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Update: I'm pleased to learn Yudkowsky seems to have suggested a similar agenda in a recent interview with Dwarkesh Patel (timestamp) as his greatest source of predictable hope about AI. It's a rather fragmented bit but the gist is: Perhaps people doing RLHF get a better grasp on what to aim for by studying where "niceness" comes from in humans. He's inspired by the idea that "consciousness is when the mask eats the shoggoth" and suggests, "maybe with the right bootstrapping you can let that happen on purpose".

I see a very important point here: Human intelligence isn't misaligned with evolution in a random direction, it is misaligned in the direction of maximizing positive qualia. Therefore, it seems very likely that consciousness played a causal role in the evolution of human moral alignment - and such causal role needs to be possible to study. 

Suggestion: Integrated search in LessWrong, EA Forum, Alignment Forum and perhaps Progress Forum posts.

  1. If Big Tech finds these kinds of salaries cost-effective to solve their problems, I would consider it a strong argument in favor of this project.
  2. I imagine Elon Musk could like this project given that he believes in small effective teams of geniuses.
  3. I'd say "polymaths" is a good label for people I'd expect to make progress like Yudkowsky, Bostrom, Hanson and von Neumann.
    1. Edit: This may be fame-selection (engineers don't often get credit, particularly in teams) or self-selection (interest in math+society).
  4. The Manhattan and Enigma projects seem like examples where this kind of strategy just worked out. Some consideration that come to mind:
    1. There could be selection effects.
    2. From what I can find, members of these teams weren't lured in by a lot of money. However, the salience of the AI threat in society is tiny, compared to that of WWII and large incentives could compensate that.
    3. I've read money can sometimes decrease intrinsic motivation, that drives exploration & inventions, however these findings are being rebutted by newer studies. Apart from that, my guess would be that getting those teams together is the key part and if large money can facilitate that, great.
  5. A wild idea that might help in case a similar phenomenon works in the sub-population of geniuses & which could make this project more appealing to donors: Limit a portion of these salaries, so that the recipients could only use them for socially beneficial uses.

I got access to Bing Chat. It seems:
- It only searches through archived versions of websites (it doesn't retrieve today's news articles, it accessed an older version of my Wikipedia user site)
- During archivation, it only downloads the content one can see without any engagement with the website (tested on Reddit "see spoiler" buttons which reveal new content in the code. It could retrieve info from posts that gained less attention but weren't hidden behind the spoiler button)
I. e. it's still in a box of sorts, unless it's much more intelligent than it pretends.

Edit: A recent ACX post argues text-predicting oracles might be safer, as their ability to form goals is super limited, but it provides 2 models how even they could be dangerous: By simulating an agent or via a human who decides to take bad advice like "run the paperclip maximizer code". Scott implies thinking it would spontaneously form goals is extreme, linking a post by Veedrac. The best argument there seems to be: It only has memory equivalent to 10 human seconds. I find this  convincing for the current models but it also seems limiting for the intelligence of these systems, so I'm afraid for future models, the incentives are aligned with reducing this safety valve.

Answer by Daniel_FriedrichJan 10, 202310

For me, the easiest to imagine model of how an AI takeover could look like has been depicted in Black Mirror: Shut Up and Dance (the episodes are fully independent stories). It's probably just meant to show scary things humans can do with current technology, but such schemes could be trivial for a superintelligence with future technology.

I'd love to see a deeper inquiry into which problems of EAs are most effectively reduced by which interventions. The suggestion there's a lack of "skilled therapists used to working with intelligent, introspective clients" is a significant novel consideration for me as an aspiring psychologist and this kind of hybrid research could  help me calibrate my intuitions.

When coming up with a similar project,* I thought the first step should be to conduct exploratory interviews with EAs that would reveal their hypotheses about the psychological factors that may go into one's decision to take AI safety seriously. My guess would be that ideological orientation would explain the most variance.

*which I most likely won't realize (98 %) 
Edit: My project has been accepted for the CHERI summer research program, so I'll keep you posted!

The core idea sounds very interesting: Increasing rationality likely has effects which can be generalized, therefore having a measure could help evaluate wider social outreach causes.

Defining intelligence could be an AI-complete problem, but I think the problem is complicated enough as a simple factor analysis (i. e. even without knowing what we're talking about :). I think estimating impact once we know the increase in any measure of rationality is the easier part of the problem - for ex. knowing how much promoting long-termist thinking increases support for AI regulation, we're only a few steps from getting the QALY. The harder part for people starting out in social outreach might be to estimate how much people they can get on board of thinking more long-termistically with their specific intervention.
So I think it might be very useful to put together a list of all attempts to calculate the impact of various social outreach strategies for anyone who's considering a new one to be able to find some reference points because the hardest estimates here also seem to be the most important (e. g. the probability Robert Wright would decrease oversuspicion between powers). My intuition tells me differences in attitudes are something intuition could predict quite well, so the wisdom of the crowd could work well here.
The best source I found when I tried to search whether someone tried to put  changing society into numbers recently is this article by The Sentience Institute.

Also, this post adds some evidence based intervention suggestions to your list.

What can an EA academic do to improve the incentives in the research side of academia? To help reward quality or even positive impact?