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EMAC 2024 Annual


Human for Exploration, AI for Exploitation
(A2024-119906)

Published: May 28, 2024

AUTHORS

Hao Zhang, HEC Paris; Anne-Sophie Chaxel, HEC Paris

ABSTRACT

Decision-makers in various domains face a tradeoff between exploring the unknown in search of better options (exploration) and optimizing based on current knowledge (exploitation). This research investigates how consumers’ exploration-exploitation tradeoff impact their adoption of AI. From three experiments, we found that consumers are less willing to rely on AI for exploration (as opposed to exploitation), and that the effect is mediated by the relative importance of creativity and reliability in giving recommendations that align with exploration or exploitation goals.