On “How”, my colleague Matt @Matt Beard has some good ideas here: https://80000hours.substack.com/p/how-to-get-into-ai-safety-in-3-months
Yes, it can take time, but one can say more:
Not everyone has taken a long time, and among my observations, this is usually because they have demonstrated exceptional bias for action. E.g. Julian Moncarz , Neav Topaz (maybe it’s no coincidence that they are both at Kairos!)
I think on priors one should expect pivots to take time, in any domain. The kinds of things one has to do could be different, e.g. getting an MBA to break into management, or a PhD to get into particle physics. Actually AI safety is much, much less gate-kept since there is no hard experience, degree, location requirements
AI safety looks as if you need to take a lot of time to pivot compared to e.g. pivoting to some mature industry, but this under-counts the actual pivot time for the latter: Mature industries have huge companies with a lot of slack in them which can take on promising but relatively unproductive pivoters and put them through years of on-the-job upskilling. (but obviously having the security of a full-time job is much preferred to fellowships or career development grants).
IANAGM so I can’t speak to why they are funding or not funding the specific bets they are/are not funding.
But, speaking abstractly, grantmaking in AI safety is conceptually complicated: Do you take a wide range of bets on unproven theories of change and new grantees, or do you narrowly fund only bets which you have high confidence on? How do you balance between the two?
My intuition is that AI safety puts 1-2 cycles of funding into first-time bets, and quickly moves on to the next set of first-time bets while only continuing to fund orgs and people who used their early money well (and had something to show for it, even negative results). One could argue that funders should be biased towards funding orgs/people for 3 or even 5 cycles before pulling the plug, but this is ultimately a hyperparameter in a quantitative model. It’s not obvious to me that the current settings of such hyperparameters are the wrong ones.
With more funding and increased diversity of funders, I absolutely expect more funding philosophies and models in the ecosystem, increasing the kinds of bets being taken.