I've significantly improved the Candidate Scoring System which looks at the 2020 US presidential election.
There is now a permanent link to reduce the confusion of different versions. When making updates, I will save over the same PDF. And within this document, the links to supplementary CSS files (the Excel model, the draft for shared editing and updates, and supplemental collections of evidence/arguments) will remain permanent as well.
https://1drv.ms/b/s!At2KcPiXB5rkyABaEsATaMrRDxwj?e=VvVnl2
The report itself has been improved in a variety of ways - more comprehensive, more accurate, etc. The conclusions have changed but not to such an extent that our previous recommendations could be considered harmful. Some major updates are: (1) Very helpful analysis from FiveThirtyEight which suggests that we should focus much more on major candidates and much less on minor candidates, as the former seem much more tractable. Thus Buttigieg becomes the top recommendation now. (2) Lower opinion of Andrew Yang, due to placing less weight on domestic tech policy and more weight on international relations for the purpose of mitigating x-risk. This was not an arbitrary change of mind, but an implication of a very sensible revision of how the issues were divided. If someone wants to increase the weight of "Emerging Tech" then we can have that debate.
I am still not confident that it is robustly argued and defended well enough to be worth broadly sharing as outreach to mass audiences (e.g. "vote for so-and-so, here's the EA proof") lest they find problems with it and then condemn EA to the detriment of other causes like global poverty, etc. However, for EAs and any EA-adjacent people, it should be useful and at least somewhat persuasive - not just for this election but also as a broader summary of ideas on political policy. It's also probably good to share with people who will happen to agree with some of its conclusions.
As always, I will take a careful look at all input and am open to collaboration.
For one thing, it's not clear how to translate polls into probabilities. Let's assume for sake of argument that when Jack is at 5% in the polls and Jill is at 4%, then Jack is necessarily more likely to win the primaries than Jill. But we still don't know: how much more likely? What are their probabilities of victory? Translating the polling into expectations (which is necessary for calculating expected value) is difficult. Better to let the prediction markets do that efficiently than to rely on my own guess.
Second, prediction markets take into account lots of other information besides the superficial polling numbers, like: who are voters 2nd and 3rd choices? Which candidate has more momentum? Which candidate is doing best in Iowa/NH? Who has more money? etc.
The reason prediction markets ever tell you something different from the polls is because they are taking into account issues like the above. Their track record is very good as I understand.