I think some of the AI safety policy community has over-indexed on the visual model of the "Overton Window" and under-indexed on alternatives like the "ratchet effect," "poisoning the well," "clown attacks," and other models where proposing radical changes can make you, your allies, and your ideas look unreasonable. I'm not familiar with a lot of systematic empirical evidence on either side, but it seems to me like the more effective actors in the DC establishment overall are much more in the habit of looking for small wins that are both good in themselves and shrink the size of the ask for their ideal policy than of pushing for their ideal vision and then making concessions. Possibly an ideal ecosystem has both strategies, but it seems possible that at least some versions of "Overton Window-moving" strategies executed in practice have larger negative effects via associating their "side" with unreasonable-sounding ideas in the minds of very bandwidth-constrained policymakers, who strongly lean on signals of credibility and consensus when quickly evaluating policy options, than the positive effects of increasing the odds of ideal policy and improving the framing for non-ideal but pretty good policies. In theory, the Overton Window model is just a description of what ideas are taken seriously, so it can indeed accommodate backfire effects where you argue for an idea "outside the window" and this actually makes the window narrower. But I think the visual imagery of "windows" actually struggles to accommodate this -- when was the last time you tried to open a window and accidentally closed it instead? -- and as a result, people who rely on this model are more likely to underrate these kinds of consequences. Would be interested in empirical evidence on this question (ideally actual studies from psych, political science, sociology, econ, etc literatures, rather than specific case studies due to reference class tennis type issues).

Quick poll [✅ / ❌]: Do you feel like you don't have a good grasp of Shapley values, despite wanting to?  (Context for after voting: I'm trying to figure out if more explainers of this would be helpful. I still feel confused about some of its implications, despite having spent significant time trying to understand it)

Trump recently said in an interview (https://time.com/6972973/biden-trump-bird-flu-covid/) that he would seek to disband the White House office for pandemic preparedness. Given that he usually doesn't give specifics on his policy positions, this seems like something he is particularly interested in. I know politics is discouraged on the EA forum, but I thought I would post this to say: EA should really be preparing for a Trump presidency. He's up in the polls and IMO has a >50% chance of winning the election. Right now politicians seem relatively receptive to EA ideas, this may change under a Trump administration.

Excerpt from the most recent update from the ALERT team:   Highly pathogenic avian influenza (HPAI) H5N1: What a week! The news, data, and analyses are coming in fast and furious. Overall, ALERT team members feel that the risk of an H5N1 pandemic emerging over the coming decade is increasing. Team members estimate that the chance that the WHO will declare a Public Health Emergency of International Concern (PHEIC) within 1 year from now because of an H5N1 virus, in whole or in part, is 0.9% (range 0.5%-1.3%). The team sees the chance going up substantially over the next decade, with the 5-year chance at 13% (range 10%-15%) and the 10-year chance increasing to 25% (range 20%-30%).   their estimated 10 year risk is a lot higher than I would have anticipated.

This is an interesting #OpenPhil grant. $230K for a cyber threat intelligence researcher to create a database that tracks instances of users attempting to misuse large language models. https://www.openphilanthropy.org/grants/lee-foster-llm-misuse-database/  Will user data be shared with the user's permission? How will an LLM determine the intent of the user when it comes to differentiating between purposeful harmful entries versus user error, safety testing, independent red-teaming, playful entries, etc. If a user is placed on the database, is she notified? How long do you stay in LLM prison?  I did send an email to OpenPhil asking about this grant, but so far I haven't heard anything back.