I think this post and Yudkowski's Twitter thread that started it are probably harmful to the cause of AI safety.
OpenAI is one of the top AI labs worldwide, and the difference between their cooperation and antagonism to the AI safety community means a lot for the overall project. Elon Musk might be one of the top private funders of AI research, so his cooperation is also important.
I think that both this post and the Twitter thread reduce the likelihood of cooperation without accomplishing enough in return. I think that the potential to do harm to potential ... (read more)
Thanks for the recommendation. I spent about an hour looking for contact info, but was only able to find 5 public addresses of ex-OpenAI employees involved in the recent exodus. I emailed them all, and provided an anonymous Google Form as well. I'll provide an update if I do hear back from anyone.
Unfortunately we may be unlikely to get a statement from a departed safety researcher beyond mine (https://forum.effectivealtruism.org/posts/fmDFytmxwX9qBgcaX/why-aren-t-you-freaking-out-about-openai-at-what-point-would?commentId=WrWycenCHFgs8cak4), at least currently.
It seems like the game would better approximate the game of mutually assured destruction if the two sides had unaligned aims somehow, and destroying the page could impede "their" ability to get in "our" way.Maybe the site that gets more new registrations on Petrov day has the right to demand that the loser advertise something of their choice for 1 month after Petrov day. Preferably, make the competition something that will be close to 50/50 beforehand.The two communities could try to negotiate an outcome acceptable to everyone or nuke the other to try to avoid having to trust them or do what they want.
Here's one possible way to distinguish the two: Under the optimizer's curse + judgement stickiness scenario retrospective evaluation should usually take a step towards the truth, though it could be a very small one if judgements are very sticky! Under motivated reasoning, retrospective evaluation should take a step towards the "desired truth" (or some combination of truth an desired truth, if the organisation wants both).
I like this post. Some ideas inspired by it:
If "bias" is pervasive among EA organisations, the most direct implication of this seems to me to be that we shouldn't take judgements published by EA organisations at face value. That is, if we want to know what is true we should apply some kind of adjustment to their published judgements.
It might also be possible to reduce bias in EA organisations, but that depends on other propositions like how effective debiasing strategies actually are.
A question that arises is "what sort of adjustment should be applied?". T... (read more)