American researchers have developed a mathematical model to gain a better understanding of how people make decisions, such as selecting a president in an election. The study, published on August 12 in the journal Physical Review E, focuses on the decision-making process involving various biases.
Using mathematical tools, scientists created models to simulate the process of discussing and reaching decisions in groups. They discovered that individuals with strong initial biases tend to make decisions much faster than those who approach the issue more rationally. Biased participants in the study were found to make choices even when facts pointed to a different, more optimal option.
The researchers’ model vividly illustrates how bias impacts the speed of decision-making. During the experiment, “agents” – mathematical representations of individuals – received information comparable to filling a bucket with water. Depending on the scenario, this information either favored one option (e.g., choosing pizza for dinner) or favored the opposite (e.g., selecting Thai food). When the “bucket” filled quickly, the agent made a decision without considering all the evidence.
The study revealed that those with the strongest biases were the quickest to make decisions, despite conflicting evidence. Conversely, participants with fewer biases took more time to analyze information and ultimately made more rational choices.
Though the study’s model lacks interactions between agents, which are crucial in real-life decision-making processes, researchers intend to conduct further experiments to examine how group dynamics can alter the decision-making process.
The findings of this research could prove valuable not only to political analysts but also to organizations that rely on group decisions through voting or polls.