Executive summary: This interview presents ML4Good as an organization running intensive AI safety bootcamps, arguing that in-person bootcamps are the most cost-effective way they have found to motivate and prepare people—especially increasingly industry professionals rather than only academics—to work full-time in AI safety, with expansion now including a new governance track.
Key points:
Carolina explains that ML4Good began in 2022 after experimenting with multiple engagement formats and found bootcamps to be the most cost-effective method for long-term commitment to AI safety.
The target audience has shifted from mainly master’s and PhD students toward a mix that increasingly includes industry professionals, driven by shorter AI timelines and placement considerations.
ML4Good currently runs a two-step application process—written application plus a 15-minute interview—to better assess genuine motivation amid widespread LLM-generated applications.
Each bootcamp typically receives 130–150 applications, interviews about 40 candidates, and selects around 20 participants.
Technical bootcamps focus on general AI safety with substantial coding, drawing inspiration from Arena while adding governance exposure to help participants choose paths.
ML4Good is developing a governance bootcamp, with roughly 40% shared curriculum with the technical track, aimed at people interested in AI governance rather than traditional government roles.
The average cost per bootcamp is about €30,000, mainly driven by staff costs, with ML4Good running around 12 bootcamps per year supported by two full-time staff.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Executive summary: This interview presents ML4Good as an organization running intensive AI safety bootcamps, arguing that in-person bootcamps are the most cost-effective way they have found to motivate and prepare people—especially increasingly industry professionals rather than only academics—to work full-time in AI safety, with expansion now including a new governance track.
Key points:
Carolina explains that ML4Good began in 2022 after experimenting with multiple engagement formats and found bootcamps to be the most cost-effective method for long-term commitment to AI safety.
The target audience has shifted from mainly master’s and PhD students toward a mix that increasingly includes industry professionals, driven by shorter AI timelines and placement considerations.
ML4Good currently runs a two-step application process—written application plus a 15-minute interview—to better assess genuine motivation amid widespread LLM-generated applications.
Each bootcamp typically receives 130–150 applications, interviews about 40 candidates, and selects around 20 participants.
Technical bootcamps focus on general AI safety with substantial coding, drawing inspiration from Arena while adding governance exposure to help participants choose paths.
ML4Good is developing a governance bootcamp, with roughly 40% shared curriculum with the technical track, aimed at people interested in AI governance rather than traditional government roles.
The average cost per bootcamp is about €30,000, mainly driven by staff costs, with ML4Good running around 12 bootcamps per year supported by two full-time staff.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.