(Post 2/N with some rough notes on AI governance field-building strategy. Posting here for ease of future reference, and in case anyone else thinking about similar stuff finds this helpful.)
Misc things it seems useful to do/find out
To inform talent development activities: talk with relevant people who have skilled up. How did they do it? What could be replicated via talent pipeline infrastructure? Generally talk through their experience.
Kinds of people to prioritise: those who are doing exceptionally well; those who have grown quite recently (might have better memory of what they did)
To inform talent search activities: talk with relevant people—especially senior folks—about what got them involved. This could feed into earlier stage talent pipeline activities
Case studies of important AI governance ideas (e.g. model evals, importance of infosec) and/or pipeline wins. How did they come about? What could be replicated?
How much excess demand is there for fellowship programs? Look into the strength of applications over time. This would inform how much value there is in scaling fellowships.
Figure out whether there is a mentorship bottleneck.
More concretely: would it be overall better if some of the more established AI governance folk spent a few more hours per month on mentorship?
Thing to do: very short survey asking established AI governance people how many hours per month they spend on mentorship.
Benefits of mentorship:
For the mentee: fairly light touch involvement can go a long way towards bringing them up to speed and giving them encouragement.
For the mentor: learn about fit for mentorship/management. Can be helpful for making object-level progress on work.
These benefits are often illegible and delayed in time, so a priori likely to be undersupplied.
If there’s a mentorship bottleneck, it might be important to solve ~now. The number of AI governance jobs is likely going to rise dramatically over the coming years—so having more thoughtful, risk-conscious people who are better placed to land those roles is more urgent than you might think if only considering having enough people by the acute risk period.
If there is a mentorship bottleneck how might one actually go about solving that? Obvious idea is to nudge potential mentors to consider:
Asking GovAI, who have been collecting expressions of interest for RAs, whether there’s anyone who might be a good fit as your mentee
Posting on the forum or otherwise broadcasting what kind of thing a potential mentee could do that might make you excited about mentoring them (e.g. write a review of report X, or write a memo on topic Y), and that (e.g.) if they do that they should send it to you, and you’ll at least take a 30 minute call with them
Mentoring someone on a summer program (e.g. GovAI Fellowship, ERIs, SERI MAGS, HAIST/MAIA programs, AI Safety Camp, …)
(Post 2/N with some rough notes on AI governance field-building strategy. Posting here for ease of future reference, and in case anyone else thinking about similar stuff finds this helpful.)
Misc things it seems useful to do/find out
To inform talent development activities: talk with relevant people who have skilled up. How did they do it? What could be replicated via talent pipeline infrastructure? Generally talk through their experience.
Kinds of people to prioritise: those who are doing exceptionally well; those who have grown quite recently (might have better memory of what they did)
To inform talent search activities: talk with relevant people—especially senior folks—about what got them involved. This could feed into earlier stage talent pipeline activities
Case studies of important AI governance ideas (e.g. model evals, importance of infosec) and/or pipeline wins. How did they come about? What could be replicated?
How much excess demand is there for fellowship programs? Look into the strength of applications over time. This would inform how much value there is in scaling fellowships.
Figure out whether there is a mentorship bottleneck.
More concretely: would it be overall better if some of the more established AI governance folk spent a few more hours per month on mentorship?
Thing to do: very short survey asking established AI governance people how many hours per month they spend on mentorship.
Benefits of mentorship:
For the mentee: fairly light touch involvement can go a long way towards bringing them up to speed and giving them encouragement.
For the mentor: learn about fit for mentorship/management. Can be helpful for making object-level progress on work.
These benefits are often illegible and delayed in time, so a priori likely to be undersupplied.
If there’s a mentorship bottleneck, it might be important to solve ~now. The number of AI governance jobs is likely going to rise dramatically over the coming years—so having more thoughtful, risk-conscious people who are better placed to land those roles is more urgent than you might think if only considering having enough people by the acute risk period.
If there is a mentorship bottleneck how might one actually go about solving that? Obvious idea is to nudge potential mentors to consider:
Asking GovAI, who have been collecting expressions of interest for RAs, whether there’s anyone who might be a good fit as your mentee
Posting on the forum or otherwise broadcasting what kind of thing a potential mentee could do that might make you excited about mentoring them (e.g. write a review of report X, or write a memo on topic Y), and that (e.g.) if they do that they should send it to you, and you’ll at least take a 30 minute call with them
Mentoring someone on a summer program (e.g. GovAI Fellowship, ERIs, SERI MAGS, HAIST/MAIA programs, AI Safety Camp, …)