Non-EA interests include chess and TikTok (@benthamite). Formerly @ CEA, METR + a couple now-acquired startups.
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I don't disagree, it's more that this feels a bit like privileging the hypothesis? I think the modal reason I've heard from people who did capabilities work and now regret it is something like "I knew I was misaligned with leadership but I thought leaving would be even worse."Â
If, for some reason, Anthropic asked me how to prevent people from regretting working for them, I would focus much more on "have a thing for people to do once they realize their colleague is corrupt" instead of "have a more nuanced way of telling if their colleague is corrupt."
Thanks! I only know a handful of people in this category, but for what it's worth, it again feels like people who were predisposed to thinking that working on pretraining would be okay rather than them being "corrupted."Â
E.g., I recently talked to someone who told me that their main takeaway from a safety fellowship was realizing that they didn't fit in because they actually weren't worried about existential risk in the same way that the other attendees were.
People seem surprised and bewildered when AI folks defect away from AI safety towards capabilities. People trust that as AI companies grow, those gaining power and money from shares will not be adversely influenced by that power and money.
fwiw I don't actually know many examples of this, and the ones I hear cited often seem uncompelling to me. E.g.:
(Counterexamples appreciated, though!)
And credit to the AI skeptics that they seem to mostly have updated in light of the new evidence (or at least claimed that they never actually believed in long timelines, which is maybe less noble, but ends up in the same place).
Yeah I agree that if you only have one bit of detail that you can store, then saying it is "hard" rather than "easy" is probably the correct bit. However I would suggest that for something as important as your career you should investigate in substantially more detail. If you do so I expect you will come up with a range of needed skills/attributes for these jobs, some of which you might find easy, others of which you might find hard.Â
Many people said they wanted to work for METR. I made what I thought was a good offer: take one of the benchmarks we give AIs; if you get a good score then I guarantee that I will fly you out for an interview, even if you have no work history, have no money to pay for the trip, or any other barrier one might have to employment.
Exactly zero people took me up on this.[1]
How is it possible for there to be sky-high rejection rates yet also zero people sending me applications?
I think the answer is that raw rejection rates aren't a very useful metric. After all, an 80% rejection rate means that the AI safety jobs are 1/10th as selective as Walmart!
I would suggest ignoring raw rejection rates in favor of just looking at the criteria for the jobs you want. Particularly for something like s-risks the criteria are going to be unusual and specific, meaning that even generically qualified people will often have to dedicate substantial time to skilling up, but if you're able to do so, then your odds are pretty good.[2]Â
I wouldn't be surprised to learn that some people tried this, failed, and then were too embarrassed about failing to tell me. But, to the best of my recollection, literally zero people have told me that they even attempted this task.
I say this even with the knowledge that you are 19. I don't want to pretend that the deck isn't stacked against younger people - it totally is - but we employ some 19 year olds, as do other AI safety orgs. If a 19 year old had sent me a good solution to that METR challenge, for example, I would have been happy to hire them.
I think the AI ethics crowd is the subject of attacks (though arguably this is because they tried to seek power and influence).