Futarchy
The economist Robin Hansen has explored the application of prediction markets in similar contexts in his work on the idea of a “Futarchy”. His focus has been on using such markets to replace existing models of democratic governance, but his exploration of how they could be relevant to public policy choices is pretty close to what we are talking about. As Hansen notes:
"Policy disputes arise at all scales of governance: in clubs, non-profits, firms, nations, and alliances of nations. Both the means and ends of policy are disputed. While many, perhaps most, policy disputes arise from conflicting ends, important disputes also arise from differing beliefs on how to achieve shared ends."
He suggests that by using prediction markets we could improve the process of selecting the most effective public policies, once we had decided what our goals were and elected representatives who shared those goals. (He catchily sums this up as “vote on values, bet on beliefs”). Hansen makes a number of theoretical arguments in favour of a prediction market model, but is also careful to point out that we needn’t rely on theoretical justification because:“the main reason to believe in speculative market accuracy…is the robust and consistent empirical track record.” i.e. You don’t need to have any ideological commitment to the idea of prediction markets as a way of addressing information failure, because the available evidence is just that they do work.
He is also clear that his idea is not the same as the “wisdom of crowds”, and that there is still quite a lot of inherent value in expertise:
“Speculators tend to rely more on crowds when crowds know more, and on experts when experts know more. Yes, the best track bettors have no higher IQ, but speculative markets if anything still over-emphasize experts, both public and private….Instead, the main reasons for superior speculative market accuracy seem to be incentive and selection effects: stronger accuracy incentives tend to reduce cognitive biases, and those who think they know more tend to trade more, and specialists are paid to eliminate any biases they can find.”
This should be reassuring (in one sense) to existing charitable organisations when it comes to considering the possibility of social impact prediction markets, as they would surely have an advantage as a result of their knowledge of what works in terms of delivering social outcomes (wouldn’t they…?) I suppose the really interesting thing is that this model would provide a concrete test of that supposition, by gauging exactly how much confidence each participant actually had in their own “theory of change”.
This gives me amazing visions of a huge (metaphorical) poker table, around which a range of philanthropic funders are sitting and assessing how strong their own hand is to gauge whether they think they can win the big social impact pot in the middle. There are some high-rolling foundations dotted around the table as well as a mix of innovative smaller charities, philanthropists, individual social entrepreneurs, corporates and social purpose start-ups. So whose idea about how to solve the problem at hand is going to prove to be most effective, and ho much are they willing to stake on their belief in it? Ooh, look: the Effective Altruist on the end of the table has just gone all in on her hand- but is she bluffing…?