Funding the Future of AI Safety: The Alignment Fellowship Proposal
Coverage of lessw-blog
A new proposal on LessWrong explores a crowd-sourced, unconditional grant model to support researchers working on AI alignment and existential risk.
In a recent post on LessWrong, a community member has put forward a proposal for an "Alignment Fellowship," a funding initiative designed to support individuals working on AI alignment and existential risk reduction. The post addresses a persistent bottleneck in the scientific and technical research communities: the friction caused by traditional funding mechanisms.
The Context: The Cost of Bureaucracy
In the current landscape of academic and non-profit research, securing funding is often a job in itself. Researchers frequently spend a significant portion of their time writing grant applications, tailoring their proposals to fit specific criteria, and managing reporting requirements. This administrative burden does more than just consume time; it can warp the trajectory of research. To secure funds, researchers may pivot toward safer, more incremental projects that appeal to grant committees, rather than pursuing high-risk, high-reward work that is critical for nascent fields like AI safety.
The proposed Alignment Fellowship draws inspiration from the Thiel Fellowship, which famously offers unconditional grants to young entrepreneurs and researchers. The underlying philosophy is that by removing financial constraints and administrative oversight, "nerds and creatives" can maximize their productivity and focus entirely on the problems they are trying to solve.
The Proposal: Crowd-Sourced Patronage
The LessWrong post outlines a specific vision: funding approximately three individuals for a duration of two years. The goal is to identify people who are passionate about mitigating existential risks but are currently held back by financial constraints. However, the most distinct aspect of this proposal is not the money itself, but the selection mechanism.
Rather than relying on a centralized committee or a board of directors, the author proposes a crowd-sourced selection process involving the Alignment Forum community. Under this model, members of the forum would nominate candidates and vote on recipients. This approach leverages the collective intelligence of the specific community most knowledgeable about the technical nuances of AI alignment, potentially surfacing talent that traditional institutions might overlook.
The author is currently soliciting feedback on the viability of this model, seeking input on potential candidates, the appropriate size of the grants, and the mechanics of the voting system. It represents an experiment in decentralized research funding, aiming to optimize how resources are allocated in a field where speed and focus are paramount.
Why This Matters
For observers of the AI safety landscape, this proposal highlights a shift toward more agile, community-driven infrastructure. As the urgency of AI alignment research grows, the community is actively seeking ways to bypass traditional institutional sluggishness. If successful, this model could serve as a blueprint for how niche, high-impact technical fields support their talent pool outside of the university or corporate lab systems.
We recommend reading the full post to understand the specific mechanics proposed and the community discussion surrounding the efficacy of unconditional grants.
Read the full post on LessWrong
Key Takeaways
- The proposal advocates for unconditional grants to remove administrative burdens and boost researcher productivity.
- The model draws inspiration from the Thiel Fellowship, targeting high-potential individuals constrained by finances.
- Selection of grant recipients would be crowd-sourced via the Alignment Forum community rather than a centralized committee.
- The initiative aims to fund approximately three researchers for two-year terms to focus on existential risk.
- The author is actively seeking community feedback to refine the selection mechanics and grant structure.