The mission of ISDM is to support, unite and develop the interdisciplinary study of human decision-making throughout the academic and policy landscape at NYU – linking the study of decision-making from the level of neurons to the level of social policy.
We accomplish this goal by connecting academic scholars in neuroscience, psychology, economics, marketing, management, information systems and finance with practitioners in urban informatics and with medical clinicians wrestling with the pathologies of decision-making. Our goal is to better understand the mechanisms, predict the impacts, and shape the policies that will define the study of decision-making tomorrow. We accomplish this goal by promoting interdisciplinary teaching of graduate and undergraduate students, by developing novel research infrastructures to support the propagation of neurobiological insights about the human animal into the policy domain, and by eliminating the friction that traditionally limits interdisciplinary study between disparate fields of inquiry. We hope to define a new kind of decision science that will impact not only international academic scholarship, but also medical practice, financial markets, and the social policies that shape our urban setting.
Central to this mission will be the linkage between traditional scholars working to understand decision-making and NYU’s flagship division for the study of urban informatics: The Center for Urban Science and Progress. Founded in 2012, CUSP is rapidly becoming the world center for urban informatics. With access to the massive data streams flowing through the City of New York, CUSP will provide the ISDM with a truly unique opportunity to test models and policies developed by scholars at a previously unimaginable scale. NYU’s unique assets: CUSP, the Stern School of Business, The Langone Medical Center, our International Campuses and our unique connection with New York, offer an unparalled opportunity to unite scholars studying decision-making in a synergy that would be possible nowhere else.