The interest within the EA community in forecasting long predates the existence of any gamified forecasting platforms, so it seems pretty unlikely that at a high level the EA community is primarily interested because it’s a fun game (this doesn’t prove more recent interest isn’t driven by the gamified platforms, though my sense is that the current level of relative interest seems similar to where it was a decade ago, so it doesn’t feel like it made a huge shift).
Also, AI timelines forecasting work has been highly decision-relevant to a large number of people within the EA community. My guess is it’s the single research intervention that has caused the largest shift in altruistic capital allocation in the last few years. There also exists a large number of pretty simple arguments in favor of forecasting work being valuable, which have been made in many places (some links here, also a bunch of Robin Hanson’s work on prediction markets).
At a higher level, there are also many instances of new types of derivatives markets increasing efficiency of some market, which would probably also apply to prediction markets.
I feel like the prediction-markets themselves are best modeled as derivative markets. And then you are talking about second-order derivative markets here. But IDK, mostly sounds like semantics.
The interest within the EA community in forecasting long predates the existence of any gamified forecasting platforms, so it seems pretty unlikely that at a high level the EA community is primarily interested because it’s a fun game (this doesn’t prove more recent interest isn’t driven by the gamified platforms, though my sense is that the current level of relative interest seems similar to where it was a decade ago, so it doesn’t feel like it made a huge shift).
Also, AI timelines forecasting work has been highly decision-relevant to a large number of people within the EA community. My guess is it’s the single research intervention that has caused the largest shift in altruistic capital allocation in the last few years. There also exists a large number of pretty simple arguments in favor of forecasting work being valuable, which have been made in many places (some links here, also a bunch of Robin Hanson’s work on prediction markets).
At a higher level, there are also many instances of new types of derivatives markets increasing efficiency of some market, which would probably also apply to prediction markets.
FYI, just wrote a small piece on “Higher-order forecasts”, which I see as the equivalent to derivatives. https://forum.effectivealtruism.org/posts/PB57prp5kEMDgwJsm/higher-order-forecasts
I agree they can help with efficiency.
I feel like the prediction-markets themselves are best modeled as derivative markets. And then you are talking about second-order derivative markets here. But IDK, mostly sounds like semantics.
Yea, that’s a reasonable way of looking at it. Agreed it is just semantics.
As semantics though, my guess is that “nth-order forecasts” will be more intuitive to most people than something like “n-1th order derivatives”.