peterslattery(Peter Slattery)
Templates and videos for doing annual and daily reviews
Glad it is useful! Did you see the comments in the google sheet? Just hover over the cells. Overall is your measure of how the day was overall as a hedonic experience while life satisfaction is satisfaction with life as a whole on that particular day.
I have updated this and made some explainer videos—please see here (will add to post when I get a chance)
A spreadsheet/template for doing an annual review
A ranked link of LessWrong tags/concepts
Hi, thanks for writing this. Sorry to hear that things are hard. I would really like if you can help me to understand these points:
A few days later, I saw this post. And it reminded me of everything that bothers me about the EA community. Habryka covered the object level problems pretty well, but I need to communicate something a little more… delicate.
What bothers you about the EA community specifically? At times, I am not sure if you are talking about the EA community, the AIS technical research community, the rationalist community or the Berkeley AIS community? I think of them all as being very different.
I want to address the central flaw of Akash+Olivia+Thomas’s argument in the Buying Time post, which is that actually, people can improve at things.I feel I don’t properly understand what you think of this argument and why you think it is flawed.
The AI Safety community has four main work groups, Strategy, Governance, Technical and Movement Building
AI Safety Movement Builders should help the community to optimise three factors: contributors, contributions and coordination
A template for doing annual reviews
Thanks for writing this up Simeon, it’s given me a lot to think about. The table is particularly helpful.
Thanks for doing/sharing this Vael. I was excited to see it!
I am currently bringing something of a behaviour change/marketing mindset to thinking about AI Safety movement building and therefore feel that testing how well different messages and materials work for audiences is very important. Not sure if it will actually be as useful as I currently think though.
With that in mind, I’d like to know:
was this as helpful for you/others as expected?
are you planning related testing to do next?
Two ideas I wonder if it would be valuable to first test predictions among communicators for which materials will work best before then doing the test. This could make the value of the new information more salient by showing if/where our intuitions are wrong
I wonder about the value of trying to build an informal panel/mailing list of ML researchers who we can contact/pay to do various things like surveys/interviews. Also to potentially review AI Safety arguments/post from a more skeptical perspective so we can more reliably find any likely flaws in the logic or rhetoric.
Would welcome any thoughts or work on either if you have the time and inclination.
Yeah, I agree with Kaj here. We do need to avoid the risk of using misleading or dishonest communication. However it also seems fine and important to optimise relevant communication variables (e.g., tone, topic, timing, concision, relevance etc) to maximise positive impact.
Thanks! Quick responses:
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.
Good to know. When discussing some recent ideas I had for surveys, several people told me that their survey results underperformed their expectations, so I was curious if you would say the same thing.
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.
Thanks for explaining. I realise that the point of that part of my comment was unclear, sorry. I think that using these sorts of surveys to test if best practice contrasts with current practice could make the findings clearer and spur improvement/innovation if needed.
For instance, doing something like this: “We curated the 10 most popular public communication paper from AI Safety organisations and collected predictions from X public AI Safety communicators about which of thse materials would be most effective at persuading existing ML researchers to care about AI Safety. We tested these materials with a random sample of X ML researchers and [supported/challenged existing beliefs/practices]… etc.”
I am interested to hear what you think of the idea of testing using these sorts of surveys to test if best practice contrasts with current practice, but ok if you don’t have time to explain! I imagine that it does add some extra complexity and challenge to the research process, so may not be worth it.
I hope you can do the larger study eventually. If you do, I would also like to see how sharing readings compares against sharing podcasts or videos etc. Maybe some modes of communication perform better on average etc.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!
Thanks, that’s helpful. Yeah, I think that the panel idea is one for the future. My thinking is something like this: Understanding why and how AI Safety related materials (e.g., arguments, research agendas, recruitment type messages etc) influence ML researchers is going to become increasingly important to a growing number of AI Safety community actors (e.g., researchers, organisations, recruiters and movement builders).
Whenever an audience becomes important to some social/business actor (e.g., government/academics/companies), this usually creates sufficient demand to justify setting up a panel/database to service those actors. Assuming the same trend, it may be important/useful to create a panel of ML researchers that AI Safety actors can access.
Does that seem right?
I mention the above in part because I think that you are one of the people who might be best-placed to set something like this up if it seemed like a good idea. Also, because I think that there is a reasonable chance that I would use a service like this within the next two years and end up referring several other people (e.g., those producing choosing educational materials for relevant AI Safety courses) to use it.
Is there a plan to review and revise this to keep it up to date? Or is there something similar that I can look at which is more updated? I have this saved as something to revisit, but I worry not that it could be out of date and inaccurate given the speed of progress.
Also, just as feedback (which probably doesn’t warrant any changes being made unless similar feedback provided), I will flag that it would be good to be able to see posts that this is mentioned in ranked by recency rather than total karma.
- Part 3: A Proposed Approach for AI Safety Movement Building: Projects, Professions, Skills, and Ideas for the Future [long post][bounty for feedback] by 22 Mar 2023 0:54 UTC; 21 points) (EA Forum;
- A Proposed Approach for AI Safety Movement Building: Projects, Professions, Skills, and Ideas for the Future [long post][bounty for feedback] by 22 Mar 2023 1:11 UTC; 14 points) (
A Proposed Approach for AI Safety Movement Building: Projects, Professions, Skills, and Ideas for the Future [long post][bounty for feedback]
I just want to say that this seems like a great idea, thanks for proposing it.
I have a mild preference for you to either i) do this in collaboration with a project like Stampy or ii) plan how to integrate what you do into with another existing project in the future.
In general, I think that we should i) minimise the number of education providers and ii) maximise uniformity of language and understanding within the AI existential risk educational ecosystem.
Please help me sense-check my assumptions about the needs of the AI Safety community and related career plans
Anonymous submission:
I only skimmed your post so I very likely missed a lot of critical info. That said, since you seem very interested in feedback, here are some claims that are pushing back against the value of doing AI Safety field building at all. I hope this is somehow helpful.- Empirically, the net effects of spreading MIRI ideas seems to be squarely negative, both from the point of view of MIRI itself (increasing AI development, pointing people towards AGI), and from other points of views.
- The view of AI safety as expounded by MIRI, Nick Bostrom, etc is essentially an unsolvable problem. To put it in words that they would object it, they believe at some point humanity is going to invent a Godlike machine and this Godlike machine will then shape the future of the universe as it sees fit; perhaps according to some intensely myopic goal like maximizing paperclips. To prevent this from happening, we need to somehow make sure that AI does what we want it to do by formally specifying what we really want in math terms.
The reason MIRI have given up on making progress on this and don’t see any way forward is because this is an unsolvable situation.
Eliezer sometimes talks about how the textbook from the future would have simple alignment techniques that work easily but he is simply imagining things. He has no idea what these techniques might be, and simply assumes there must be a solution to the problem as he sees it.
- There are many possibilities of how AI might develop that don’t involve MIRI-like situations. The MIRI view essentially ignores economic and social considerations of how AI will be developed. They believe that the economic advantages of a super AI will lead to it eventually happening, but have never examined this belief critically, or even looked at the economic literature on this very big, very publicly important topic that many economists have worked on.
- A lot of abuse and bad behavior has been justified or swept under the rug in the name of ‘We must protect unaligned AGI from destroying the cosmic endowment’. This will probably keep happening for the foreseeable future.
- People going into this field don’t develop great option value.
Thanks! Link sharing should be fixed now. Let me know if not!