One of the people I met in my visit to George Mason University was Robin Hanson. At lunch we had a lively conversation about democracy–Hanson thinks it’s overrated! When I (innocently) told him that representative democracy seemed better than the alternatives, he pointed out that there are some successful alternatives out there. For example, Microsoft is a (de-facto) dictatorship, and it does pretty well. Did I think Microsoft would work better as a democracy, he asked? Well, hmm, I don’t know much about Microsoft, but yeah, I suppose that if some element of representative democracy were included, where employees, customers, and other “stakeholders” could vote for representatives that would have some vote in how things were run, maybe that would work well. At this point, someone else at lunch (sorry, I don’t remember his name) objected and said that only shareholders should have the vote. I said maybe that’s true about “should,” but in terms of actual outcomes I wouldn’t be surprised if things could be improved by including employees (and suppliers, customers, etc) in the decision-making. Bringing back to the main discussion, Robin pointed out that I had retreated from the claim that “democracy is best” to the claim that “some democracy could make things a little better.” He said that his point about democracy’s problems leads him to want to restrict the range of powers given to a democratic government and make the private sphere larger.
I don’t really know what to say about that–the distinction I was making was between “pure democracy” and “representative democracy.” My impression from the work in social and cognitive psychology on information aggregation is that representative democracy will work better than dictatorship or pure democracy.
Anyway, Robin gave me a copy of his paper proposing decision-making using betting markets. It’s an interesting paper, sort of a mix of a policy proposal and a criticism of our current political system. Here’s the abstract:
Democracies often fail to aggregate information, while speculative markets excel at this
task. We consider a new form of governance, wherein voters would say what we want, but
speculators would say how to get it. Elected representatives would oversee the after-the-fact
measurement of national welfare, while market speculators would say which policies they
expect to raise national welfare. Those who recommend policies that regressions suggest
will raise GDP should be willing to endorse similar market advice. Using a qualitative
engineering-style approach, we present three scenarios, consider thirty design issues, and
then present a more specific design responding to those concerns.
It’s an interesting paper and I have a few comments and questions:
– On page 8, Hanson notes that “betting markets beat major opinion polls.” I think betting markets are great, but comparing to opinion polls is a little misleading–a poll is a snapshot, not a forecast (see here for elaboration on this point).
– On page 10, Hanson proposes using GDP as a measure of policy success. When I read this, I thought, why not just use some measure of “happiness,” as measured in a poll, for example? One problem with a measure from a survey is that then the survey response itself becomes a political statement, so if, for example, you oppose the current government, you might be more likely to declare yourself “unhappy” for the purpose of such a poll. Joe Bafumi has found such patterns in self-reports of personal financial situations. GDP, on the other hand, can’t be so easily manipulated. For the purposes of Robin’s paper, I guess my point is that these properties of the “success measure” are potentially crucial.
– On page 11, Handon says, “an engineer [as compared to a scientist] is happy to work on a concept with a five percent chance of success, if the payoff from success would be thirty times the cost of trying.” I would hope that a scientist would think that way too!
– On pages 11-12, he says that “scientists usually have little use for prototypes and their tests…” This may be true of some scientists, but “prototypes” (in the sense of data analyses that illustrate new or untested methods) play a huge role in statistics. In fact, this may characterize most of my own published papers!
– On page 12, Hanson writes that “most corporations are in effect small democratic governments.” However, the vote of stockholders is not representative democracy as in U.S. politics, with defined districts, regularly scheduled elections for representatives, and so forth. I think this makes a big difference.
Now for my larger questions, which I think reflect my confusion about how this proposal would actually be implemented.
– Choice of policies to evaluate. I don’t quite see how you would decide which potential policies get a chance of being evaluated in the prediction market. There could be potentally thousands or millions of policies to compare, right? On page 26, Hanson suggests limiting these via a $100,000 fee, but this would seem to shut a lot of people out of the system. (Of course, Hanson might reply that the current system, in which politicians from Bloomberg to Bush can parlay money into votes, also has this problem. And I would agree. I’m just trying to understand how the current system would work. In practice, would there need to be a system of “primary elections” or “satellite tournaments” to winnow the proposals?
– Picking which proposal to implement. Suppose two or more conflicting proposals are judged (by the prediction markets) to improve expected GDP. Which one would be implemented? This sort of problem would just get worse if there were thousants of proposals to compare.
In some ways, this reminds me my idea of “institutional decision analysis,” which is that formal decision rules are appropriate for “institutional” settings where there is agreement on goals and also the need for careful justification of decisions. Similarly, Hanson’s “futarchy” technocratically formalizes decisions that otherwise would have been made politically (though bargaining, persuasion, maneuvering, manipulation of rules, and so forth).