Foraging in a non-foraging task: Fitness maximization explains human risk preference dynamics under changing environment

Yasuhiro Mochizuki, Norihiro Harasawa, Mayank Aggarwal, Chong Chen and Haruaki Fukuda

PLOS Computational Biology, 2024, vol. 20, issue 5, 1-34

Abstract: Changes in risk preference have been reported when making a series of independent risky choices or non-foraging economic decisions. Behavioral economics has put forward various explanations for specific changes in risk preference in non-foraging tasks, but a consensus regarding the general principle underlying these effects has not been reached. In contrast, recent studies have investigated human economic risky choices using tasks adapted from foraging theory, which require consideration of past choices and future opportunities to make optimal decisions. In these foraging tasks, human economic risky choices are explained by the ethological principle of fitness maximization, which naturally leads to dynamic risk preference. Here, we conducted two online experiments to investigate whether the principle of fitness maximization can explain risk preference dynamics in a non-foraging task. Participants were asked to make a series of independent risky economic decisions while the environmental richness changed. We found that participants’ risk preferences were influenced by the current and past environments, making them more risk-averse during and after the rich environment compared to the poor environment. These changes in risk preference align with fitness maximization. Our findings suggest that the ethological principle of fitness maximization might serve as a generalizable principle for explaining dynamic preferences, including risk preference, in human economic decision-making.Author summary: Decision-making involving probabilistic outcomes (i.e., under risk) is an integral part of our daily lives. Empirical studies have shown that risky behavior often deviates from standard economic theory, and peoples’ risk preferences change depending on their psychological and physiological states, and the context of the decision. While previous studies have developed empirical mathematical models to provide mechanistic explanations of these effects, there is no unifying principle that explains why human risky decision-making is tuned this way. Here, we document one such context effect and suggest that this effect can be explained by the ethological principle of fitness maximization. In our study, participants made sequential independent risky decisions in different environments. We found that rich environments in which it was easy to get large rewards increased participants’ risk-aversiveness both during and after experiencing them, and experiencing poor environments increased risk taking behavior. The foregoing modulations of risk-aversiveness are predicted if participants make decisions to satisfy some internal threshold for minimum reward gain, akin to reaching a minimum threshold for survival, rather than to maximize reward gain. Our results suggest that a better understanding of human economic behavior may be achieved under the principle of fitness maximization.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1012080

DOI: 10.1371/journal.pcbi.1012080

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