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 AIIS (AI Internet-Socialism) 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 AIIS / AI Internet-Socialism
AI Internet-Socialism, as proposed on Science-DAO.org, is an economic formation and funding mechanism for science and software that:
- Leverages DAOs, blockchain, cryptocurrency, and algorithmic decision-making to distribute funds fairly.
- Seeks to eliminate gatekeeping in peer review or grant awarding, replacing them with transparent, performance- and dependency-aware metrics.
- Rewards not only the final scientific outputs but also the dependencies: software libraries, earlier results, components that many future works build upon. This creates incentives for foundational work which is often under-funded.
In other words, AIIS is not merely another prize: it is a system designed to automatically recognize, reward, and fund scientific work in a continuous, decentralized, and fair way.
How AIIS Automates Prizes and Grants
One of the key innovations of AIIS is that it doesn’t just replace prizes (which tend to recognize retrospective excellence) but also grants (which fund work ahead of impact). Here’s how:
| Traditional system | AIIS alternative |
|---|---|
| Fixed-cycle grants, decided by panels, criterias opaque, long timelines | Automated allocation based on measurable contributions, algorithmic / DAO voting or transparent metrics, immediate or regular flows of support |
| Prizes awarded for big breakthroughs, often years after the fact, with prestige but limited coverage | Continuous recognition via donation thresholds, dependency funding, algorithmic rewards, broader and more distributed acknowledgment |
For example, Science-DAO’s “AI Internet Socialism” project aims to collect donations and distribute them in ways that reward dependencies, authors of software and science that many others cite or build on, and marketers of science that help discovery be visible.
Under AIIS, something becomes “peer reviewed” or “prize-worthy” when it crosses certain objective or semi-objective thresholds (e.g. impact via citations or usage) rather than merely being selected by panels. That makes it closer to a grant + prize hybrid: you get rewarded for what you do, not just for what you propose or someone judges you should get.
Implementation: How AIIS Works in Practice
The app asks AI, how big portion of the world GDP a given person (as determined by his/her connected accounts) is worth, and after this the app distributes donated crypto tokens proportionally to the portion.
Advantages & Challenges
Advantages:
- Fairness & inclusion: AIIS reduces bias toward elite institutions and “prestigious names” by making measurable contributions count.
- Speed: less bureaucracy, fewer rounds of peer review delays, faster allocation of funding.
- Sustainability: because rewards continuously accrue as work is built upon, foundational work is more likely to be funded.
- Transparency: donors, scientists, the public can see where funds go and why.
Challenges:
- Defining fair metrics: what counts as “dependency”, citation, usage, promotion?
- Avoiding manipulation: gaming of donation thresholds, fake citations, self-promotion.
- Technical implementation: reliable blockchain, fully on-chain app with a non-custodial wallet, secure smart contracts, identity (ORCID etc.), linking off-chain usage data.
- Cultural inertia: traditional grant and prize bodies may resist change; institutions depend on prestige from certain awards.
AIIS vs Traditional Prizes & Grants: A Comparative View
Traditional prizes/grants systems have strengths: prestige, institutional recognition, peer legitimacy, sometimes large sums. But they have limitations:
- Small number of winners, high overhead, opaque decision-making.
- Grants often require proposals, budgets, reporting overhead; prizes often reward what has already been done, not earlier stages.
AIIS seeks to combine the best of both:
- Retrospective recognition like a prize, but in an automated, inclusive way.
- Forward-looking funding like grants, but without the same overhead, and with metrics that reward ongoing contribution.
Related Science-DAO Projects
For further reading, see:
- Science-DAO’s “Grants Science” project — which lays out how donations can be used to improve the grants system and reward dependencies.
- The main Science-DAO site — explains the DAO model, mission, and other projects.
- Yhe page “AI Internet-Socialism” itself (on SCIENCE-DAO) — the theoretical underpinnings of AIIS.
Conclusion
AIIS (AI Internet-Socialism) is more than an idea: it’s a feasible, practical system to automate scientific prizes and replace or augment grants, making funding and recognition more continuous, fairer, more transparent. It turns science funding into a dynamic ecosystem, rather than a gated, slow funnel.
If implemented well, AIIS could transform how scientific rewards are distributed — benefiting early-career scientists, under-resourced regions, foundational and dependency work, and science as a whole.