Press & Media Kit: Science DAO and AI Internet-Meritocracy (AIIM)

Press & media kit · Updated 29 September 2026

This page is a compact source for journalists, editors, podcasters, researchers, conference organizers, and other media professionals covering Science DAO, AI Internet-Meritocracy (AIIM), or related projects. For claims that may change over time, follow the linked source pages rather than treating this press kit as the final record.

30-word description

Science DAO develops experimental infrastructure for funding science and open-source software. Its flagship project, AI Internet-Meritocracy (AIIM), uses AI-assisted evaluation of documented contributions to help allocate available donated funds.

100-word description

Science DAO is an online project developing experimental tools for transparent funding and coordination in science and open-source software. Its flagship project, AI Internet-Meritocracy (AIIM), is an operational beta that uses AI-assisted assessments of documented research and software contributions as inputs to funding allocation. The current beta still uses custodial and administrative components; decentralized governance and non-custodial infrastructure remain under development. Payment transactions are recorded on-chain, while current payment initiation remains off-chain. Science DAO is preparing public testing and explicitly invites independent external criticism. AIIM is experimental and has not yet been independently validated as an effective or fair funding system.

Current status

As of 29 September 2026:

AIIM: operational beta. Current product status →
Validation: independent validation is still pending. Testing & Evidence →
Governance: quorum-based voting is implemented; an administrator may intervene only as an extraordinary fallback. Details →
Payments: payment transactions are recorded on-chain; current payment initiation is still off-chain through a custodial Node.js workflow. Transparency →
Decentralization: Science DAO is not currently operating as a DAO. Migration toward ICP-based decentralized governance and non-custodial infrastructure is planned. Current governance disclosure →
Next proposed evidence milestone: a five-month public adversarial test. The published plan describes a $1,300 funding target: $1,000 for recipient payments and $300 for AI, hosting, and related operating costs. Adversarial testing plan →

What is established — and what is not

Established/documented: the beta application exists; source code is publicly inspectable; payment records are recorded on-chain; the project documents current custodial and administrative limitations; the testing plan and independent-review policy are public.

Not established: AIIM has not been independently validated as an accurate measure of scientific or economic impact, as a fair allocation system, as resistant to strategic manipulation, or as superior to traditional funding mechanisms. AI-generated scores are heuristic estimates and can be wrong or biased.

For a claim-by-claim view, use AIIM in 10 Citable Claims and the AIIM Claim–Evidence Graph.

About Science DAO

Science DAO is the umbrella project. Its work includes AIIM, science-funding experiments, open-source infrastructure, and related projects. It is not currently a separate incorporated charity and is not currently operating as a DAO. Donations for the project are legally received and controlled by Victor Porton’s Foundation. For governance, legal, financial, and conflict-of-interest disclosures, see Transparency and About Us.

Founder / principal contributor

Victor Porton is CEO of World Science DAO, a mathematician and software developer, and the primary developer behind AIIM. Public verification links, research profiles, publications, software repositories, and source documents are collected on the Key Contributors page.

Short bio for media use: Victor Porton is a mathematician and software developer building Science DAO and AI Internet-Meritocracy (AIIM), an experimental AI-assisted funding system for science and open-source software. His public work includes mathematics research, software development, and open-source projects.

Key project links

AIIM overview — what the system is and how it is intended to work.
AIIM beta app — public application.
Source code — public GitHub repository.
Product Status — current implementation and limitations.
Testing & Evidence — evidence hub and validation priorities.
Adversarial Testing — proposed public red-team test.
Independent Review — reviewer packet and policy.
Transparency — governance, finances, technical limitations, and conflicts of interest.
10 Citable Claims — stable, source-linked statements.
Claim–Evidence Graph — claims connected to supporting evidence, limitations, and next tests.

Media assets

The following existing site assets can help reporters understand the project. For reuse permissions, attribution requirements, or high-resolution originals, please contact us.

Frequently asked questions for journalists

Is Science DAO currently a DAO?

No. The project previously used DAO infrastructure, but the current public disclosure says it is not presently operating as a DAO. Migration toward ICP-based decentralized governance is planned. See Transparency.

Is AIIM already proven to work?

No. AIIM is an operational beta, but independent validation remains pending. The project is explicitly treating adversarial testing, reproducibility, stability, and external review as open evidence questions.

Does AIIM measure the true impact of scientific work?

No validated causal-impact measurement has been established. AIIM’s AI-generated scores are heuristic estimates used in its experimental allocation logic. See AIIM-C3.

Is AIIM fully on-chain or non-custodial?

No. Payment transactions are recorded on-chain, but current payment initiation and wallet management still use off-chain custodial components. Non-custodial infrastructure remains under development.

Does a researcher need a PhD?

A science degree is not a general prerequisite for consideration. Other requirements can still apply, including documentation, authorship, identity, supported sources, eligibility rules, and available funds.

Does Science DAO invite critical coverage?

Yes. The project explicitly invites independent analysis, including critical, mixed, or negative conclusions. See the Independent Review page.

Media contact

For interviews, factual checks before publication, requests for source documents, asset permissions, or other media inquiries, use the Science DAO Contact page →.

When possible, please identify the publication, topic, deadline, and which Science DAO or AIIM claim you are checking. Questions that challenge the project’s claims are welcome.

Editorial note

This press kit is maintained by the project itself and should be treated as a primary source about how Science DAO describes its own work, not as independent validation. Journalists and researchers are encouraged to consult the linked source code, records, external sources, and independent reviews.

👉 Help fund the next public test of AIIM.

Help Test a New Way to Fund Science

AI Internet-Meritocracy (AIIM) is an operational beta designed to allocate available donations to researchers and open-source developers using AI-assisted evaluation of documented contributions. Payment transactions are already recorded on-chain.

The next major evidence milestone is a proposed five-month public adversarial test of the allocation model, with $1,000 distributed to eligible funding recipients. Donations help pay for the development, infrastructure, reviewer and participant recruitment, outreach, and operating work needed to reach and evaluate that milestone.

You do not need to assume AIIM is already proven to support the project. Your donation helps turn the proposal into evidence: what works, what fails, and what should change.

Support the next testing milestone → Read the test proposal →

Independent review

Researchers and technical reviewers: independent criticism is welcome, including negative conclusions. Review AIIM’s assumptions, governance, failure modes, and testing plan →

Research status: AIIM remains experimental. AI-generated evaluations can contain factual errors or biases, and decentralized governance and non-custodial components remain under development. That uncertainty is why public testing, auditability, and external criticism are central to the project.