New research reveals how physiology-inspired networks could improve political decision-making

By using simulations modeled after physiological systems, the researchers explored how networked structures of decision-makers can be designed to balance democratic values, efficiency, and technical limitations.

"Many existing political systems are inefficient, unstable, or undemocratic," said Alan Cohen, PhD, associate professor in the Butler Columbia Aging Center, and Principal Investigator on the study. "In our simulations, we found that while no single structure is perfect, some governance models are clearly more effective than others."

Cohen explains that the human body -- honed by billions of years of evolution -- offers a powerful analogy for organizing complex decision-making. "Our physiological systems constantly integrate signals and make decisions that maintain equilibrium. We applied a similar logic to political structures," he said.

The research focused on a model where small, interconnected subgroups operate within larger populations, allowing decisions to emerge through a structured, bottom-up process. This network-based model enables populations to make complex decisions efficiently while still reflecting the will of the broader group.

"Our findings highlight the value of decentralized, structured decision-making," noted Cohen, who is also associate professor of Environmental Health Sciences at Columbia Mailman School of Public Health. "The way these groups are organized -- and the connections between them -- can fundamentally shape the outcomes."

Despite the promise of the model, Cohen emphasizes that several important questions remain: How large should decision-making groups be? How should participants be selected? How many connections -- or "bridges" -- should exist between groups?

"There are also behavioral dynamics to consider," Cohen added. "What happens when some individuals dominate the discussion or refuse to reconsider their positions?"

Other critical dimensions, such as public satisfaction with decisions and the system itself, are more challenging to incorporate into the model but are vital for real-world applications. The potential for innovation -- how group discussions spark novel solutions -- also remains an open area for future study.

"While challenges remain, our research shows that a complex systems and modeling approach to governance offers a powerful lens through which to understand and improve decentralized decision-making," said Cohen. "This could open the door to more resilient, adaptive political systems in the future. This first study is a proof-of-concept: it shows that we can derive models of effective governance inspired by biological networks. Future work will illuminate the best ways to do that. Given the current state of politics, I think we'd all agree there is a pressing need for more robust political systems."

Co-authors are Laurent Hébert-Dufresne, Nicholas W. Landry, Juniper Lovato, Jonathan St-Onge, Jean-Gabriel Young from the University of Vermont; and Marie-Ève Couture-Ménard and Stéphane Bernatchez, and Catherine Choquette, Université de Sherbrooke, Canada

The study was supported by the Fonds de recherche du Québec through an Audace award and by The Alfred P. Sloan Foundation.