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Outcome context-dependence is not WEIRD: Comparing reinforcement- and description-based economic preferences
Hernán Anlló1,2,3, Sophie Bavard1,3,4, FatimaZzahra Benmarrakchi3,5
1Human Reinforcement Learning Team, Laboratory of Cognitive and Computational Neuroscience, ENS-PSL, Paris, France.
Abstract:
Recent evidence indicates that reward value encoding in humans is highly context-dependent, leading to suboptimal decisions in some cases. But whether this computational constraint on valuation is a shared feature of human cognition remains unknown. To address this question, we studied the behavior of individuals from across 11 countries of markedly different socioeconomic and cultural makeup using an experimental approach that reliably captures context effects in reinforcement learning. Our findings show that all samples presented evidence of similar sensitivity to context. Crucially, suboptimal decisions generated by context manipulation were not explained by risk aversion, as estimated through a separate description-based choice task (i.e., lotteries) consisting of matched decision offers. Conversely, risk aversion significantly differed across countries. Overall, our findings suggest that context-dependent reward value encoding is a hardcoded feature of human cognition, while description-based decision-making is significantly sensitive to cultural factors.
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