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Samotsvety Nuclear Risk update October 2022 (2022/10/03)

This writeup was originally posted on the EA Forum, which has some good discussion.

After recent events in Ukraine, Samotsvety convened to update our probabilities of nuclear war. In March 2022, at the beginning of the Ukraine war, we were at ~0.01% that London would be hit with a nuclear weapon in the next month. Now, we are at ~0.02% for the next 1-3 months, and at 16% that Russia uses any type of nuclear weapon in Ukraine in the next year. 

Expected values are more finicky and more person-dependent than probabilities, and readers are encouraged to enter their own estimates, for which we provide a template. We’d guess that readers would lose 2 to 300 hours by staying in London in the next 1–3 months, but this estimate is at the end of a garden of forking paths, and more pessimistic or optimistic readers might make different methodological choices. We would recommend leaving if Russia uses a tactical nuclear weapon in Ukraine.

Samotsvety’s AI risk forecasts (2022/09/09)

Crossposted to the EA Forum, LessWrong and Foxy Scout


In my review of What We Owe The Future (WWOTF), I wrote:

Samotsvety Nuclear Risk Forecasts — March 2022 (2022/03/10)

Thanks to Misha Yagudin, Eli Lifland, Jonathan Mann, Juan Cambeiro, Gregory Lewis, @belikewater, and Daniel Filan for forecasts. Thanks to Jacob Hilton for writing up an earlier analysis from which we drew heavily. Thanks to Clay Graubard for sanity checking and to  Daniel Filan for independent analysis. This document was written in collaboration with Eli and Misha, and we thank those who commented on an earlier version.

This writeup was originally posted on the EA Forum, which has some good discussion.


Prediction Markets in The Corporate Setting (2021/12/31)

What follows is a report that Misha Yagudin, Nuño Sempere, and Eli Lifland wrote back in October 2021 for Upstart, an AI lending platform that was interesting in exploring forecasting methods in general and prediction markets in particular. 

We believe that the report is of interest to EA as it relates to the institutional decision-making cause area and because it might inform EA organizations about which forecasting methods, if any, to use. In addition, the report covers a large number of connected facts about prediction markets and forecasting systems which might be of interest to people interested in the topic.

Note that since this report was written, Google has started a new internal prediction market. Note also that this report mostly concerns company-internal prediction markets, rather than external prediction markets or forecasting platforms, such as Hypermind or Metaculus. However, one might think that the concerns we raise still apply to these. 

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