Faculty
Abdullah Almaatouq is a computational social scientist and the Douglas Drane Career Development Associate Professor in Information Technology and Management at the MIT Sloan School of Management.
Abdullah’s research focuses on improving cooperation, coordination, and collective intelligence in decision-making systems, such as teams, committees, crowds, markets, and elections. Abdullah also explores ways to advance social and behavioral research methodology through innovative research designs and theory-building strategies, with the ultimate goal of developing a deeper understanding of collective decision systems and how to design them effectively in various contexts. He is affiliated with the MIT Center for Computational Engineering, the MIT Center for Collective Intelligence, and the MIT Connection Science Research Initiative.
Abdullah holds a PhD in computational science and engineering, as well as dual master's degrees in media arts and sciences (MIT Media Lab) and computational science and engineering from MIT. Prior to joining MIT, he earned his undergraduate degree from Southampton University in the United Kingdom.
Featured Publication
"Task Complexity Moderates Group Synergy."Almaatouq, Abdullah, Mohammed Alsobay, Ming Yin, and Duncan J. Watts. Proceedings of the National Academy of Sciences of the United States of America Vol. 118, No. 36 (2021): e210106211. Download Paper.
Featured Publication
"Adaptive Social Networks Promote the Wisdom of Crowds."Almaatouq, Abdullah, Alejandro Noriega-Campero, Abdulrahman Alotaibi, P.M. Krafft, Mehdi Moussaid, and Alex Pentland. Proceedings of the National Academy of Sciences Vol. 117, No. 21 (2020): 11379-86. Download Paper.
Almaatouq, Abdullah, Thomas L. Griffiths, Jordan W. Suchow, Mark E. Whiting, James Evans, and Duncan J. Watts. Behavioral and Brain Sciences Vol. 47, (2024): e33. SSRN Preprint.
Vaccaro, Michelle, Abdullah Almaatouq, and Thomas W. Malone. Nature Human Behaviour Vol. 8, No. 12 (2024): 2293-2303.
Burton, Jason W., Ulrike Hahn, Abdullah Almaatouq, and M. Amin Rahimian. Collective Intelligence Vol. 3, No. 2 (2024).
Almaatouq, Abdullah, Mohammed Alsobay, Ming Yin, and Duncan J. Watts. Topics in Cognitive Science Vol. 12, No. 2 (2024): 302-321.
A combination of AI and humans works best in tasks where humans outperform AI and in those that involve creating content.
After her daughter's traumatic brain injury (TBI), Lynne Becker became an entrepreneur on a mission—a mission to share with others what she learned about TBI. And ultimately, a mission to accelerate research and clinical trials. Two student teams taking MIT Sloan’s Analytics Lab (A-Lab) helped her through the early stages of her startup journey.
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."
"Users may be hesitant to trust a system whose decision-making process they do not understand."
Teams, it turns out, are better at solving complex problems, according to a recent paper by professor Abdullah Almaatouq.
