Professor Scott Page Elected to the National Academy of Sciences

Page’s research focuses on diversity, institutions, and collective intelligence. He has written five books and more than one hundred articles in management, economics, political science, philosophy, statistics, psychology, and sociology.  

Page’s primary focus is theoretical, writing models that refine and challenge thinking. In recent years, one question has motivated his work: how can groups of people, and now increasingly, groups of people and artificial intelligence models, make better decisions and find more innovative solutions to problems than the individuals on their own? His most recent papers with Lu Hong, professor of finance from Loyola University Chicago, challenge traditional merit systems by demonstrating that when a group or team confronts a complex task, there exists no test that you can apply to select the best team.  

“You have to consider differences in cognitive tools, perspectives, and frameworks. In some instances, the collective intelligence of a group can be thought of as superadditive. The group does the same things as the individual, but does it better,” shared Page. “Often, groups and teams exhibit emergent collective intelligence in which the collective has functionalities that the individual parts don't.”  

A perfect example is how a well-established restaurant operates smoothly despite its many moving parts. Water glasses are filled. Dishes arrive. Plates are cleared. "All of this happens through adaptively coordinated actions. It's not like a marching band with a conductor. People create their routines, and the wait staff, the bussing staff, and the cooking staff learn procedures and protocols, queuing off information in their environment.”

In addition to his research, Page teaches courses on complex systems, such as Collective Intelligence (MO 410), at the Ross School of Business. In the classroom, Page blends mathematical concepts with practical business applications. He encourages students to tackle complex problems through simulations and interactive learning experiences. This dynamic classroom helps students develop the problem-solving and critical thinking skills they will need to build organizations and teams in the future.

When I arrived at the University of Michigan in 1981 as an undergrad, U-M’s value add was information and knowledge. Here were the books, the captured knowledge of the ages. As students, we were encouraged to spend time in the libraries as this would be our moment to have access to all that knowledge. Now, that’s all on our phones. I see my role as a professor as teaching students how to interact with and process that knowledge. I place a big emphasis on learning models and frameworks that they can use for sense making.

Looking to the future of his research, Page plans to explore the interaction between AI and humans in creative problem-solving and decision-making scenarios. He aims to uncover how AI can support businesses in reducing bias and improving organizational structures, particularly how AI and human systems can evolve together to enhance fairness and efficiency in decision-making.

“I’m particularly interested in how we redesign institutions in light of modern technology. If you were going to design a university, a democracy, or an organization from scratch, you would not design anything like our current institutions. Their forms are highly path-dependent, and owing to many structural forces, they do not perform as well as they could. In many ways, I am headed back in the direction of my graduate training in mechanical design.”

In addition to his work as a researcher and professor, Page is a frequent public speaker and consultant. He has brought his work on collective intelligence to globally recognized organizations, including NASA, Google, Boeing, the Aspen Ideas Festival, the World Economic Forum, the Federal Reserve System, Ford, and Gilead.