Borau, Sylvie, Otterbring, Tobias, Laporte, Sandra and Fosso Wamba, Samuel (2021) The most human bot: Female gendering increases humanness perceptions of bots and acceptance of AI. Psychology and Marketing, vol.38 (n°7). pp. 1052-1068.

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Identification Number : 10.1002/mar.21480

Abstract

Companies have repeatedly launched Artificial Intelligence (AI) products such as intelligent chatbots and robots with female names, voices, and bodies. Previous research posits that people intuitively favor female over male bots, mainly because female bots are judged as warmer and more likely to experience emotions. We present five online studies, including four preregistered, with a total sample of over 3,000 participants that go beyond this longstanding perception of femininity. Because warmth and experience (but not competence) are seen as fundamental qualities to be a full human but are lacking in machines, we argue that people prefer female bots because they are perceived as more human than male bots. Using implicit, subtle, and blatant scales of humanness, our results consistently show that women (Studies 1A and 1B), female bots (Studies 2 and 3), and female chatbots (Study 4) are perceived as more human than their male counterparts when compared with non-human entities (animals and machines). Study 4 investigates explicitly the acceptance of gendered algorithms operated by AI chatbots in a health context. We found that the female chatbot is preferred over the male chatbot because it is perceived as more human and more likely to consider our unique needs. These results highlight the ethical quandary faced by AI designers and policymakers: Women are said to be transformed into objects in AI, but injecting women's humanity into AI objects makes these objects seem more human and acceptable.

Item Type: Article
Language: English
Date: July 2021
Refereed: Yes
Place of Publication: Hoboken
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSM Research (Toulouse)
Site: UT1
Date Deposited: 15 Jun 2021 08:58
Last Modified: 21 Apr 2022 09:05
OAI Identifier: oai:tse-fr.eu:125694
URI: https://publications.ut-capitole.fr/id/eprint/43613
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