Irving Wladawsky-Berger

Are Markets Efficient, Irrational, or Both?

The 2013 Nobel Prize in Economic Sciences was awarded last month to professors Eugene Fama and Lars Peter Hansen from the University of Chicago, and Robert Schiller  from Yale University “for their empirical analysis of asset prices.”  While there is general agreement that these three economists are most deserving of the prize, quite a few were also surprised that Fama and Schiller shared the award because they hold such different views of their discipline.

Professor Fama is the father of the efficient market theory, which says that prices in financial markets reflect all available information.  He has long maintained that he does not understand what people mean by financial bubbles and is thus not sure if they actually exist.  He is associated with the Chicago School of Economics, which believes that people generally make rational choices about their financial interests. 

Professor Schiller, one of the fathers of behavioral economics, holds very different views.  He believes that individual and crowd psychology strongly influence the behavior of markets and that social and emotional factors have a strong influence on the economic decisions made by individuals and institutions.  In 2000 Schiller published Irrational Exuberance, a book about the dot-com bubble, which he updated in 2005 to cover the housing bubble.

Understanding the Workings of Our Minds

Advances in technology, big data and analytics hold the promise to significantly augment our judgement and expertise and help us make smarter, more effective decisions.  But, as we contemplate these exciting innovations, it’s good to take a step back and ask ourselves a few basic questions: How do we make decisions in the first place? What goes on in our minds when we are making decisions, from the simplest to the most complex? 

I heard a fascinating talk by Daniel Kahneman that directly addressed these questions at the IBM Cognitive Systems Colloquium which I attended last month.  Kahneman is Professor of Psychology Emeritus at Princeton University and Senior Scholar at the Woodrow Wilson School.  In 2002, he was awarded the Nobel Prize in Economics “for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty.” 

The talk was based on his 2011 bestseller Thinking, Fast and Slow.  The book explains the major discoveries by psychologists and cognitive scientists over the past several decades that have led to our current understanding of judgement and decision-making.  In particular, it describes the pioneering work of Kahneman and his long time collaborator Amos Tversky, who died in 1996.

Humans, Machines and Collective Intelligence

Tom Malone gave a very interesting talk on collective intelligence at the IBM Cognitive Systems Colloquium which I recently attended and wrote about.  Malone is Professor of Management at MIT’s Sloan School and the founding director of the MIT Center for Collective Intelligence (CCI).  His research is primarily driven by this fundamental question: “How can people and computers be connected so that - collectively - they act more intelligently than any individuals, groups, or computers have ever done before?”  This is a very important question to explore to help us understand the impact of our increasingly smart machines on the very nature of work and organizations.  

Malone and his collaborators are conducting research on a number of topics in this area.  Do groups exhibit characteristic levels of intelligence which can be measured and used to predict the group’s performance across a wide variety of cognitive tasks?  If so, can you devise tests to measure the group’s intelligence using methodologies and statistical techniques similar to those that have been applied to measure the IQs of individuals for the past hundred years?

To answer these questions they conducted a number of studies where they randomly assigned individuals to different groups, which then worked on a variety of tasks.  Their research results were published in the October 2010 issue of Science.

Organizing Big Data Initiatives: Lessons from the Internet

In a recent CIO Journal article, Is There a Leadership Vacuum for Big Data?, my fellow guest columnist Tom Davenport reflected on whether institutions should appoint a dedicated executive to oversee their company-wide big data and analytics initiatives, and if so, which C-level senior executives should such a position report to.  His column was motivated by a 2012 Deloitte survey he was personally involved with of over 75 companies.

About 80 percent of the participating companies said that they were already using big data and analytics to a greater or lesser extent.  With few exceptions, all companies expected that these initiative will become more important to their organizations over the next three years.  But, the responsibility for the initiatives was all over the map, being managed by a variety of executives and functions.     

“An ongoing matter of debate among data analytics practitioners is whether or not analytics should be a more centralized function or one that is embedded within various corporate work streams and geographies,” notes the Deloitte survey . “The opinions are as varied as the companies and industries involved.”