VERIPHIX CO-AUTHORED RESEARCH PAPERS: JENNIFER WATKINS / CTO

From a psychological perspective, the laundry list of ways in which humans fail to make good decisions is extensive. Cognitive biases, as they are called, confound a sizable portion of our thinking. An individual may use a few salient examples of negative comments from her boss to conclude that she is going to lose her job (attribution bias). She subconsciously begins to seek out additional information confirming this belief, ignoring the fact that she just received high marks in her annual performance review (confirmation bias). Eventually, her fear over losing her job affects her performance enough that she is fired (self-fulfilling prophecy) and when she looks back she can say with total confidence that she saw it coming the whole time (hindsight). When we consider individuals acting in a group, the situation only worsens. Indeed, if we are to believe the anecdotes of MacKay’s mad crowds, 2 when people act together their worst characteristics are only magnified. More recently, this phenomenon has been characterized as groupthink, the bane of every boardroom. In fact, if we refer to the cognition literature, groupthink is only one of many socially based cognitive biases that boardroom executives should fear.

Watkins, Jennifer H., “Collectively Intelligent Systems”, Collective Intelligence: Creating a Prosperous World at Peace, Ed. Mark Tovey. Oakton, VA: EIN Press, ISBN 13: 978-0-9715661-6-3, April 2008. 275--278.

Prediction Markets as an Aggregation Mechanism for Collective Intelligence,

Collective intelligence is the result of the proper aggregation of local information from many individuals to generate an optimal global solution to a problem. Often, these solutions are more optimal than what any individual could have provided. In this article, we focus on prediction markets as the aggregation mechanism for collective intelligence. Prediction markets, like commodity markets, channel inputs from all traders into a single dynamic stock price. Instead of determining the value of a particular good, a prediction market is used to determine the probability of a particular event occurring. We present and discuss five features of prediction markets that urge a collective toward optimal solutions. Through the combination of these features, prediction markets lend themselves to the systematic study of the promising phenomenon of collective intelligence.

Watkins, Jennifer H., “Prediction Markets as an Aggregation Mechanism for Collective Intelligence,” Proceedings of 2007 UCLA Lake Arrowhead Human Complex Systems Conference, Lake Arrowhead, CA, 25--29 April 2007. LA-UR-07-2027.

Measuring Cross-Cultural Stimulus-Response on the Internet

The Internet is now an accepted form of discourse around the world on subjects ranging from the mundane to the serious. Weblogs, chat rooms, and forums provide a new source of data on attitude diffusion and opinions to events across the world. In addition to providing valuable data for social science research, the Internet is allowing new forms of social and political behavior to occur. In this paper we present initial research on measuring the rate of Internet activity to key events over time. We present measurements of stimulus-response temporal dynamics using open-source free web analysis tools.

MacKerrow, Edward P. and Jennifer H. Watkins. “Measuring Cross-Cultural Stimulus-Response on the Internet,” Advances in Occupational, Social, and Organizational Ergonomics, Eds. Peter Vink and Jussi Kantola, Boca Raton, FL: CRC Press, June 2010, chapter 7.

A Survey of Web-based Collective Decision Making Systems

A collective decision making system uses an aggregation mechanism to combine the input of individuals to generate a decision. The decisions generated serve a variety of purposes from governance rulings to forecasts for planning. The Internet hosts a suite of collective decision making systems, some that were inconceivable before the web. In this paper, we present a taxonomy of collective decision making systems into which we place seven principal web-based tools. This taxonomy serves to elucidate the state of the art in web-based collective decision making as well as to highlight opportunities for innovation.

Watkins, Jennifer H. and Marko A. Rodriguez, “A Survey of Web-based Collective Decision Making Systems”, Studies in Computational Intelligence: Evolution of the Web in Artificial Intelligence Environments, Eds. R. Nayak, N. Ichalkaranje, and L.C. Jain, Berlin: Springer-Verlag, LA-UR-07-2028, ISBN: 978-3-540-79139-3, 2008. 245--279.

Jen is a computational social scientist specializing in collective decision systems. Before Veriphix she worked at Los Alamos National Laboratory designing agent based simulations that modeled key policy questions and designing web applications to aid counterterrorism operations.