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:
- No need to manually create a description of each grant and review them manually
- No project rejections
- No need for verifying conforming to the rules for each grant.
- It takes into account even smallest projects of a user (that if they are many, may form a majority of the user’s income).
- No long pause before paying. We can pay every week or even more often.
- No users not donating due to being confused over the topic (like: ordered semicategory actions) of a grant.
- No dependencies on the “commercial business” of somebody advertising their grants in different media, but equal funding opportunities for everybody: rich and poor.
👉 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.
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