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The most human bot: Female gendering increases humanness perceptions of bots and acceptance of AI

Author

Listed:
  • Sylvie Borau

    (TBS - Toulouse Business School)

  • Tobias Otterbring

    (UIA - University of Agder, Institute of Retail Economics)

  • Sandra Laporte

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Samuel Fosso Wamba

    (TBS - Toulouse Business School)

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.

Suggested Citation

  • Sylvie Borau & Tobias Otterbring & Sandra Laporte & Samuel Fosso Wamba, 2021. "The most human bot: Female gendering increases humanness perceptions of bots and acceptance of AI," Post-Print hal-03648092, HAL.
  • Handle: RePEc:hal:journl:hal-03648092
    DOI: 10.1002/mar.21480
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    Citations

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    Cited by:

    1. Tao Zhang & Chao Feng & Hui Chen & Junjie Xian, 2022. "Calming the customers by AI: Investigating the role of chatbot acting-cute strategies in soothing negative customer emotions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2277-2292, December.
    2. Borghi, Matteo & Mariani, Marcello M., 2022. "The role of emotions in the consumer meaning-making of interactions with social robots," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    3. Pei-Fang Hsu & Tuan (Kellan) Nguyen & Chen-Ya Wang & Pei-Ju Huang, 2023. "Chatbot commerce—How contextual factors affect Chatbot effectiveness," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    4. Hu, Hai-hua & Ma, Fang, 2023. "Human-like bots are not humans: The weakness of sensory language for virtual streamers in livestream commerce," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    5. Yang, Nanyin & Palma, Marco & Drichoutis, Andreas C., 2023. "Humanization of Virtual Assistants and Delegation Choices," MPRA Paper 119275, University Library of Munich, Germany.
    6. Shengxing Yang, 2022. "A systematic literature review on the disruptions of artificial intelligence within the business world: in terms of the evolution of competences [Une revue systématique de la littérature sur les bo," Post-Print hal-03694170, HAL.
    7. Jan, Ihsan Ullah & Ji, Seonggoo & Kim, Changju, 2023. "What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    8. Kim, Jungkeun & Kim, Jeong Hyun & Kim, Changju & Park, Jooyoung, 2023. "Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    9. Darius-Aurel Frank & Christian T Elbæk & Caroline Kjær Børsting & Panagiotis Mitkidis & Tobias Otterbring & Sylvie Borau, 2021. "Drivers and social implications of Artificial Intelligence adoption in healthcare during the COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-11, November.
    10. Ali, Nimra & Sheeraz, Muhammad, 2023. "How do I look: The role of Brand Anthropomorphism and Implicit Self-Theories on Brand Evaluations?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1), pages 51-70.
    11. Mark Anthony Camilleri & Ciro Troise, 2023. "Live support by chatbots with artificial intelligence: A future research agenda," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 61-80, March.
    12. Shailendra Kumar & Sanghamitra Choudhury, 2022. "Gender and feminist considerations in artificial intelligence from a developing-world perspective, with India as a case study," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    13. Liu, Yun & Wang, Xingyuan & Wang, Shuyang, 2022. "Research on service robot adoption under different service scenarios," Technology in Society, Elsevier, vol. 68(C).
    14. Frank, Darius-Aurel & Otterbring, Tobias, 2023. "Being seen… by human or machine? Acknowledgment effects on customer responses differ between human and robotic service workers," Technological Forecasting and Social Change, Elsevier, vol. 189(C).

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