Can I interest you in working in AI policy if technical alignment doesn’t work out? You’ll want to visit DC and ask a ton of people there if you seem like a good fit (or ask them who can evaluate people). Or you can apply for advising on 80k or use the Lesswrong intercom feature in the bottom-right corner.
I know that technical alignment is quant and AI policy is not, and accounting is quant, but my current understanding is that >50% of accountants can be extremely helpful in AI policy whereas <50% of accountants can do original technical alignment research.
More ML background is a huge boost in both areas, not just alignment. People good at making original discoveries in alignment will be able to reskill back to alignment research during crunch time, but right now is already crunch time for AI policy.
Hi @trevor! I appreciate the ideas you shared and yeah I agree that most accountants are probably better of helping in the AI policy route!
But to point out, I’m doing some AI policy work/ help back home in the Philippines as part of the newly formed Responsible AI committee so I think I am not falling short from this end.
I have looked at the AI safety problem deeply and my personal assessment is that it is difficult to create workable policies that can route to the best outcomes because we (as a society) lack the understanding of the mechanisms that make the transformer tech work. My vision of AI policies that can work will somehow capture a deep level of lab work being done by AI companies like learning rates standardization or number of epochs allowed that is associated hopefully with a robust and practical alignment theory, something that we do not have for the moment. Because of this view, I chosed to help in the pursuit of solving the alignment problem instead. The theoretical angle I am pursuing is significant enough to push me to learn machine learning and so far I was able to create RLFC and ATL through this process but yeah maybe an alternative scenario for me is doing 100% AI policy work—open for it if it will produce better results in the grand scheme of things.
(Also, regarding the Lesswrong intercom feature in the bottom-right corner: I did have many discussions with the LW team, something I wished was available months ago but yeah I think one needs a certain level of karma to get access to this feature.)
Can I interest you in working in AI policy if technical alignment doesn’t work out? You’ll want to visit DC and ask a ton of people there if you seem like a good fit (or ask them who can evaluate people). Or you can apply for advising on 80k or use the Lesswrong intercom feature in the bottom-right corner.
I know that technical alignment is quant and AI policy is not, and accounting is quant, but my current understanding is that >50% of accountants can be extremely helpful in AI policy whereas <50% of accountants can do original technical alignment research.
More ML background is a huge boost in both areas, not just alignment. People good at making original discoveries in alignment will be able to reskill back to alignment research during crunch time, but right now is already crunch time for AI policy.
Hi @trevor! I appreciate the ideas you shared and yeah I agree that most accountants are probably better of helping in the AI policy route!
But to point out, I’m doing some AI policy work/ help back home in the Philippines as part of the newly formed Responsible AI committee so I think I am not falling short from this end.
I have looked at the AI safety problem deeply and my personal assessment is that it is difficult to create workable policies that can route to the best outcomes because we (as a society) lack the understanding of the mechanisms that make the transformer tech work. My vision of AI policies that can work will somehow capture a deep level of lab work being done by AI companies like learning rates standardization or number of epochs allowed that is associated hopefully with a robust and practical alignment theory, something that we do not have for the moment. Because of this view, I chosed to help in the pursuit of solving the alignment problem instead. The theoretical angle I am pursuing is significant enough to push me to learn machine learning and so far I was able to create RLFC and ATL through this process but yeah maybe an alternative scenario for me is doing 100% AI policy work—open for it if it will produce better results in the grand scheme of things.
(Also, regarding the Lesswrong intercom feature in the bottom-right corner: I did have many discussions with the LW team, something I wished was available months ago but yeah I think one needs a certain level of karma to get access to this feature.)