Faculty
Thomas W. Malone is the Patrick J. McGovern (1959) Professor of Management at the MIT Sloan School of Management and the founding director of the MIT Center for Collective Intelligence. At MIT, he is also a Professor of Information Technology and a Professor of Work and Organizational Studies. Previously, he was the founder and director of the MIT Center for Coordination Science and one of the two founding codirectors of the MIT Initiative on Inventing the Organizations of the 21st Century. Malone teaches classes on organizational design, information technology, and leadership, and his research focuses on how new organizations can be designed to take advantage of the possibilities provided by information technology.
Malone predicted in an article published in 1987 many of the major developments in electronic business over the following 25 years, including electronic buying and selling for many kinds of products. In 2004, Malone summarized two decades of his research in his critically acclaimed book, The Future of Work. His newest book, Superminds, appeared in May 2018. Malone has also published over 100 articles, research papers, and book chapters. He is the coeditor of four books.
Malone has been a cofounder of four software companies and has consulted and served as a board member for a number of other organizations. He is also an inventor with 11 patents.
His background includes work as a research scientist at Xerox Palo Alto Research Center (PARC), a PhD from Stanford University, an honorary doctorate from the University of Zurich, and degrees in applied mathematics, engineering, and psychology.
Featured Publication
Superminds: The Surprising Power of People and Computers Thinking Together.Malone, Thomas W. New York, NY: Little, Brown and Company, 2018.
Vaccaro, Michelle, Abdullah Almaatouq, and Thomas Malone. Nature Human Behaviour. Forthcoming.
Laubacher, Robert, Annalyn Bachman, Kathleen Kennedy, and Thomas W. Malone, MIT Sloan Working Paper 6961-23. Cambridge, MA: MIT Sloan School of Management, December 2023.
Alice Cai, Steven R. Rick, Jennifer Heyman, Yanxia Zhang, Alexandre Filipowicz, Matthew K. Hong, Matthew Klenk, and Thomas W. Malone. In CI '23: Proceedings of The ACM Collective Intelligence Conference, Delft, Netherlands: November 2023.
Flack, Jessica, Panos Ipeirotis, Thomas W. Malone, Geoff Mulgan, and Scott E. Page. Collective Intelligence, August 2022.
Koppineni, Akhilesh, David Sun Kong, and Thomas W. Malone, MIT Sloan Working Paper 6569-22. Cambridge, MA: MIT Sloan School of Management, February 2022.
“We’re looking for innovative ways to combine people and computers by taking advantage of what each does best,” says Tom Malone.
“When Combinations of Humans and AI Are Useful” is the first large-scale meta-analysis conducted to better understand when human-AI combinations are useful in task completion, and when they are not.
Humans and AI don't work as well together as many assume. What is the point in which human tasks and AI tasks are best blended?
"A growing number of studies reveal that human–AI systems do not necessarily achieve better results than the best of humans or AI alone."
We asked 8 MIT Sloan faculty members about their new projects and what they see as the most exciting — and concerning — aspects of the AI boom.
"It may be cheaper just to pay a driver to sit in the car and drive it."
This online program from the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) challenges common misconceptions surrounding AI and will equip and encourage you to embrace AI as part of a transformative toolkit. With a focus on the organizational and managerial implications of these technologies, rather than on their technical aspects, you’ll leave this course armed with the knowledge and confidence you need to pioneer its successful integration in business.
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.
