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--- how_to_make_valuable_prediction_markets [2022/12/17 20:52] – [How to make valuable prediction markets?] katjagrace
+++ how_to_make_valuable_prediction_markets [2023/09/29 17:59] (current) – [Ideas for classes of valuable prediction market] katjagrace
@@ Line 16: / Line 16: @@
 ===== Ideas for classes of valuable prediction market =====
   * **How much funding will org X get?** Seems maybe valuable because funders thinking about what is going to get funded anyway seems like a bit of a mess, though ideally you probably want some kind of coordination between the different parties who might fund a thing vs. everyone playing chicken and hoping someone else will fund something, or whatever happens; for making decisions in orgs, would often be really nice to know if you will have money, and there is much uncertainty. This also seems like a good use case for prediction markets because the info about it is spread among people, and you dont' know who has it really
+  * **Effectiveness-related metrics for charities** e.g. 'when this two-year trial is done, how many people will have turned out to get malaria in these villages?'
   * **funding of projects that haven't yet been funded** e.g. 'will I get a $50k grant from SFF or LTFF or OP to build ----'. People often fail to ask for money for projects, when they could get the money pretty easily, because they don't know what it looks like inside the funding orgs.
   * **‘Change my mind’ markets on research questions**
@@ Line 25: / Line 26: @@
   * **Recommendations for important problems** E.g. ‘What intervention will Alice do and consider responsible for causing her to work for >20h in some week?’ or ‘Who will Alice marry? (self-nominations only)’ [to avoid people being involved who don’t consent]
   * **What will happen with EA hubs in the coming years** E.g. ‘Will at least 100 people say they live in Austin in the 2025 EA survey?’
+  * **What will be the outcome of a trial?** RCTs for instance can be expensive and time consuming, so this is good for both getting results earlier, and in cases where the study isn't done. Apparently superforecasters were great at guessing what will happen in trials, in some research.
+===== More places where straightforward forecasts are used in decisionmaking =====
+  * What ads will be clicked?
+  *
+===== Types of uses for prediction market style forecasts =====
+  * Causing visceral updates, e.g. having to put a number on particular AI trait in 2028 makes it feel real in a different way.
+  * Info the
+===== Why are prediction markets not as useful as they seem? =====
+  * Just takes time for new things to be used (Katja doesn't buy that this is much of it)
+  * Questions need to either be formed as decision markets and thus conditional (and those markets are kind of awkward) or they need to be about a factual claim that would imply a decision directly.
+  * Prediction markets don't interface with people's normal decisionmaking
 ===== Ideas for specific valuable markets =====
   * How much will AI Impacts raise?