What if you could measure the intelligence of a group? What if you could predict which committees, assigned to design a horse, would end up with a camel, versus which would develop a thoroughbred—or a racecar? The MIT Sloan School of Management’s Center for Collective Intelligence (CCI) was set up to accomplish just that sort of evaluation. Under the leadership of its founding director, Thomas W. Malone, the center’s ambition is to put forth a new theory of group performance, bringing together insights from social psychology, computer science, group dynamics, social media, crowdsourcing, and the center’s own experiments in group behavior. The results could help business teams produce more thoroughbreds and fewer camels.
Malone is the Patrick J. McGovern Professor of Management at the MIT Sloan School and a key figure in organizational learning and design studies. Formerly a research scientist at Xerox Palo Alto Research Center (PARC), he holds 11 patents, largely in user interface design and the representation of complex processes in software. Like other technologists (one thinks of the late computer interface pioneer Douglas Engelbart), Malone grew interested in the ways that organizational design and computer systems design could augment each other. His book The Future of Work: How the New Order of Business Will Shape Your Organization, Your Management Style, and Your Life (Harvard Business School Press, 2004) proposed that in an increasingly networked world, strict hierarchies would be less viable. The book also foreshadowed the decentralized “bottom-up” management model that has influenced companies like Zappos.
Why Women Make Teams Smarter
MIT professor Thomas Malone discusses why women can increase a group's collective intelligence.
Malone set up CCI in 2006, drawing together a group of management scholars, neuroscientists, and computer scientists (some of whom, including Alex “Sandy” Pentland, Erik Brynjolfsson, and Pattie Maes, have been featured in our pages). Tim Berners-Lee, Jimmy Wales, and Alpheus Bingham—the progenitors of the World Wide Web, Wikipedia, and the crowdsourcing platform InnoCentive, respectively—make up the center’s advisory board.
CCI’s most provocative finding so far is that, by and large, the higher the proportion of women on a team, the more likely it is to exhibit collective intelligence (and thus achieve its goals). This research was originally published in Science (“Evidence for a Collective Intelligence Factor in the Performance of Human Groups,” by Malone and Carnegie Mellon assistant professor Anita Williams Woolley et al., Oct. 2010) and highlighted in April 2013 in a Harvard Business Review interview with Malone and Woolley. The critical factor appears to be social perception. Women are, on average, more perceptive than men about their colleagues. Social perceptiveness is a kind of social intelligence; it’s the ability to discern what someone is thinking, either by looking at their facial expression or through some other means of human observation. When it comes to the effectiveness of groups, we are what we see in each other. And if this kind of acumen can be learned, Malone’s research suggests that the performance of teams (and companies) can be dramatically improved.
Audio — In Conversation with Thomas Malone
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In December 2013, Malone met with strategy+business at MIT’s Sloan School in Cambridge, Mass. He talked about the origins of his research, the comprehensive study he conducted with about 150 groups, and the implications for individuals, teams, and large-scale enterprises.
S+B: How did your work on measuring collective intelligence get its start?
MALONE: As codirector of the MIT project “Inventing the Organizations of the 21st Century,” I did a lot of thinking about how new technologies would change the ways work is organized. In The Future of Work, I suggested that cheap communications would lead to much more human freedom and decentralized decision making in business. After that, I considered following up with another book about how to implement these ideas, and what companies were actually making them work. But the more I thought about it, the more I became convinced that I should look instead at what was coming next: the evolution of management beyond decentralization.
Around that time, I had dinner with the venture capitalist and writer Esther Dyson and the mathematician and science fiction writer Vernor Vinge. Vernor was working on his book Rainbows End, which describes what he calls “superhuman intelligence” that combines the intelligence of people and computers. Of course, Douglas Engelbart and others had talked about possibilities like this for a long time, and it was certainly something I had thought about, too. By the end of that conversation, I was convinced that I should work on this concept next. It didn’t so much feel like a new idea or an inspiration; I was finally taking a path that, at some level, I had known for a long time was the right path to take.
I began to imagine what it would be like to have very intelligent organizations. From there came the question, which would ultimately be the core research question of the Center for Collective Intelligence: How can people and computers be connected so that—collectively—they act more intelligently than any person, group, or computer has ever done before? When you take that question seriously, it leads to a view of organizational effectiveness that is very different from the prevailing wisdom of the past.
S+B: Why are computers part of the definition of collective intelligence?
MALONE: Actually, they’re not part of the definition. I define collective intelligence as groups of individuals acting together in ways that seem intelligent. In other words, intelligence is not just something that happens inside individual brains. It also arises in groups of individuals. Those groups don’t require computers. In fact, by this broad definition, collective intelligence has existed for thousands of years. For instance, armies, companies, countries, and families are all examples of groups of people who work together in ways that—at least sometimes—seem intelligent.