Can mathematics and probability explain and predict human behavior, or are humans too complex and irrational? This question has been a topic of interest for researchers who aim to understand and predict human actions.
One example that highlights the unpredictability of human behavior is the rush on toilet paper during the COVID-19 pandemic. This unexpected behavior left supermarket shelves empty in many countries. However, by combining mathematics, economics, and behavioral science, researchers were able to create mathematical models that explained the panic buying of toilet paper.
In a recent study published in the Journal of the Royal Society Interface, researchers took a similar approach to understanding the spread of disease. They found that human reactions to the spread of disease can be just as important as the behavior of the disease itself in determining how an outbreak develops.
Context plays a significant role in shaping human behavior. For instance, the popular TV game show Deal or No Deal demonstrates how context can influence decision-making. Contestants often turn down offers of free money in the hopes of getting a larger sum later, despite rational calculations suggesting they should accept the offer. This behavior cannot be predicted solely through mathematics.
Behavioral science offers insights into what drives people to take specific actions. It suggests that setting realistic goals and creating powerful motivational contexts can lead to more reasonable behavior. However, even individuals with clear goals can be influenced by emotion and context, leading them to make irrational choices.
Researchers have found ways to understand the behavior of Deal or No Deal contestants by combining ideas from mathematics, economics, and the study of risky choices. They discovered that contestants’ decisions are “path-dependent,” meaning their choice to accept a bank offer depends not only on their goal and the odds but also on the choices they have already made.
Understanding group behaviors is crucial when studying the spread of disease. Social psychology reveals that group behaviors and attitudes can influence individual actions. By combining mathematics and behavioral science, researchers can better predict group behaviors.
During the COVID-19 pandemic, some mass behaviors, such as panic-buying toilet paper, were highly visible, while others, like individuals limiting their own movement, were not. Taking into account feedback loops, where fear and perceived risk drive self-preservation behaviors, is crucial in understanding the spread of disease. Many mathematical models have failed to consider this feedback loop.
The researchers’ new study combines population disease spread modeling with mass behavior modeling to understand the links between behavior and infection. This framework allows for the consideration of dynamic and self-driven protective health behaviors in the presence of an infectious disease. It provides valuable insights for making informed choices and policy recommendations for future epidemics.
To better understand human behavior from a mathematical perspective, more data on human choices during infectious diseases is needed. This data can help identify patterns that can be used for prediction.
In conclusion, predicting human behavior is a complex task that depends on various factors such as emotion, context, risk perception, social observation, fear, and excitement. Mathematics can be a powerful tool in describing and predicting patterns of behavior, but it requires interdisciplinary teams to address global challenges that require changes in human behavior at scale.
