The effect of gender stereotypes on artificial intelligence recommendations

Jungyong Ahn, Jungwon Kim and Yongjun Sung

Journal of Business Research, 2022, vol. 141, issue C, 50-59

Abstract: This study explores the effects of gender stereotypes on evaluating artificial intelligence (AI) recommendations. We predict that gender stereotypes will affect human-AI interactions, resulting in somewhat different persuasive effects of AI recommendations for utilitarian vs. hedonic products. We found that participants in the male AI agent condition gave higher competence scores than in the female AI agent condition. Contrariwise, perceived warmth was higher in the female AI agent condition than in the male condition. More importantly, a significant interaction effect between AI gender and product type was found, suggesting that participants showed more positive attitudes toward the AI recommendations when the male AI recommended a utilitarian (vs. hedonic) product. Conversely, a hedonic product was evaluated more positively when advised by the female (vs. male) AI agent.

Keywords: Artificial Intelligence (AI); AI agent; Gender stereotypes; AI recommendations (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:141:y:2022:i:c:p:50-59

DOI: 10.1016/j.jbusres.2021.12.007

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