It would be very interesting to conduct a poll between the users of LW. I expect that it would show that this site is quite biased towards more negative outcomes than the average ML researcher in this study.
Also, it would be interesting to see how it correlates with karma, I expect a positive correlation between karma score and pessimism
It was about 50%
https://www.lesswrong.com/posts/KxRauM9bv97aWnbJb/results-prediction-thread-about-how-different-factors-affect
It looks like most voters have low carma. Biggest exception is https://www.lesswrong.com/users/daniel-kokotajlo
and his estimates are 80-90% of doom:( But he thinks that it can be reduced significantly with a vast ($1 trillion) funding.
Others with high karma are https://www.lesswrong.com/users/quintin-pope and https://www.lesswrong.com/users/tailcalled with 0-10% and 50-60%
Does the data note whether the shift is among new machine learning researchers? Among those who have a p(Doom) > 5%, I wonder how many would come to that conclusion without having read lesswrong or the associated rationalist fiction.
Thanks for the link! I ended up looking through the data and there wasn't any clear correlation between amount of time spent in research area and p(Doom).
I ran a few averages by both time spent in research area and region of undergraduate study here: https://docs.google.com/spreadsheets/d/1Kp0cWKJt7tmRtlXbPdpirQRwILO29xqAVcpmy30C9HQ/edit#gid=583622504
For the most part, groups don't differ very much, although as might be expected, more North Americans have a high p(Doom) conditional on HLMI than other regions.
The LessWrong Review runs every year to select the posts that have most stood the test of time. This post is not yet eligible for review, but will be at the end of 2024. The top fifty or so posts are featured prominently on the site throughout the year.
Hopefully, the review is better than karma at judging enduring value. If we have accurate prediction markets on the review results, maybe we can have better incentives on LessWrong today. Will this post make the top fifty?
Katja Grace, 8 March 2023
In our survey last year, we asked publishing machine learning researchers how they would divide probability over the future impacts of high-level machine intelligence between five buckets ranging from ‘extremely good (e.g. rapid growth in human flourishing)’ to ‘extremely bad (e.g. human extinction).1 The median respondent put 5% on the worst bucket. But what does the whole distribution look like? Here is every person’s answer, lined up in order of probability on that worst bucket:
And here’s basically that again from the 2016 survey (though it looks like sorted slightly differently when optimism was equal), so you can see how things have changed:
The most notable change to me is the new big black bar of doom at the end: people who think extremely bad outcomes are at least 50% have gone from 3% of the population to 9% in six years.
Here are the overall areas dedicated to different scenarios in the 2022 graph (equivalent to averages):
That is, between them, these researchers put 31% of their credence on AI making the world markedly worse.
Some things to keep in mind in looking at these:
Here’s the 2022 data again, but ordered by overall optimism-to-pessimism rather than probability of extremely bad outcomes specifically:
For more survey takeaways, see this blog post. For all the data we have put up on it so far, see this page.
See here for more details.
Thanks to Harlan Stewart for helping make these 2022 figures, Zach Stein-Perlman for generally getting this data in order, and Nathan Young for pointing out that figures like this would be good.
Notes