What Is Effective Altruism?
Effective Altruism (EA) is a philosophy and social movement that aims to use evidence and reason to do the most good. Associated thinkers such as William MacAskill and Peter Singer emphasize:
- Cause prioritization
- Cost-effectiveness
- Measurable impact
- Long-term global benefit
EA-aligned organizations like 80,000 Hours and GiveWell focus on optimizing where resources flow to maximize expected value.
The central question in EA is:
Where can each marginal dollar produce the greatest positive impact? 📊
What Is AI Internet-Meritocracy?
AI Internet-Meritocracy (AIIM) is a Web-based system that:
- Accepts cryptocurrency donations
- Uses AI to evaluate participants
- Distributes funds based on assessed merit
- Removes traditional gatekeeping (degrees, grant writing, institutional affiliation)
- Supports science marketing to address publication inefficiencies
It proposes AI as a neutral allocator of funding rather than relying solely on human committees.
Alignment with Effective Altruism Principles
Impact Maximization
EA prioritizes interventions with the highest expected value.
AIIM attempts to:
- Reduce overhead from grant bureaucracy
- Allocate funds continuously rather than episodically
- Redirect resources toward under-recognized contributors
If successful, this could increase funding efficiency per donated dollar ⚙️
Cause-Neutral Evaluation
Effective Altruism emphasizes impartiality between causes.
AIIM’s model:
- Evaluates individuals rather than institutions
- Removes credential-based bias
- Potentially enables discovery of overlooked talent
This parallels EA’s effort to avoid status-quo favoritism.
Reduction of Structural Bias
Traditional research funding often depends on:
- Institutional prestige
- Network effects
- Publication visibility
AIIM attempts to:
- Bypass publication bottlenecks
- Reward scientific marketing
- Recognize non-traditional contributors
This is conceptually compatible with EA’s critique of inefficient systems.
Scalability Through Automation
EA supports scalable interventions.
AI-driven funding:
- Scales algorithmically
- Operates globally
- Reduces marginal administrative costs
Automation can theoretically improve long-term sustainability 🌍
Other Points with Effective Altruism
Evaluation Transparency
EA organizations such as Open Philanthropy emphasize detailed reasoning behind grants.
AIIM needs:
- Transparent evaluation criteria (implemented by releasing all the code open-source)
- Auditability (all AI reasonings are stored and publicly shown)
- Robust safeguards against manipulation (banning of misbehaving users by public voting backed by KYC to avoid Sybil attacks)
Epistemic Risk
EA is highly sensitive to:
- Model uncertainty
- Overconfidence in untested mechanisms
- Adversarial dynamics
EA culture strongly prefers empirical validation before large-scale deployment 🔍
Measurement of Outcomes
EA prioritizes measurable outcomes.
AIIM must answer:
- How is “merit” quantified? (it is quantified by the share in world GDP and is displayed in the leaderboard and Audit Logs).
- How are downstream impacts measured?
- How are long-term benefits tracked?
Without clear metrics, EA alignment remains partial rather than complete.
Strategic Positioning Within EA
AIIM most closely fits within:
- Meta-science optimization
- Institutional reform efforts
- Funding infrastructure innovation
- Decentralized science (DeSci)
It could be framed as a cause-neutral funding infrastructure upgrade, rather than as a specific cause area.
This positioning aligns it with:
- Improving how science is funded
- Increasing global talent utilization
- Reducing epistemic waste
Comparative Summary
| EA Principle | AIIM Compatibility | Notes |
|---|---|---|
| Cost-effectiveness | Potentially high | Depends on admin overhead & AI reliability |
| Impartiality | Strong alignment | Removes credential bias |
| Evidence-based | Conditional | Requires transparent validation |
| Scalability | High | AI allows global scaling |
| Long-termism | High | Due to use of AI |
Conclusion
AI Internet-Meritocracy fits within the Effective Altruism framework primarily as a meta-level funding reform mechanism rather than a direct cause intervention.
It aligns with EA in:
- Seeking maximal impact per dollar
- Reducing bias and gatekeeping
- Increasing scalability
However, full integration into the EA ecosystem would require:
- Strong empirical validation
- Governance safeguards
- Clear impact metrics
In EA terms, AIIM represents a high-variance, potentially high-upside institutional innovation. ⚖️
Whether it becomes EA-endorsed depends less on its philosophical alignment and more on demonstrated, measurable effectiveness.
👉 Please, support AI Internet Meritocracy
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.