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
- AIIM: whether its proposed evaluation and funding mechanisms are coherent, testable, and resistant to manipulation.
- Testing and evidence: whether experiments, preregistrations, metrics, and reported results support the claims being made.
- Governance: incentives, accountability, appeals, concentration of power, and transition toward DAO-based governance.
- Technical implementation: architecture, source code, blockchain components, security assumptions, and operational limitations.
- AI safety: assumptions behind the Symbiote initiative, human-in-the-loop mechanisms, prompt-injection risks, and failure modes.
- Nonprofit and financial transparency: whether public descriptions of legal control, spending, fundraising, and project status are sufficiently clear.
Useful source material
- AI Internet-Meritocracy (AIIM)
- Testing & Evidence
- Adversarial testing plan
- Current product status and limitations
- Transparency
- Key Contributors
- The Strongest Arguments Against AIIM
Questions reviewers may investigate
- Are the project’s central claims stated precisely enough to be falsifiable or empirically tested?
- Do the proposed evaluation mechanisms measure what they claim to measure?
- What incentives could cause gaming, Goodhart effects, collusion, or strategic self-presentation?
- Are the planned adversarial tests strong enough to reveal important failure modes?
- Which decisions should remain subject to independent human judgment?
- Are the project’s current limitations and development status disclosed clearly?
- Which technical or governance assumptions are most fragile?
- What evidence would materially increase or decrease confidence in AIIM?
- What risks are missing from the current documentation?
- Which claims should be weakened, strengthened, or tested differently?
Independence policy
Science DAO does not require a favorable conclusion. Reviewers retain editorial control over their work. We may point out factual errors or provide source material on request, but reviewers are not expected to adopt our wording or conclusions.
Substantive external reviews may be linked from Science DAO’s evidence pages regardless of whether they are supportive, mixed, or critical. Inclusion of a review does not imply endorsement of its conclusions.
Conflicts and compensation
Reviewers should disclose any material relationship with Science DAO, Victor Porton’s Foundation, project contributors, or funders. If compensation is ever offered for a review, that fact should be disclosed publicly and payment must not depend on the review being favorable.
Publish independently
The preferred outcome is a review published somewhere Science DAO does not control. Suitable venues can include an academic or personal research website, a journal or repository, an AI-safety or open-science forum, or another independently administered publication platform.
Submit your independent review
Published a substantive independent assessment? Submit it here. Supportive, mixed, and critical reviews are welcome under the same policy. Pseudonymous reviews are accepted; reviewers who want their credentials privately verified may provide them confidentially.
Published independent reviews and criticism
No substantive external reviews are listed here yet. When they are available, this section will link to them with the author, affiliation where applicable, publication venue, date, and a clear note that Science DAO does not control the reviewer’s conclusions.
Support Independent Science
Our flagship product, AI Internet-Meritocracy, is an app (in the stage of open beta-testing) designed to allocate donated funds to researchers and open-source developers using AI-assisted evaluation of documented contributions. Payments depend on available funds and eligibility requirements.
Help fund the proposed five-month public test of AIIM’s allocation model with distribution of $1000 to real salary recipients. Support the next testing milestone.
Supporting independent science is not only a matter of fairness to researchers whose expertise and work are often underfunded. It is also essential for addressing systemic failures in scientific publishing that delay discoveries and leave important results unnoticed. In science and software, even one missing component can prevent an entire system from working.
Help valuable research and open-source infrastructure move forward. Please make a donation to support independent scientists and free software developers.
Independent review
Researchers and AI-safety reviewers: We invite independent technical criticism of Science DAO, AIIM, and related AI-safety work, including critical conclusions. Please examine assumptions, human-in-the-loop mechanisms, prompt-injection risks, governance, and failure modes. Use the independent-review packet →
Disclaimer
Experimental-system notice: AI Internet-Meritocracy is an experimental funding system. Its AI-generated evaluations are heuristic judgments based on available public or connected-account evidence; they are not validated measurements of a person’s causal economic or scientific impact. Payment transactions are already recorded on-chain and can be verified on the blockchain. The current beta initiates payments off-chain through Node.js and uses custodial and administrative components. Decentralized governance and non-custodial wallets remain under development; on-chain payment records are already available. Evaluations may contain factual errors or biases and should be interpreted together with audit logs, appeals, human oversight, and published test results.