ML4Good runs intensive, fully-funded in-person bootcamps to train motivated people for careers in AI safety, covering both technical and governance tracks.
ML4Good runs intensive, fully-funded in-person bootcamps to train motivated people for careers in AI safety, covering both technical and governance tracks.
People– no linked people
Updated 04/03/26Funding Details
Updated 04/03/26- Annual Budget
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- Current Runway
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- Funding Goal
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- Funding Raised to Date
- $104,803
Org Details
Updated 04/03/26ML4Good was founded in 2022 as a project of EffiSciences (now the Centre pour la Securite de l'IA, CeSIA) in France. The first two bootcamps were held in France that year. The program expanded to Switzerland and Germany in 2023, and reached Brazil in 2024, marking its first non-European location. In 2024, co-founders Nia Gardner and Charbel-Raphael Segerie established ML4Good as an independent organization, incorporated in the UK as ML4Good Ltd (Companies House number 16065072, incorporated 6 November 2024). An official launch in early 2025 led to nine bootcamps across three continents, including the first in Asia, and saw the debut of governance and strategy bootcamp tracks. By early 2026, ML4Good had run 25 bootcamps in total and trained over 400 alumni, with a 98% participant recommendation rate. Spring 2026 programming includes bootcamps in Western Europe, Central Europe, Canada, and South Africa. Each cohort takes approximately 20 participants selected through a two-stage process (written application and a 15-minute interview). Participants complete 10-20 hours of preparatory work before the 8-day residential program. Nia Gardner serves as Executive Director, overseeing operations and strategic direction. Charbel-Raphael Segerie, who also serves as Executive Director of CeSIA, leads curriculum development. The organization runs with a lean team of 2 full-time staff supplemented by contractors including teaching assistants and instructors. ML4Good has previously operated under fiscal sponsors including Dandelion Labs (for UK bootcamps) and EA Germany (for German bootcamps). Funders include Coefficient Giving (formerly Open Philanthropy) and the Erasmus+ program.
Theory of Change
Updated 04/03/26ML4Good's theory of change centers on talent as the key bottleneck for AI safety progress. The organization believes that intensive, in-person, residential training is more cost-effective at producing committed AI safety contributors than other engagement formats such as online courses or hackathons. By selecting highly motivated participants from technical and governance backgrounds, running rigorous 8-day bootcamps, and fostering ongoing regional peer networks, ML4Good aims to accelerate career transitions into full-time AI safety roles. The causal chain is: selective in-person training of motivated individuals → career transitions to AI safety organizations → increased talent and capacity at safety-focused institutions → better AI safety outcomes and reduced catastrophic risk.
Grants Received
Updated 04/03/26Projects– no linked projects
Updated 04/03/26Discussion
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