Frequently Asked Questions

Frequently Asked Questions About SciWard

What is SciWard?

SciWard is an experimental AI-assisted research-funding system. The current beta uses custodial and administrative components. Payment transactions may be recorded on-chain, but SciWard’s governance and payment authorization operate off-chain under administrative oversight. There is no active on-chain governance system.

How does SciWard works?

1. Researchers submit their research sites (without any grant writing).

2. Sites are reviewed transparently by an AI.

3. Funding allocations are calculated and authorized off-chain by the current application.

4. Transactions remain publicly auditable forever.

Why blockchain?

Why Science DAO uses blockchain

• Full transparency of all donations and payouts

• Administrative oversight remains in place; SciWard does not currently provide decentralized control over funding

• An on-chain record of specified payment transactions, not on-chain governance decisions, subject to the properties and continued accessibility of the chosen blockchain

• Reduced administrative overhead

What do you present on this site?

On this site we present the SciWard initiative, the DAO to develop world science infrastructure: publishing, grants and salaries for scientists, etc. based on decentralized software architecture and cryptocurrency. The main project is SciWard app.

What is DAO?

Decentralized Autonomous Organizations (DAOs) are a new type of organization that uses blockchain technology and smart contracts to operate in a decentralized manner. They are gaining popularity as a way to fund and support various projects, including scientific research.

What is impact DAO?

Impact DAO = charity DAO, a DAO created to solve actual world problems, like global warming or human trafficking. the SciWard initiative is an impact DAO created to solve problems with science funding and publishing.

How are you going to control the world?

Simply by creating new software that will eat up the world. It’s like the story of Linux and of Bitcoin.

What is your flagship project?

Our flagship project is SciWard (SciWard) – the AI app for distributing salaries.

Why not traditional science funding?

• Institutional gatekeeping: funding not for everybody
• Traditional funding: opaque review process
• Science DAO: fully transparent proposal evaluation
• Traditional funding: slow grant distribution
• SciWard: automated off-chain allocation logic; any blockchain transfer is a separate payment-recording step

If an author of a fundamental discovery happens not to have a science degree (for example, as a result of discrimination) or for example is located in  Zimbabwe, then what I call “scientific covery” happens: The discovery receives no money for publicity, and it remains so even if rediscovered by an established PhD. This may take the world economy down by several times.

Existing mechanisms do not fully eliminate credential, institutional and visibility disadvantages.

Do I need an academic degree to receive a salary?

No, we don’t require academic degrees, but AI decides your salary based on your publications.

What is Grants Science?

Grants Science, a blockchain-based algorithm to distribute scientific grants in a smart way.

It is a more cumbersome alternative to SciWard (SciWard). SciWard is considered superior over Grants Science. But probably we will implement both.

How do I participate?

You participate by donating or by helping to set our DAO app. Bureaucracy is a paid work, that is you receive a cryptocurrency, for example, when you vote. To participate you need SCI tokens. Currently you can receive SCI tokens only by invitation, but it is planned to distribute the token widely, so that people be able to buy it at crypto exchanges.

Which blockchain you operate on?

We will operate on several chains.

Which DAO toolkit do you use?

Colony

Aren’t you afraid that giving control over money to AI, you endanger mankind?

Distributing money between scientists is a narrow task, just like chess. It does not give AI power to make any other decisions. So, it is safe.

How does the platform decide who gets paid and how much?

The app asks an AI to estimate what portion of world GDP a user is worth based on scanning their public web output and then allocates donated funds according to that estimated portion. Details.

Who can receive funding through this system?

Currently the software distributes money to scientists and free/open-source software (FOSS) developers themselves, regardless of formal degrees. Future plans include funding new roles like science marketers. For more.

How is SciWard different from existing donation platforms like Gitcoin or Giveth?

SciWard claims to use AI-driven merit estimation of individuals (based on their online contributions) to allocate donated funds, rather than relying on community matching or reputation-only mechanisms. See more.

Is the software open source and where can I inspect it?

Yes, the project has a public open software repository and development information; the site notes the software is almost ready but needs funding to fully launch.

How can I support the project?

You can donate, link to the site to increase visibility, or volunteer as a software developer. The site provides donation and contribution options

How does the project deal with AI prompt-injection or manipulation?

The project acknowledges prompt-injection and related AI integrity issues as an intricacy it must address; it is developing algorithmic defenses as part of the platform. More context.

Why is funding every scientist and FOSS developer important, according to the site?

The project argues that many valuable scientific contributions are lost or mis-published and that providing salaries and marketing support would prevent stagnation and accelerate progress. The rationale is explained here.

What are ‘science marketers’ and why are they planned?

Science marketers are a proposed new occupation to professionally market and promote scientific works, ensuring important research reaches the right audiences.

Where can I read the project’s paper or technical background?

The site links to a project paper and status pages describing the economic formation and technical approach.

How does the project view conventional academic credentials like science degrees?

The project criticizes degree-based gatekeeping (e.g., the Bologna system) as amplifying discrimination and aims to fund contributions regardless of formal degrees.

Are donations secure?

