I doubt that there are surveys of when people stayed home. You could maybe try to look at prediction markets but I'm not sure what you would compare them to to see if the prediction market was more accurate than some other reference group.

Thanks for collecting this timeline! 

The version of the claim I have heard is not that LW was early to suggest that there might be a pandemic but rather that they were unusually willing to do something about it because they take small-probability high-impact events seriously. Eg. I suspect that you would say that Wei Dai was "late" because their comment came after the nyt article etc, but nonetheless they made 700% betting that covid would be a big deal.

I think it can be hard to remember just how much controversy there was at the time. E.g. you say of March 13, "By now, everyone knows it's a crisis" but sadly "everyone" did not include the California department of public health, who didn't issue stay at home orders for another week. 

[I have a distinct memory of this because I told my girlfriend I couldn't see her anymore since she worked at the department of public health (!!) and was still getting a ton of exposure since the California public health department didn't think covid was that big of a deal.]

Congrats Samantha and the AIM team!

Thanks Vasco, I hadn't seen that. Do you know if anyone has addressed Nathan's "Comparative advantage means I'm guaranteed work but not that that work will provide enough for me to eat" point? (Apart from Maxwell, who I guess concedes the point?)

why are there fewer horses?

+1 to this being an important question to ask.

+1 to maintaining justification standards across cause areas, thanks for writing this post!

Fwiw I feel notably less clueless about WAW than about AI safety, and would have assumed the same is true of most people who work in AI safety, though I admittedly haven't talked to very many of them about this. (And also haven't thought about it that deeply myself.)

Is the amount which has been donated to the fund visible anywhere?

Sorry, I don't mean models that you consider to be better, but rather metrics/behaviors. Like what can V-JEPA-2 (or any model) do that previous models couldn't which you would consider to be a sign of progress?

What are examples of what you would consider to be progress on "effective video prediction"?