110 | Neil Johnson on Complexity, Conflict, and Infodemiology
Aug 17, 2020
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Neil Johnson, a Professor of Physics at George Washington University, dives into the world of complexity and information networks. He explains how self-organization occurs in systems driven by individual agendas, revealing the unpredictable nature of these interactions. The discussion also highlights how misinformation spreads like an infectious disease, impacting society and democracy. Additionally, Johnson explores the dynamics of online extremism and the power laws that govern these phenomena, shedding light on how disparate ideologies can cluster within complex systems.
Complex systems exhibit emergent behavior and are characterized by power law behavior and interconnections between components.
The El Farol problem demonstrates how individual strategies in complex systems lead to crowd behavior and the importance of studying adaptive agents.
Power laws with fat tails extending to extreme values are commonly observed in complex systems, and understanding them can inform strategies for addressing issues like the growth of extremist groups.
Deep dives
Defining features of complex systems
Complex systems are different from complicated systems in that they have many moving parts and exhibit emergent behavior. Complexity is characterized by power law behavior and the interconnections between components. The dynamics of complex systems can lead to surprising and unexpected outcomes, such as traffic jams or stock market crashes.
The El Farol problem
The El Farol problem is a famous example in complexity that highlights how individual strategies interact and lead to crowd behavior. In the El Farol bar scenario, people must decide whether to go to a bar with limited seats, and their decisions depend on previous outcomes and the actions of others. The dynamics of this simple problem reveal clustering and fragmentation phenomena, with the emergence of two groups or crowds of people following opposite strategies. This highlights the importance of studying adaptive agents and their behavior in complex systems.
Power laws and their significance
Power laws are distributions commonly observed in complex systems. Unlike bell curves, power laws have fat tails that extend to extreme values, indicating the presence of highly unequal outcomes. Power laws with a slope of 2.5 are often observed in various systems, such as wealth distribution or the growth of extremist communities online. Understanding power laws can inform strategies for addressing complex issues, such as mitigating the buildup of extremist groups by targeting the smaller clusters that contribute to their growth.
Power laws and scale-free behavior in complex systems
Power laws and scale-free behavior are fundamental concepts in physics, particularly in the study of phenomena like earthquakes and forest fires. These systems exhibit a distribution of events where the behavior at one scale is similar to that at a different scale, indicating scale invariance. This scale-free behavior has important implications in understanding and predicting the occurrence of large-scale events such as dangerous earthquakes. It suggests that the same underlying principles and theories can be applied across different scales, highlighting the interconnectedness and universality of natural phenomena.
Understanding power law distributions in wars and terrorism
Analyzing casualty data in wars and terrorist attacks reveals a surprising pattern: a power law distribution of the number of casualties per event. This means that there are many events with few casualties and a few events with a large number of casualties. Moreover, this power law distribution is consistent across different wars and conflicts, suggesting a common mechanism underlying the dynamics of violence. By studying the clustering behavior of attackers and the formation of insurgent groups, researchers have found that these power laws emerge from the way individuals coalesce and fragment within these groups. Understanding these power law distributions can have significant implications for predicting and managing conflicts and terrorism.
Physicists have traditionally simplified systems as much as possible, in order to shed light on fundamental properties. But small, simple parts build up into large, complex wholes. Are there new rules and laws of nature that apply specifically to the realm of complexity? This has been a popular question for a few decades now, and we have some answers but not as many as we would like. Neil Johnson is an expert on complex systems generally, and information networks in particular. We discuss how self-organization can arise from individual units following their own agendas, and how we can mathematically characterize such behavior. Then we talk about information networks in the modern world, including how they have been used to spread disinformation and find recruits for radical fringe groups.
Neil Johnson received his Ph.D. in physics from Harvard University. He is currently professor of physics at George Washington University, where he heads an initiative in Complexity and Data Science. In 1999 he presented the annual Christmas Lectures at the Royal Institution in London. He was the recipient of the Burton Award from the American Physical Society in 2018. Among his books are the textbook Financial Market Complexity and the trade book Simply Complexity.