You donate at GiveButter (money) or Giveth (crypto) sites, big companies that secure their payments thoroughly. You don’t enter your credit card number at our site.

What are the organisation’s main goals?

Our goals include saving basic science, supporting discoveries, protecting researchers from predatory publishers, providing salaries to scientists, and promoting post‑publication moderation and XML publishing. Details.

What are “coveries”?

Coveries are valid scientific discoveries that remain unknown or under‑recognized because the system fails to promote or finance them—often when their authors lack formal academic affiliation. Learn more.

Why do coveries happen?

They occur when ministries and institutions fund only insiders, ignore promotion costs (PR, outreach, translation), and treat degrees or affiliations as gatekeepers rather than assessing content quality. Read the full explanation.

How do coveries harm society and the economy?

Overlooked discoveries can block technological advances, economic growth, and intellectual leadership—potentially costing trillions if useful ideas never reach application. Details.

Are coveries the same as bad or fringe science?

o—coveries refer to legitimate, documented discoveries neglected because of institutional barriers, not to unrigorous or pseudoscientific work. More context.

What should citizens demand from their Science Minister?

Citizens should push for funding that covers promotion as well as research, open access to promotion programs for all valid work, ending degree‑based gatekeeping, dedicated ‘covery funds,’ and public accountability reporting. See recommendations.

What concrete policies can reduce coveries?

Create transparent promotion grants open to independent researchers, allocate a budget line for discovery promotion, evaluate work by content quality not credentials, and require ministers to report outreach support metrics. Policy ideas.

How can I tell if my Science Minister is tolerating coveries?

Look for closed promotion programs favoring institutional applicants, lack of funding for outreach, no transparency about support for independent work, and persistent neglect of documented discoveries outside academia. Guidance.

What actions can I take if my minister tolerates coveries?

Write to your representatives, demand public reporting and dedicated promotion funds, vote for officials who back open promotion, back projects like Science DAO, and join campaigns calling for accountability or resignation if failures persist. Action steps.

Where can I learn more or support efforts to eliminate coveries?

Read this blog, call your science minister to resign, donate to this project.

How could Science DAOs multiply global GDP?

In an optimistic scenario, better discovery and allocation mechanisms could produce large economic benefits. Science DAO has not yet quantified this effect through a validated causal model.

We can speculate that by accelerating the pace of discovery, enabling faster commercialization of technologies, and scaling scientific coordination globally, Science DAOs could possibly increase the rate of innovation severalfold — with potentially trillions in economic impact if scaled worldwide. Details.

How has scientific funding evolved over time?

Scientific funding began with private patrons and personal wealth (e.g., Galileo, Newton), shifted to state-sponsored national science in the 19th–20th centuries, expanded into competitive grant systems after WWII, and more recently diversified with philanthropic, corporate, and decentralized (DeSci) models. See details.

Why is scientific visibility a global problem?

Many valid discoveries are trapped behind paywalls, institutional bias, formatting issues, or poor indexing, so AI and the public never see them — causing repeated rediscoveries and an incomplete scientific record. Details.

Why can’t AI alone solve the problem of hidden discoveries?

AI can only learn from what is visible and indexed online. If results are mis-published or hidden, even the best AI won’t detect them. The solution requires active exposure and reward systems as explained here.

Who is behind the project?

The project lead is Victor Porton, a mathematician and developer with 2.5 years of ICP experience and background in React, Node.js, and Rust. More details.

How does SciWard compare to platforms like Gitcoin or Giveth?

SciWard aims to outperform existing platforms by automating fair distribution using AI-driven policies rather than relying primarily on human or market-driven allocation. For the author’s comparison and reasoning, see here.

How can science degrees act as a “discrimination amplifier”?

Degrees (Bachelor, Master, PhD) create a hierarchy that often excludes talented people who lack formal credentials. When systems privilege degree-holders for funding, publication, or employment, important contributors without degrees can be ignored, slowing or blocking discoveries. See details.

Do I need to write a grant description or review projects to participate?

No — AIIS eliminates the requirement to manually create grant descriptions or to review and vet each grant; the AI handles distribution decisions.

How does AIIS handle many small projects from a single user?

AIIS is designed to take into account even very small projects a user runs, so a collection of small efforts can meaningfully contribute to that user’s income under the AI allocation model. See here.

What are the main security threats (e.g., prompt injection) and mitigations?

The proposal identifies prompt injection as a major threat and suggests countermeasures: an explicit ‘check for prompt injections’ instruction, banning users who inject prompts, manual review of top accounts, randomized prompt transformations (high temperature) to avoid fixed-prompt exploits, and bringing suspicious high-earnings accounts to human/AI scrutiny. Full discussion here.

What is GEO (gaming of endorsements) and how would it be handled?

GEO refers to coordinated or repeated endorsements (e.g., many pages praising someone) that could inflate value; the author proposes an anti-GEO prompt that computes a reducing coefficient rather than outright bans, to avoid abuse via false reports—see the article.

Will there be human oversight or audits over the AI?

There will be, at least on beginning stages. Maybe, later we’ll make the system fully automated, with automated replies to complain, and even automated appellations.

