“Possibly produce useful alignment work” is a really low bar, such that the answer is ~100%. Lots of things are possible. I’m going to instead answer “for what fraction of people would I think that the Long-Term Future Fund should fund them on the current margin”.
If you imagine that the people are motivated to work on AI safety, get good mentorship, and are working full-time, then I think on my views most people who could get into an ML PhD in any university would qualify, and a similar number of other people as well (e.g. strong coders who are less good at the random stuff that academia wants). Primarily this is because I think that the mentors have useful ideas that could progress faster with “normal science” work (rather than requiring “paradigm-defining” work).
In practice, there is not that much mentorship to go around, and so the mentors end up spending time with the strongest people from the previous category, and so the weakest people end up not having mentorship and so aren’t worth funding on the current margin.
I’d hope that this changes in the next few years, with the field transitioning from “you can do ‘normal science’ if you are frequently talking to one of the people who have paradigms in their head” to “the paradigms are understandable from the online written material; one can do ‘normal science’ within a paradigm autonomously”.
Hey Rohin, thanks a lot, that’s genuinely super helpful. Drawing analogies to “normal science” seems both reasonable and like it clears the picture up a lot.
“Possibly produce useful alignment work” is a really low bar, such that the answer is ~100%. Lots of things are possible. I’m going to instead answer “for what fraction of people would I think that the Long-Term Future Fund should fund them on the current margin”.
If you imagine that the people are motivated to work on AI safety, get good mentorship, and are working full-time, then I think on my views most people who could get into an ML PhD in any university would qualify, and a similar number of other people as well (e.g. strong coders who are less good at the random stuff that academia wants). Primarily this is because I think that the mentors have useful ideas that could progress faster with “normal science” work (rather than requiring “paradigm-defining” work).
In practice, there is not that much mentorship to go around, and so the mentors end up spending time with the strongest people from the previous category, and so the weakest people end up not having mentorship and so aren’t worth funding on the current margin.
I’d hope that this changes in the next few years, with the field transitioning from “you can do ‘normal science’ if you are frequently talking to one of the people who have paradigms in their head” to “the paradigms are understandable from the online written material; one can do ‘normal science’ within a paradigm autonomously”.
Hey Rohin, thanks a lot, that’s genuinely super helpful. Drawing analogies to “normal science” seems both reasonable and like it clears the picture up a lot.