Gitcoin and Giveth distribute money unfairly and inefficiently because of inherent problems with quadratic funding, while SciWard uses a different allocation model intended to reduce reliance on donor popularity and proposal writing. Its comparative fairness and efficiency require empirical testing.
SciWard (SciWard) is an experimental funding app that uses AI-assisted allocation. This article compares its design with Gitcoin, Giveth, and Manifund.
SciWard 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 Turn AIIM’s Beta into Evidence
AIIM remains experimental. The next proposed milestone is a five-month public adversarial test, with $1,000 planned for distribution to eligible funding recipients. Donations support the work required to run and evaluate that test.
Fund the public test → Test proposal → Independent review →
AI-generated evaluations can contain factual errors or biases; decentralized governance and non-custodial components remain under development. Public testing, auditability, and external criticism remain part of the project.
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