Body networks inspire better political systems

What should I do if the governance structure is more like the human body? A pioneering study published in NPJ complexity shows that this biological approach can help solve one of the most fundamental challenges of democracy – comparing coherent decision-making with public opinion representing diverse representations.

Researchers at Columbia and the University of Vermont have developed a mathematical framework that models political decision-making as an interconnected network rather than traditional hierarchical structures, drawing inspiration from the stability of biological systems.

“Many existing political systems are inefficient, unstable or undemocratic,” said Alan Cohen, the Butler Columbia Center for Aging and principal investigator of the study. “In our simulations, we found that while no perfect structure is perfect, some governance models are obviously more effective than others.”

The research team builds decisions on “democratic satisfaction issues” – basically asking the group how to make logically coherent decisions while still respecting public opinion. Their simulations test various configurations of decision groups, varying in size and overlap between groups.

“In our simulations, we found that while no perfect structure is perfect, some governance models are obviously more effective than others.”

Surprisingly, the most effective governance emerges when decisions involve medium-sized groups, with overlapping memberships. These structures outperform direct democracy (everyone votes on everything) and central authority (in which few decide).

“Our physiological system constantly integrates signals and makes decisions to keep balanced. We apply similar logic to political structures,” Cohen explained.

The researchers found that this approach is particularly valuable when populations are polarized or inconsistent within individuals. In a simulation involving polarized communities, decision-making groups with fewer members overlapped, but significantly improved coherence without significantly sacrificing democratic satisfaction.

This networked governance model resembles emerging real-world practices where professional stakeholders and government representatives address specific policy challenges and share information from various sectors.

The findings suggest that certain types of complex decisions, especially those involving technical expertise or interconnection policies, may benefit from more distributed, networked decision-making processes rather than simple majority voting or performing tasks.

“Our findings highlight the value of decentralized, structured decisions,” Cohen notes. “The way these groups are organized and how they are connected can fundamentally shape the results.”

Although the computational model represents an early step, the researchers believe that their framework can ultimately provide practical improvements to organizational governance in environments ranging from companies to government agencies.

“Although challenges remain, our research shows that complex systems and modeling approaches to governance provide a strong perspective for understanding and improving the strong perspective of decentralized decision making,” Cohen said. “This could open the door to a more resilient, adaptive political system in the future.”

The researchers believe that their approach may be particularly valuable in addressing complex social challenges such as climate change, emerging technologies and public health crises – which requires technical expertise and a wide range of stakeholders’ participation.