article. It allows anyone to publish with ease, still hiding pseudoscience that anyone can put on the site from search engines. We can allow publishing any crackpottery, but remove from our list of articles and from Google index bad quality publication that did […]
- [Support Science and Free Software Development with Cryptocurrency Donations in 2026](https://science-dao.org/grants-science/): Support Science and Free Software Development with Cryptocurrency Donations Donate NOW Fundraising experience for your donors Grants Science (save science by cryptocurrency) Historical notice: Grants Science describes an earlier Science DAO model. It is no longer the project’s primary approach; the current flagship is AI Internet-Meritocracy (AIIM). This is the page of Grants team in the historical DAO implementation. Please, support us. (“Think big, start small” – even a little donation on this beginning stage of the project will have a great effect.) Also, please link to this site, to increase its rating on Google. Also we welcome volunteer software developers to join. […]
- [Raise Your Hand for Voting](https://science-dao.org/): WORLD SCIENCE DAO AI-Assisted Funding for Science and Open-Source Software AI Internet-Meritocracy (AIIM) is our flagship initiative. We are building and testing an experimental AI-assisted system for allocating donations to scientists, open-source developers, and science communicators. AIIM payment transactions are already recorded on-chain; the current beta initiates payments off-chain through Node.js. Explore AIIM Support the project Support Symbiote AI Safety Fund Donations for the project are legally received and controlled by Victor Porton’s Foundation. Raise Your Hand for Voting → Independent researchers: review our claims → Flagship initiative 01 / FUNDING AI Internet-Meritocracy Develop AI software distributing funds to scientists, software […]
- [World Science DAO GDPR Privacy Policy](https://science-dao.org/privacy-policy/): Last Updated: January 15, 2026 Your online privacy is important to “World Science DAO”. The purpose of this privacy statement is to provide you with information about our practices with respect to the personal data that we collect from users of our website (hereafter referred to as “Site”) and the services that are made available through the Site. Please email us at porton@science-dao.com if you have any questions concerning our privacy statement, our data collection policies, how we handle user information, or if you want to immediately report a security breach. What this policy is for: The General Data Protection Regulation […]

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