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Humans exhibit irrational decision-making patterns in response toenvironmental triggers, such as experiencing an economic loss or gain. In thispaper we investigate whether algorithms exhibit the same behavior by examiningthe observed decisions and latent risk and rationality parameters estimated bya random utility model with constant relative risk-aversion utility function.We use a dataset consisting of 10,000 hands of poker played by Pluribus, thefirst algorithm in the world to beat professional human players and find (1)Pluribus does shift its playing style in response to economic losses and gains,ceteris paribus; (2) Pluribus becomes more risk-averse and rational following atrigger but the humans become more risk-seeking and irrational; (3) thedifference in playing styles between Pluribus and the humans on the dimensionsof risk-aversion and rationality are particularly differentiable when both haveexperienced a trigger. This provides support that decision-making patternscould be used as "behavioral signatures" to identify human versus algorithmicdecision-makers in unlabeled contexts.

Rational AI: A comparison of human and AI responses to triggers of economic irrationality in poker