Small update: Two authors gave me permission to publish their transcripts non-anonymously!
Interview with Michael L. Littman (https://docs.google.com/document/d/1GoSIdQjYh21J1lFAiSREBNpRZjhAR2j1oI3vuTzIgrI/edit?usp=sharing)
Interview with David Duvenaud (https://docs.google.com/document/d/1lulnRCwMBkwD9fUL_QgyHM4mzy0al33L2s7eq_dpEP8/edit?usp=sharing)
Two authors gave me permission to publish their transcripts non-anonymously! Thus:
Interview with Michael L. Littman (https://docs.google.com/document/d/1GoSIdQjYh21J1lFAiSREBNpRZjhAR2j1oI3vuTzIgrI/edit?usp=sharing)
Interview with David Duvenaud (https://docs.google.com/document/d/1lulnRCwMBkwD9fUL_QgyHM4mzy0al33L2s7eq_dpEP8/edit?usp=sharing)
Anonymous comment sent to me, with a request to be posted here:
“The main lede in this post is that pushing the materials that feel most natural for community members can be counterproductive, and that getting people on your side requires considering their goals and tastes. (This is not a community norm in rationalist-land, but the norm really doesn’t comport well elsewhere.)”
was this as helpful for you/others as expected?
I think these results, and the rest of the results from the larger survey that this content is a part of, have been interesting and useful to people, including Collin and I. I’m not sure what I expected beforehand in terms of helpfulness, especially since there’s a question “helpful with respect to /what/”, and I expect we may have different “what”s here.
are you planning related testing to do next?
Good chance of it! There’s some question about funding, and what kind of new design would be worth funding, but we’re thinking it through.
I wonder if it would be valuable to first test predictions among communicators
Yeah, I think this is currently mostly done informally—when Collin and I were choosing materials, we had a big list, and were choosing based on shared intuitions that EAs / ML researchers / fieldbuilders have, in addition to applying constraints like “shortness”. Our full original plan was also much longer and included testing more readings—this was a pilot survey. Relatedly, I don’t think these results are very surprising to people (which I think you’re alluding to in this comment) -- somewhat surprising, but we have a fair amount of information about researcher preferences already.
I do think that if we were optimizing for “value of new information to the EA community” this survey would have looked different.
I wonder about the value of trying to build an informal panel/mailing list of ML researchers
Instead of contacting a random subset of people who had papers accepted at ML conferences? I think it sort of depends on one’s goals here, but could be good. A few thoughts: I think this may already exist informally, I think this becomes more important as there’s more people doing surveys and not coordinating with each other, and this doesn’t feel like a major need from my perspective / goals but might be more of a bottleneck for yours!
My guess is that people were aware (my name was all over the survey this was a part of, and people were emailing with me). I think it was also easily inferred that the writers of the survey (Collin and I) supported AI safety work far before the participants reached the part of the survey with my talk. My guess is that my having written this talk didn’t change the results much, though I’m not sure which way you expect the confound to go? If we’re worried about them being biased towards me because they didn’t want to offend me (the person who had not yet paid them), participants generally seemed pretty happy to be critical in the qualitative notes. More to the point, I think the qualitative notes for my talk seemed pretty content focused and didn’t seem unusual compared to the other talks when I skimmed through them, though would be interested to know if I’m wrong there.
Yeah, we were focusing on shorter essays for this pilot survey (and I think Richard’s revised essay came out a little late in the development of this survey? Can’t recall) but I’m especially interested in “The alignment problem from a deep learning perspective”, since it was created for an ML audience.
Whoa, at least one of the respondents let me know that they’d chatted about it at NeurIPS—did multiple people chat with you about it? (This pilot survey wasn’t sent out to that many people, so curious how people were talking about it.)
Edited: talking via DM
Thanks! (credit also to Collin :))
Agreed that status / perceived in-field expertise seems pretty important here, especially as seen through the qualitative results (though the Gates talk did surprisingly well, given not an AI researcher, but the content reflects that). We probably won’t have [energy / time / money] + [we have limited access to researchers] to test something like this, but I think we can hold “status is important” as something pretty true given these results, Hobbhann’s (https://forum.effectivealtruism.org/posts/kFufCHAmu7cwigH4B/lessons-learned-from-talking-to-greater-than-100-academics), and a ton of anecdotal evidence from a number of different sources.
(I also think the Sam Bowman article is a great article to recommend, and in fact recommend that first a lot of the time.)
(Just a comment on some of the above, not all)
Agreed and thanks for pointing out here that each of these resources has different content, not just presentation, in addition to being aimed at different audiences. This seems important and not highlighted in the post.
We then get into what we want to do about that, where one of the major tricky things is the ongoing debate of “how much researchers need to be thinking in the frame of xrisk to make useful progress in alignment”, which seems like a pretty important crux, and another is “what do ML researchers think after consuming different kinds of content”, where Thomas has some hypotheses in the paragraph “I’d guess...” but we don’t actually have data on this and I can think of alternate hypotheses, which also seems quite cruxy.
These results were actually embedded in a larger survey, and were grouped in sections, so I don’t think it came off as particularly long within the survey. (I also assume most people watched the video at faster than 1x.) People also seemed to like this talk, so I’d guess that they watched it as or more thoroughly than they did everything else. We don’t have analytics regretfully. (I also forgot to add that we told people to skip the Q&A, so we had them watch the first 48m.)
I told him I only wanted the bare-bones of interactions, and he’s been much better to work with!
I see there’s an associated talk now! https://www.youtube.com/watch?v=EIhE84kH2QI
Re: “Targeted Outreach to Experienced Researchers”
Please apply to work with the aforementioned AISFB Hub! I am actively trying to hire for people who I think would be good fits for this type of role, and offer mentorship / funding / access to and models of the space. Note that you’ll need to have AI safety knowledge (for example, I want you to have read / have a plan for reading all of the main readings in the AGISF Technical Curriculum) and high generalist competence, as two of the most important qualifications.
I think most people will not be a good fit for this role (there’s more complicated status hierarchies and culture within experienced researchers than are visible at first glance), and like Akash I caution against unilateral action here. I’m psyched about meeting people who are good fits, however, and urge you to apply to work with me if you think that could be you!
Does Anyuan(安远) have a website? I haven’t heard of them and am curious. (I’ve heard of Concordia Consulting https://concordia-consulting.com/ and Tianxia https://www.tian-xia.com/.)