I think "Changes in funding in the AI safety field" was published by the Centre for Effective Altruism.

Part 2: https://twitter.com/dwarkesh_sp/status/1673355293890347010

The transcript can be found on this link as well.

You may want to have a look at the list of topics. Some of the terms above are listed there; e.g. Bayesian epistemology, counterfactual reasoning, and the unilateralist's curse.

Nice comment, you make several good points. Fwiw, I don't think our paper is conflict with anything you say here.

On this theme: @Lucius Caviola and myself have written a paper on virtues for real-world utilitarians. See also Lucius's talk Against naive effective altruism.

I gave an argument for why I don't think the cry wolf-effects would be as large as one might think in World A. Afaict your comment doesn't engage with my argument.

I'm not sure what you're trying to say with your comment about World B. If we manage to permanently solve the risks relating to AI, then we've solved the problem. Whether some people will then be accused of having cried wolf seems far less important relative to that.

I also guess cry wolf-effects won't be as large as one might think - e.g. I think people will look more at how strong AI systems appear at a given point than at whether people have previously warned about AI risk.

Thanks, very interesting.

Regarding the political views, there are two graphs, showing different numbers. Does the first include people who didn't respond to the political views question, whereas the second exclude them? If so, it might be good to clarify that. You might also clarify that the first graph/sets of numbers don't sum to 100%. Alternatively, you could just present the data that excludes non-responses, since that's in my view the more interesting data.

Yes, I think that him, e.g. being interviewed by 80K didn't make much of a difference. I think that EA's reputation would inevitably be tied to his to an extent given how much money they donated and the context in which that occurred. People often overrate how much you can influence perceptions by framing things differently.