AI Uncovers Irrationality in Human Decision-Making During Complex Games

Researchers from Princeton University and Boston University used machine learning to predict human strategic decisions in various games. A deep neural network trained on human decisions accurately predicted players' choices. A hybrid model, combining a classical behavioral model with a neural network, outperformed the neural network alone, particularly in capturing the impact of game complexity. The study reveals that people act more predictably in simpler games but less rationally in complex ones. This research offers new insights into human decision-making processes and lays the groundwork for behavioral science interventions aimed at promoting more rational choices.