Are you aware of Effective Altruism’s AI governance branch? I didn’t look into it in detail myself, but there are definitely dozens of people already working on outreach strategies that they believe to be the most effective. FHI, CSER, AI-FAR, GovAI, and undoubtedly more groups have projects ongoing for outreach, political intervention, etc. with regards to AI Safety. If you want to spend your marginal time on stuff like this, contact them.
It does appear true that the lesswrong/rationalist community is less engaged with this strategy than might be wise, but I’m curious if those organisations would say if people currently working on technical alignment research should switch to governance/activism, and what their opinion is on activism. 80,000 hours places AI technical research above AI governance in their career impact stack, though personal fit plays a major part.
I was not aware. Are these outreach strategies towards the general public with the aim of getting uninvolved people to support AI alignment efforts, or are they toward DeepMind employees to get them to stop working so hard on AGI? I know there are lots of people raising awareness in general, but that’s not really the goal of the strategy that I’ve outlined.
Much of the outreach efforts are towards governments, and some to AI labs, not to the general public.
I think that because of the way crisis governance often works, if you’re the designated expert in a position to provide options to a government when something’s clearly going wrong, you can get buy in for very drastic actions (see e.g. COVID lockdowns). So the plan is partly to become the designated experts.
I can imagine (not sure if this is true) that even though an ‘all of the above’ strategy like you suggest seems like on paper it would be the most likely to produce success, you’d get less buy in from government decision-makers and be less trusted by them in a real emergency if you’d previously being causing trouble with grassroots advocacy. So maybe that’s why it’s not been explored much.
This post by David Manheim does a good job of explaining how to think about governance interventions, depending on different possibilities for how hard alignment turns out to be: https://www.lesswrong.com/posts/xxMYFKLqiBJZRNoPj/
In case of interest, I’ve been conducting AI strategy research with CSER’s AI-FAR group, amongst others a project to survey historical cases of (unilaterally decided; coordinated; or externally imposed) technological restraint/delay, and their lessons for AGI strategy (in terms of differential technological development, or ‘containment’).
(see longlist of candidate case studies, including a [subjective] assessment of the strength of restraint, and the transferability to the AGI case) https://airtable.com/shrVHVYqGnmAyEGsz This is still in-progress work, but will be developed into a paper / post within the next month or so. --- One avenue that I’ve recently gotten interested in, though I’ve only just gotten to read about it and have large uncertainties about it, is the phenomenon of ‘hardware lotteries’ in the historical development of machine learning—see https://arxiv.org/abs/2009.06489 -- to describe cases were the development of particular types of domain specialized compute hardware make it more costly [especially for e.g. academic researchers, probably less so for private labs] to pursue particular new research directions.
It strikes me that 80000 hours puts you just about when the prediction markets are predicting AGI to be available, i.e., a bit late. I wonder if EA folks still think government roles are the best way to go?
Are you aware of Effective Altruism’s AI governance branch? I didn’t look into it in detail myself, but there are definitely dozens of people already working on outreach strategies that they believe to be the most effective. FHI, CSER, AI-FAR, GovAI, and undoubtedly more groups have projects ongoing for outreach, political intervention, etc. with regards to AI Safety. If you want to spend your marginal time on stuff like this, contact them.
It does appear true that the lesswrong/rationalist community is less engaged with this strategy than might be wise, but I’m curious if those organisations would say if people currently working on technical alignment research should switch to governance/activism, and what their opinion is on activism. 80,000 hours places AI technical research above AI governance in their career impact stack, though personal fit plays a major part.
I was not aware. Are these outreach strategies towards the general public with the aim of getting uninvolved people to support AI alignment efforts, or are they toward DeepMind employees to get them to stop working so hard on AGI? I know there are lots of people raising awareness in general, but that’s not really the goal of the strategy that I’ve outlined.
Much of the outreach efforts are towards governments, and some to AI labs, not to the general public.
I think that because of the way crisis governance often works, if you’re the designated expert in a position to provide options to a government when something’s clearly going wrong, you can get buy in for very drastic actions (see e.g. COVID lockdowns). So the plan is partly to become the designated experts.
I can imagine (not sure if this is true) that even though an ‘all of the above’ strategy like you suggest seems like on paper it would be the most likely to produce success, you’d get less buy in from government decision-makers and be less trusted by them in a real emergency if you’d previously being causing trouble with grassroots advocacy. So maybe that’s why it’s not been explored much.
This post by David Manheim does a good job of explaining how to think about governance interventions, depending on different possibilities for how hard alignment turns out to be: https://www.lesswrong.com/posts/xxMYFKLqiBJZRNoPj/
In case of interest, I’ve been conducting AI strategy research with CSER’s AI-FAR group, amongst others a project to survey historical cases of (unilaterally decided; coordinated; or externally imposed) technological restraint/delay, and their lessons for AGI strategy (in terms of differential technological development, or ‘containment’).
(see longlist of candidate case studies, including a [subjective] assessment of the strength of restraint, and the transferability to the AGI case)
https://airtable.com/shrVHVYqGnmAyEGsz
This is still in-progress work, but will be developed into a paper / post within the next month or so.
---
One avenue that I’ve recently gotten interested in, though I’ve only just gotten to read about it and have large uncertainties about it, is the phenomenon of ‘hardware lotteries’ in the historical development of machine learning—see https://arxiv.org/abs/2009.06489 -- to describe cases were the development of particular types of domain specialized compute hardware make it more costly [especially for e.g. academic researchers, probably less so for private labs] to pursue particular new research directions.
These are really interesting, thanks for sharing!
It strikes me that 80000 hours puts you just about when the prediction markets are predicting AGI to be available, i.e., a bit late. I wonder if EA folks still think government roles are the best way to go?