The Twin Revolutions in Social Science
Stanford GSB faculty are taking advantage of two massive changes in the science of how we behave, Dean Levin explains.
May 01, 2018
Stanford GSB strives to educate innovative and principled leaders, and to create and apply knowledge for the betterment of the world. This year I’ve had the pleasure of talking with many Stanford GSB faculty and graduate students about the work they’re doing, as well as others around Stanford as part of the university’s long-range planning process. I have been struck by two transformative changes that are happening in the areas from which many Stanford GSB faculty are drawn, in particular the social sciences and engineering.
The first is the result of greater collection of and access to data. Over the last decade, it has become possible to measure and record far more human activity than at any previous point in history. This has given rise to vast private and public sector datasets with information on individual behavior, households and organizations, market transactions, physical locations, communication, and relationships. In the hands of faculty at Stanford and elsewhere, these new data are changing our understanding of inequality and mobility, economic and organizational productivity, the structure of social networks, and market behavior.
A few examples are illustrative. Recently, Stanford GSB economists Rebecca Diamond and Paul Oyer set out to study whether there is a gender gap in earnings among gig economy workers. They developed a collaboration with Uber that allowed them to analyze the anonymized driving histories of over a million drivers. Their study found that female drivers earn around 7% less than their male counterparts, and isolated the exact sources of the earnings gap, including driver choices about when and how much to work. A few years ago, a leading study on work hours and pay differentials might have looked only at annual earnings or the detailed behavior of a few hundred or thousand workers.
Amir Goldberg, a faculty member in organizational behavior, collaborates with sociologists and computer scientists to study organizational culture. He has developed methods to translate enormous datasets of corporate emails into insights about organizational networks and relationships. Ilya Strebulaev, one of our finance faculty members, has partnered with Stanford GSB alumni, and others in the venture capital industry, to construct perhaps the most comprehensive dataset on venture financing contracts. His recent work, which has attracted significant attention, shows that the valuations of tech unicorns are misleading unless one accounts for the share preferences received by later-stage investors.
The second transformative change, which parallels the ongoing data revolution, is the increased desire of faculty to translate research ideas into applications with social impact. This work can take several forms: collaborations with firms, social sector organizations, and government agencies to develop and implement solutions to practical problems; or the design of field experiments to test theories and identify “what works,” guided by academic innovation. This impact revolution draws on both data-intensive and theoretical research.
Starting more than 20 years ago, faculty members Paul Milgrom and Robert Wilson began to develop auction methods that have enabled the United States and other countries to allocate hundreds of billions of dollars of telecommunications licenses. The National Academies recently recognized their work, along with that of David Kreps, with the biennial Carty Award. Today, Stanford has the strongest collection of “market designers” anywhere in the world, including Stanford GSB faculty members Mohammad Akbarpour, Susan Athey, Jeremy Bulow, Michael Ostrovsky, Daniela Saban, Andy Skrzypacz, and Gabriel Weintraub, who use game theory and data to study everything from government procurement to internet marketplaces to the allocation of donated kidneys to patients.
Other examples at Stanford GSB include efforts to address social problems by working with government agencies. Benoît Monin, in our organizational behavior group, got involved several years ago in studying the Oakland Police Department. Today, he and other Stanford researchers are collaborating with the department to reduce racial disparities and improve relationships with the communities they serve. Political economy faculty member David Broockman has taken a different approach to studying discrimination. David, whose research often utilizes large-scale field experiments to study political campaigns and belief formation, has shown that it is possible to durably reduce ingrained prejudices against transgender individuals and shift attitudes toward anti-discrimination legislation with relatively short face-to-face conversations.
The twin revolutions in social science promise to open the door to fundamental advances in discovery and understanding, and to accelerate the innovation and application of private and public sector solutions to societal challenges. As the examples illustrate, they also call for innovative new models in academia — a greater focus on collaborative research, the need to assemble teams and computing infrastructure to deal with enormous datasets, and the need to partner with public and private sector organizations to obtain data, run experiments, and implement solutions — which we are supporting.
The opportunity is exciting because both innovation and execution are sorely needed to address many of the pressing problems facing society — the need for broad-based social and economic opportunity, for greater organizational innovation, for addressing the impacts of changing technology, and for designing effective public policy. As we move forward in this new era, Stanford GSB faculty are a catalyzing force in developing a deeper understanding of business and social issues, and promoting solutions.
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