Friday, October 6, 2017

Using Prediction Markets to Enhance US Intelligence Capabilities - Puong Fei Yeh

Summary and Critique by Evan Garfield


 Prediction markets allow participants to stake bets on the likelihood of various events taking place. This method involves the trading of contracts tied to future outcomes.The market price is essentially an estimate of the probability of a future outcome occurring. These market prices reflect the  participants collective confidence that an outcome will occur. In this article the author discusses the value in using prediction markets for the intelligence community. Shes emphasizes that prediction markets are reliable aggregate measures of disparate and dispersed information and can result in forecasts that are more accurate than those of experts. 

According to the author, use of prediction markets in the intelligence community can be traced back to 2001 within the Defense Advanced Research Project Agency (DARPA). DARPA’s Future Markets Applied to Prediction (FutureMAP) program tested the effectiveness of prediction markets in forecasting future events. Under the FutureMap program, the Policy Analysis Market (PAM) offered trading on a variety of different contracts (political, economic, military indicators, etc). The program, however, was very brief and terminated in 2003.

The author continues to discuss the Hayek hypothesis that market prices are the means in which disparate pieces of information are aggregated. According to Hayek, 

"The mere fact that there is one price for any commodity…brings about the solution which…might have been arrived at by one single mind possessing all the information which is, in fact, dispersed among all the people involved in the process"

Going off this point, the author stresses that prediction markets works even when people have limited knowledge about their surrounding environment and the people with whom they transact. She then applies this utility to address needs of the intelligence community. She cites the 9/11 Commission, and its conclusion that lack of unity of effort in information sharing as the biggest impediment to all-source analysis. 

The author then discusses some concerns with prediction markets including market design issues and market manipulation and bias. There are questions with regards to number of traders in a market. Furthermore, Analysts might engage in trading behavior to fit a certain policy outcome. Behavioral bias may also occur when traders trade according to the outcomes they desire rather than a dispassionate assessment of what is likely. She states, "An analogy is that in the run-up to the Iraq war, intelligence analysts were so convinced that Iraq had reconstituted their WMD programs that any evidence, regardless of its veracity, only served to harden their earlier convictions".


The author does a good job discussing the utility is using prediction markets for strategic intelligence as well as potential concerns when using prediction markets. However, more research is needed with regards to  as whether real-money markets produce better accuracy than play-money markets. Furthermore, more study is needed on whether prediction markets can be applied for tactical analysis. The author also does a good job stressing the utility of prediction markets in promoting collaborative intelligence and enhanced forecasting. The nature of this methodology also allows for non-subject matter experts to contribute without significantly hurting forecasting accuracy. This approach allows for broad contribution across the entire intelligence community and helps reduce the risk of group think. Given the compartmentalization of the intelligence community, prediction markets allow for invaluable aggregation of analyst input for complex issues.



  1. Evan, I believe that the number and diversity of traders in a prediction market affect the market price. Therefore, it would be interesting to know how the army goes about it.

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  3. Did this study show whether 'the market' got more accurate as time went on?