Faculty
Catherine Tucker is the Sloan Distinguished Professor of Management and a Professor of Marketing at MIT Sloan. She is the faculty director of the EMBA program. She has also been the Chair of the MIT Sloan PhD Program.
Her research interests lie in how technology allows firms to use digital data and machine learning to improve performance, and in the challenges this poses for regulation. Tucker has particular expertise in online advertising, digital health, social media, and electronic privacy. Her research studies the interface between marketing, the economics of technology, and law.
She has received an NSF CAREER Award for her work on digital privacy, the Erin Anderson Award for an Emerging Female Marketing Scholar and Mentor, the Garfield Economic Impact Award for her work on electronic medical records, the Paul E. Green Award for contributions to the practice of Marketing Research, the William F. O'Dell Award for most significant, long-term contribution to Marketing, and the INFORMS Society for Marketing Science Long Term Impact Award for long-run impact on marketing.
She is a cofounder of the MIT Cryptoeconomics Lab which studies the applications of blockchain. She has been a Visiting Fellow at All Souls College, Oxford. She has testified to Congress regarding her work on digital privacy and algorithms, and presented her research to the OECD, World Bank, IMF, and the ECJ.
Tucker is senior editor at Marketing Science. She has been coeditor at Quantitative Marketing and Economics and associate editor at Management Science, Marketing Science, and the Journal of Marketing Research. She is the codirector of the program on Digital Economics and Artificial Intelligence at the National Bureau of Economic Research.
She teaches MIT Sloan's course on Pricing and the EMBA course "Marketing Management for the Senior Executive." She has received the Jamieson Prize for Excellence in Teaching as well as being voted "Teacher of the Year" at MIT Sloan.
She holds a PhD in economics from Stanford University and a BA from the University of Oxford.
Tucker, Catherine. In Fair by Design, edited by Alex Teyteboym and Scott Kominers. Forthcoming.
Caro, Felipe, Jean-Edouard Colliard, Elena Katok, Axel Ockenfels, Nicolas Stier-Moses, Catherine Tucker, and D. J. Wu. Management Sciences. Forthcoming.
Cecere, Grazia, Fabrice Le Guel, Vincent Lefrere, Catherine E. Tucker, and Pai-Ling Yin. Academy of Management Perspectives. Forthcoming. SSRN Preprint.
Kozlova Guglielmi, Olga, Philipp Tillmann, and Catherine Tucker. In Research Handbook on Data, Privacy and Competition Law, edited by Catherine Tucker, Olga Kozlova Guglielmi, and Philipp Tillmann, 35-57. Cheltenham, UK: Edward Elgar Publishing, 2025.
Li, Linyi, Catherine Tucker, Rui Yan, and Rowan wang, Working Paper. October 2025.
Valenti, Albert, Chadwick J. Miller, and Catherine Tucker. Management Sciences Vol. 71, No. 10 (2025): 8586-8603.
Blockchain’s permanent record is one of its strengths, but it can cause problems for marketing strategies and consumer privacy.
Researchers analyzed 110 million YouTube comments. Their recommendation: Use algorithms to hide toxic speech, then follow up with human review.
Professor Catherine Tucker wrote: "AI systems can fail not only because they make biased predictions, but also because they make no meaningful predictions at all for certain individuals or populations. That is, unfairness may arise not only because an algorithm sees individuals incorrectly, but also because it does not see them at all when it tries to make real-time predictions."
"It matters when you see a competitor that's not part of this case actually say we're competing against Google Play."
Removing harmful social media platforms from the internet may push users to seek out other, more extreme outlets.
"Algorithmic exclusion occurs when algorithms are unable to even make predictions because they lack the data to so."
Machine learning, a branch of artificial intelligence, is the science of programming computers to improve their performance by learning from data. Dramatic progress has been made in the last decade, driving machine learning into the spotlight of conversations surrounding disruptive technology. This six-week online program from the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) aims to demystify machine learning for the business professional – offering you a firm, foundational understanding of the advantages, limitations, and scope of machine learning from a management perspective.
This online program draws on the work of leading MIT faculty and cryptoeconomics expert, Professor Christian Catalini, to examine blockchain technology from an economic perspective. You’ll be offered a foundational overview of how blockchain technology works, in order to demystify the technology and to understand its possibilities and limitations. Over the course of six weeks, you’ll be guided to understand blockchain technology beyond the fundamentals, and to appreciate its application and promise in the context of your own organization.
