The podcast explores the mathematical perspective of war and conflict, analyzing casualty numbers and patterns in wars. It discusses the feedback process of height and its potential impact on extreme heights. The concept of all wars being a collection of battles is challenged, highlighting the importance of understanding the underlying mechanism of casualties. The relationship between border length and wars is explored through the study of insurgencies and data collection within conflicts.
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Quick takeaways
Large wars are scaled-up versions of smaller ones, revealing collective behavior and feedback mechanisms in conflicts.
Power laws play a crucial role in understanding human conflict, challenging conventional notions of averages and predictions.
Deep dives
Understanding the Complexity of Human Conflict
Human conflict is a complex system with diverse reasons and terrains. While there is great diversity in why people fight and where wars take place, a complex systems view reveals common themes. Professor Neil Johnson explores human conflict in different eras, starting with the pre-internet era. He discusses Lewis Fry Richardson, a scientist who collected casualties data during World War I and uncovered patterns. Richardson found a power law distribution with a slope of 1.8, indicating that large wars are scaled-up versions of smaller ones. This power law reveals the collective behavior and feedback mechanisms that contribute to the unpredictability and fat-tailed nature of conflicts.
The Impact of Power Laws in Human Conflict
Power laws play a crucial role in understanding human conflict. The prevalence of power laws in complex systems suggests that most systems follow this pattern. Unlike traditional averages, power laws are characterized by fat-tailed distributions, where extremely large events have a non-zero probability. The study of human conflicts shows that the mean number of casualties can be predicted, but the probability of larger-scale conflicts with significantly more casualties is lower. Understanding the mechanisms behind power laws in conflicts helps explain the collective behavior and interactions that lead to varying levels of violence.
Rethinking Average and Predictions in Human Conflict
The understanding of power laws in human conflict challenges conventional notions of averages and predictions. Unlike systems like heights or pensions that adhere to normal distributions, conflicts exhibit a long tail of extreme events. This means that predicting the average casualties in conflict based on past data becomes unreliable. Instead, the focus should be on understanding the mechanisms that generate power laws, which represent the collective behavior and feedback processes in conflicts. By uncovering these mechanisms, interventions and policies can be developed to potentially mitigate the impact of conflicts.
When we think of what caused a certain number of people to die in a specific war, we tend to think about a number of factors. for example, the terrain or political drivers. But what if the number of deaths that occur in a war is actually dictated by something far less obvious?
Neil Johnson, Professor of Physics and Head of the Dynamic Online Networks Lab at George Washington University, has returned to explain how studying the casualties of war can give us a greater understanding of the causes of war.