Which sciences does SciWard support?

We are going to support all modern sciences and their subfields, not limited to the below list. Here is the list of modern sciences and subfields:

NATURAL SCIENCES

1. Physics

• Classical Physics: mechanics, thermodynamics, electromagnetism, acoustics

• Modern Physics: relativity, quantum mechanics, quantum field theory, particle physics

• Applied Physics: condensed-matter physics, materials physics, nuclear engineering, optical physics

• Astrophysics & Cosmology: stellar physics, planetary science, cosmology, gravitational physics

• Interdisciplinary: biophysics, geophysics, medical physics

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2. Chemistry

• Organic Chemistry: synthesis, biochemistry, polymer chemistry

• Inorganic Chemistry: coordination chemistry, organometallics

• Physical Chemistry: thermodynamics, kinetics, spectroscopy, quantum chemistry

• Analytical Chemistry: chromatography, mass spectrometry, electroanalysis

• Materials Chemistry: nanochemistry, solid-state chemistry, surface chemistry

• Environmental Chemistry

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3. Earth & Planetary Sciences

• Geology: petrology, mineralogy, volcanology, tectonics

• Geophysics: seismology, geomagnetism, geodynamics

• Geochemistry: isotope geochemistry, cosmochemistry

• Meteorology & Atmospheric Science: climatology, weather dynamics

• Oceanography: physical, chemical, biological, geological

• Planetary Science: planetary geology, exoplanets, astrogeology

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4. Biology

• Molecular Biology: genomics, proteomics, epigenetics

• Cell Biology: cell signaling, membrane biology

• Microbiology: bacteriology, virology, mycology, parasitology

• Ecology: ecosystems, conservation biology, population biology

• Evolutionary Biology: phylogenetics, evolutionary genetics

• Organismal Biology: botany, zoology, anatomy, physiology

• Neuroscience: cognitive neuroscience, neurobiology, computational neuroscience

• Systems Biology & Synthetic Biology

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FORMAL SCIENCES

5. Mathematics

• Pure Mathematics: algebra, analysis, geometry, topology, number theory, logic

• Applied Mathematics: differential equations, numerical analysis, optimization

• Statistics & Probability

• Theoretical Computer Science: algorithms, complexity theory, automata, cryptography

• Mathematical Physics

• Discrete Mathematics

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6. Computer Science

(Though often classified under engineering + formal sciences)

• Core Theory: algorithms, computation theory, cryptography

• Artificial Intelligence: ML, NLP, computer vision, reinforcement learning

• Systems: operating systems, distributed systems, networks

• Software Engineering: programming languages, compilers, formal verification

• Data Science: data mining, big data, information retrieval

• Human-Computer Interaction

• Cybersecurity

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SOCIAL SCIENCES

7. Psychology

• Cognitive, clinical, developmental, social, neuropsychology, behavioral

8. Sociology

• Social theory, social networks, stratification, demography, economic sociology

9. Economics

• Microeconomics, macroeconomics, econometrics, behavioral economics, development economics, finance

10. Political Science

• Comparative politics, international relations, political theory, public policy, security studies

11. Anthropology

• Cultural anthropology, biological anthropology, archaeology, linguistic anthropology

12. Human Geography

• Urban studies, population geography, economic geography, GIScience

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HEALTH & LIFE SCIENCES

13. Medicine & Clinical Sciences

• Internal medicine, surgery, cardiology, oncology, neurology

• Genetics, immunology, pathology

• Epidemiology, public health

• Pharmacology

14. Veterinary Science

15. Nursing & Allied Health

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ENGINEERING & APPLIED SCIENCES

16. Engineering (General)

• Mechanical Engineering: thermofluids, robotics, acoustics

• Electrical Engineering: circuits, signal processing, power engineering

• Computer Engineering

• Civil Engineering: structural, geotechnical, transport, environmental

• Chemical Engineering: process engineering, biochemical engineering

• Materials Engineering

• Aerospace Engineering

• Nuclear Engineering

• Industrial & Systems Engineering

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17. Environmental & Sustainability Sciences

• Environmental science

• Climate science

• Conservation science

• Sustainable engineering

• Renewable energy systems

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INTERDISCIPLINARY / EMERGING SCIENCES

18. Data, Information, and Complexity Sciences

• Data science

• Complexity science

• Network science

• Information theory

19. Cognitive & Brain Sciences

• Cognitive science

• Computational neuroscience

• AI + neuroscience hybrids

20. Life-Environmental Interface

• Biogeochemistry

• Earth system science

• Astrobiology

21. Technology & Society

• Science and Technology Studies (STS)

• Ethics of AI

• Digital sociology

22. Space Sciences

• Space engineering

• Astrobiology

• Planetary science

• Deep-space communication

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HUMANITIES (often included in broad academic taxonomies)

23. Philosophy

• Logic, epistemology, ethics, metaphysics, philosophy of science

24. History

• World history, history of science, economic history

25. Linguistics

• Phonetics, syntax, semantics, historical linguistics, computational linguistics

26. Arts & Cultural Studies

• Literature, media studies, art history