ML4Good Impact Assessment

Published on October 15, 2026 10:43 AM GMT Intro At ML4Good, we run annual follow-up surveys to keep track of what people are doing and to measure our impact.  In late 2025, we sent our alumni survey to 340 alumni, 223 of whom responded. Of those, 135 are now doing something in AI safety, adding up to about 98 full-time equivalents (FTE).  After estimating outcomes for the people who didn't reply, we think that around 186 of the 340 (~55%) are doing something in AI safety, or ~147 FTE. Based on what alumni told us about ML4Good's counterfactual impact, we estimate that ~77 FTE were counterfactual - these people would not be spending their time on AI safety absent ML4Good.  Like others in the field, we find counterfactual impact hard to measure, so we're less confident in this figure than in the others. We also have over 200 recent alumni from 2026 bootcamps that we haven't yet followed up with.  We’re reporting all of our costs for the evaluation period openly, and we make an estimate of how cost-effectively we get people into AI Safety work. We calculated a “fully-loaded” cost of £5.4k per FTE, or £9.3k per counterfactual FTE produced. We’re publishing our data and letting other field-builders know our best guess at how many people are working in AI safety as a result of ML4Good, and at what cost. We’ll also give some caveats and uncertainties about our results, and a bottom line estimate of our impact, given all considerations. Summary of activities As of October 2026, there will have been 31 ML4Good bootcamps across 12 countries since August 2022. Over this period, we’ve trained around 600 alumni.  We initially focused on technical bootcamps. After becoming an organisation in early 2025, we scaled up our operations to run 9 bootcamps last year, and developed a new Governance & Strategy curriculum, before scaling to 12 a year in 2026.  We've operated in the highlighted countries. What this impact assessment covers Our impact assessment covers 17 bootcamps (340 participants), including 13 from Europe (inc. UK), 3 in Latin America, and 1 in Asia.  We haven’t yet run our latest round of alumni surveys, therefore only our bootcamps up until the end of September 2025 were included in this analysis. All except one were technical bootcamps. It also doesn’t include two bootcamps run in 2023 with SafeAI Lausanne in Switzerland, which used slightly differing surveying strategies. Community building as an indirect result of ML4Good has also caused many more people to engage with or contribute to AI safety. However, we don’t have concrete numbers on this and chose not to include this in our evaluation. Summary of results Our bootcamps have been successful at achieving our objectives of getting more people working in AI safety.  An estimated 186 alumni are now working in AI Safety in some capacity (~55% of all participants), or the equivalent of 147 FTE. Many of these participants consider our bootcamp the main reason they're currently working in AI safety. Based on self-reported counterfactuals, we estimate that around 77 of those 147 FTE would not have happened without ML4Good. Several alumni-founded communities have been developed as a direct result of ML4Good. We receive strongly positive feedback from all of our bootcamps, and 98% of participants recommend ML4Good.[1] There are many caveats and uncertainties, especially around how we attempt to measure counterfactual impact, so we want to be transparent about this. What we try to do ML4Good plays a role fairly high up the funnel in the AI safety talent pipeline. Our focus is on providing a transition point for people thinking seriously about a move into AI Safety. We're relatively selective - in 2026, we accepted around 15% of applicants. We usually target people who have engaged with entry level content, such as BlueDot, online technical safety courses, or reading the relevant literature, e.g. LessWrong/EA forum/80,000 Hours content, but who have usually not yet committed to a concrete path[2].  After ML4Good, we encourage and support alumni to take future steps to contribute to AI safety. Some alumni start targeted research programmes like MATS, Pivotal, SPAR, ERA, and Talos. Others enter direct roles in AI Safety, conduct independent work, or found new organisations. Some find ways to integrate AI safety into their current work, which can be promising, particularly for our alumni working in policy and law.  Over 8 days, we create a motivating in-person environment where participants are guided by inspiring teachers and surrounded by other participants with similar goals. We aim to empower attendees to think ambitiously about how to have an impact, to act with high agency, and to find whereabouts in AI safety they are best suited to contribute. They spend the final days of the bootcamp making and starting to implement concrete plans. While most of our bootcamps run in Europe, we have also succeeded in identifying and supporting talented people across five