Social exclusion in science splits people into “castes”, making science stuck by excluding some parts of the science from public consideration. Social exclusion in science is “Houthis”, that block development of all the science in its most thin place – independent scientists – like Houthis block oil transfer in the thinnest strait.
- While it is written much about Social Inclusion importance of racial and gender inclusion in science, the topic of science degrees as discrimination amplifier is mostly omitted.
- Many scientists are monopolists, often a monopolist without money. Monopolist who does not have money or does not want to pay for publication is a problem for the entire world. Sometimes, a big problem.
- Because the current system of science doesn’t give money to every scientist, but many important discoveries remain unpaid, social inclusion is not only important for every scientist, but for the science at large. Just one scientist not included may mean a big hindrance for the entire world science.
- Science is a social system built on especially bad or missing social inclusion: All people are split into three degrees: Bachelor, Masters, and PhD plus no degree. If somebody didn’t receive a PhD for any reason, he is just excluded. This makes the system of science especially bad.
- We need money to poor monopolists, especially ones holding no PhD or no degree at all. That’s the reason why I am developing AIIM (AI Internet-Meritocracy) software: It gives money to scientists and free software developers fairly, not dependently on degrees. This is a way to fix the entire broken system of science.
👉 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.