I see LessWrong is currently obsessed with AI Alignment. I spoke with some others on the unofficial LessWrong discord, and agreed that LessWrong is becoming more and more specialised, thus scaring off any newcomers who aren’t interested in AI.
That aside. I’m genuinely curious. Do any of the posts on LessWrong make any difference in the general psychosphere of AI alignment? Does anyone who has actual control on the direction of AI and LLM’s follow LessWrong? Does Sam Altman or anyone at OpenAI engage with LessWrongers?
Not being condescending here. I’m just asking this since there’s two (2) important things to note: (1) Since LessWrong has very little focus on anything other than AI at the moment, are these efforts meaningful? (2) What are some basic beginner resources someone can use to understand the flood of complex AI posts currently on the front page? (Maybe I’m being ignorant, but I haven’t found a sequence dedicated to AI...yet.)
Good ideas propagate. Nobody from an AGI org has to read a LessWrong post for any good ideas generated here to reach them. Although they definitely do read Alignment Forum posts and often LessWrong posts. Check out the Alignment Forum FAQ to understand its relationship to LW.
LessWrong and AF also provide something that journals do not: public discussion that includes both expert and outside contributions. This is lacking in other academic forums. After spending a long time in cognitive neuroscience, it looked to me like intellectual progress was severaly hampered by people communicating rarely, and in cliques. Labs each had their own viewpoint that was pretty biased and limited, and cross-lab communication was rare, but extremely valuable when it happened. So I think the existence of a common forum is extremely valuable for making rapid progress.
There are specialized filters for LW by tag. If you’re not interested in AI, you can turn that topic down as far as you want.
Ah okay, thanks. I wasn’t aware of the Alignment Forum, I’ll check it out.
I don’t disagree that informal forums are valuable. I take Jacque Ellul’s belief in Technological Society that science firms held by monopolies tend to have their growth stunted for exactly the reasons you pointed out.
I think it’s more that places like LessWrong are susceptible to having the narrative around them warped (referencing the article about Scott Alexander). Though this is slightly off-topic now.
Lastly, I am interested in AI; I’m just feeling around for what the best way to get into it is. So thanks.
Yup, sorry.
Sometimes. E.g. the Waluigi effect post was in March, and I’ve seen that mentioned by random LLM users. CNN had Conor Leahy on as an AI expert about the same time, and news coverage about Bing chat sometimes glossed Evan Hubinger’s post about it.
Yeah. And I don’t just mean on Twitter, I mean it’s kinda hard not to talk to e.g. Jan Leike when he works there.
Yeah, this is pretty tricky, because fields accumulate things you have to know to be current in them. For “what’s going on with AI in general” there are certainly good posts on diverse topics here, but nothing as systematic and in-depth as a textbook. I’d say just look for generically good resources to learn about AI, learning theory, neural networks. Some people have reading lists (e.g. MIRI, Vanessa Kosoy, John Wentworth), many of which are quite long and specialized—obviously how deep down the rabbit hole you go depends on what you want to learn. For alignment topics various people have made syllabi (This one, I think primarily based on Richard Ngo’s, is convenient to recommend despite occasional disagreements)
Thanks for that.
Out of curiosity then, do people use the articles here as part of bigger articles on other academic journals? Is this place sort of the ‘launching pad’ for ideas and raw data?
You can check out the recommended sequences at the top of the AI Alignment Forum (which is a subset of LessWrong).
To add onto other people’s answers:
People have disagreements over what the key ideas about AI/alignment even are.
People with different basic-intuitions notoriously remain unconvinced by each other’s arguments, analogies, and even (the significance of) experiments. This has not been solved yet.
Alignment researchers usually spend most time on their preferred vein of research, rather than trying to convince others.
To (try to) fix this, the community’s added concepts like “inferential distance” and “cruxes” to our vocabulary. These should be be discussed and used explicitly.
One researcher has some shortform notes (here and here) on how hard it is to communicate about AI alignment. I myself wrote some longer, more emotionally-charged notes on why we’d expect this.
But there’s hope yet! This chart format makes it easier to communicate beliefs on key AI questions. And better ideas can always be lurking around the corner...
Do you think these disagreements stem from a sort of egoistic desire to be known as the ‘owner’ of that concept? Or to be a forerunner for that vein of research should it become popular?
Or is it a genuinely good faith disagreement on the future of AI and what the best approach is? (Perhaps these questions are outlined in the articles you’ve linked, which I’ll begin reading now. Though I do think it’s still useful to perhaps include a summary here too.) Thanks for your help.
Seems to usually be good faith. People can still be biased of course (and they can’t all be right on the same questions, with the current disagreements), but it really is down to differing intuitions, which background-knowledge posts have been read by which people, etc.
The impact of the LessWrong community as a whole on the field of AI and especially on the field of AI safety seems to be fairly strong, even if difficult to estimate in a precise fashion.
For example, a lot of papers related to interpretability of AI models are publicized and discussed here, so I would expect that interpretability researchers do often read those discussions.
One of the most prominent examples of LessWrong impact is Simulator Theory which has been initially published on LessWrong (Simulators). Simulator Theory is a great deconfusion framework in regard to what LLMs are and are not, helping people to avoid mistakingly interpreting properties of particular inference runs as properties of LLMs themselves, and has recently been featured in Nature as a part of joint publication, M.Shanahan and the authors of Simulator Theory, “Role play with large language models”, Nov 8, 2023, open access.
But I also think that people ending up working on AI existential safety in major AI labs are often influenced by the AI safety discourse on LessWrong in their career choice and initial orientation, although I don’t know if it’s possible to track that well.