Faculty
David Rand is the Erwin H. Schell Professor and Professor of Management Science and Brain and Cognitive Sciences at MIT, the director of the Applied Cooperation Initiative, and an affiliate of the MIT Institute of Data, Systems, and Society, and the Initiative on the Digital Economy.
Bridging the fields of cognitive science, behavioral economics, and social psychology, David’s research combines behavioral experiments run online and in the field with mathematical and computational models to understand people’s attitudes, beliefs, and choices. His work uses a cognitive science perspective grounded in the tension between more intuitive versus deliberative modes of decision-making. He focuses on illuminating why people believe and share misinformation and “fake news,” understanding political psychology and polarization, and promoting human cooperation. David received his BA in computational biology from Cornell University in 2004 and his PhD in systems biology from Harvard University in 2009, was a post-doctoral researcher in Harvard University’s Department of Psychology from 2009 to 2013, and was an Assistant and then Associate Professor (with tenure) of Psychology, Economics, and Management at Yale University prior to joining the faculty at MIT.
David's work has been published in peer-reviewed journals such Nature, Science, Proceedings of the National Academy of Science, the American Economic Review, Psychological Science, Management Science, New England Journal of Medicine, and the American Journal of Political Science, and has received widespread attention from print, radio, TV, and social media outlets. He has also written popular press articles for outlets including the New York Times, Wired, New Scientist, and the Psychological Observer. He was named to Wired magazine’s Smart List 2012 of “50 people who will change the world,” chosen as a 2012 Pop!Tech Science Fellow, and awarded the 2015 Arthur Greer Memorial Prize for Outstanding Scholarly Research, fact-checking researcher of the year in 2017 by the Poyner Institute’s International Fact-Checking Network, and the 2020 FABBS Early Career Impact Award from the Society for Judgment and Decision Making. Papers he has coauthored have been awarded Best Paper of the Year in Experimental Economics, Social Cognition, and Political Methodology.
Featured Publication
"Durably Reducing Conspiracy Beliefs Through Dialogues with AI."Costello, Thomas H., Gordon Pennycook, and David G. Rand. Science. Forthcoming. Download Preprint.
Featured Publication
"Shifting Attention to Accuracy Reduces Misinformation Sharing."Pennycook, Gordon, Ziv Epstein, Mohsen Mosleh, Antonio Arechar, Dean Eckles, and David G. Rand. Nature Vol. 592, (2021): 590-595. Download Paper.
Mosleh, Mohsen, Qi Yang, Tauhid Zaman, Gordon Pennycook, and David G. Rand. Nature. Forthcoming.
Martel, Cameron and David G. Rand. Nature Human Behaviour. Forthcoming. Download Preprint.
Peysakhovich, Alexander and David G. Rand. Scientific Reports. Forthcoming.
Zhang, Yunhao and David G. Rand, MIT Sloan Working Paper 7064-24. Cambridge, MA: MIT Sloan School of Management, April 2024.
A paper in Nature suggests that the higher quantity of social media policy enforcement for conservative users could be explained by the higher quantity of misinformation shared by those users.
The artificial intelligence-powered “DebunkBot” reduced individuals’ belief in conspiracy theories and lessened their conspiratorial mindset, according to a new study.
Messaging based on a single characteristic — like party affiliation — can increase persuasion "by up to 70 per cent."
"Disasters are ripe for conspiracy theories because there is a lot of uncertainty as things are unfolding and a lot of fear."
"Narrowly defined 'fake news' - style misinformation is only a very small part of what causes misbelief."
A discussion of political polarization, misinformation, and how digital platforms can either foster constructive dialogue or deepen the divide.
This business process improvement course introduces a structured approach to design and customer analysis processes that draws on important trends that have become essential to successful innovation in today’s businesses: the digitization of all business processes; the blending of product and service into integrated solutions; considerations around environmental sustainability; and the use of globally-distributed teams.
Over six weeks, you’ll explore the technical and strategic considerations for robust, beneficial, and responsible AI deployment. You’ll examine the various stages of a proprietary ML Deployment Framework and unlock new opportunities by investigating the key challenges and their related impact. Guided by leading experts and MIT academics, you’ll build a toolkit for addressing these challenges within your own organization and context.
