Progress in computing technology now allows machines to use vast amounts of data to make predictions that are often more accurate than those by human experts. Yet, humans are more adept at processing unstructured information and at recognizing unusual circumstances and their consequences.  Can we combine predictions from humans and machines to get predictions that are better than either could do alone?  
This project involves using prediction markets and other methods to combine predictions from groups of people and artificial intelligence agents.  In our work so far, we have found that the combined predictions were both more accurate and more robust than those made by groups of only people or only machines. This combined approach may be especially useful in situations where patterns are difficult to discern, where data are difficult to codify, or where sudden changes occur unexpectedly.

Nagar, Y. & Malone, T. W.  Making Business Predictions by Combining Human and Machine Intelligence in Prediction MarketsProceedings of the International Conference on Information Systems ICIS 2011, Shanghai, China, December 5, 2011.

Nagar, Y., & Malone, T. W. (2012).  Improving predictions with hybrid marketsProceedings of the American Association of Artificial Intelligence (AAAI) Fall Symposium on Machine Aggregation of Human Judgment, Arlington, VA, November 2-4, 2012 (Published in on-line proceedings as AAAI Technical Report FS-12-06.

Principal Investigator
Thomas W. Malone

Graduate Students
Yiftach Nagar

Alexander (Sandy) Pentland
Tomaso Poggio
Drazen Prelec
Josh Tenenbaum