IDEAS home Printed from https://ideas.repec.org/a/gam/jscscx/v13y2024i5p251-d1389024.html
   My bibliography  Save this article

Exploring Motivators for Trust in the Dichotomy of Human—AI Trust Dynamics

Author

Listed:
  • Michael Gerlich

    (Center for Strategic Corporate Foresight and Sustainability, SBS Swiss Business School, 8302 Kloten, Switzerland)

Abstract

This study analyses the dimensions of trust in artificial intelligence (AI), focusing on why a significant portion of the UK population demonstrates a higher level of trust in AI compared to humans. Conducted through a mixed-methods approach, this study gathered 894 responses, with 451 meeting the criteria for analysis. It utilised a combination of a six-step Likert-scale survey and open-ended questions to explore the psychological, sociocultural, and technological facets of trust. The analysis was underpinned by structural equation modelling (SEM) and correlation techniques. The results unveil a strong predilection for trusting AI, mainly due to its perceived impartiality and accuracy, which participants likened to conventional computing systems. This preference starkly contrasts with the scepticism towards human reliability, which is influenced by the perception of inherent self-interest and dishonesty in humans, further exacerbated by a general distrust in media narratives. Additionally, this study highlights a significant correlation between distrust in AI and an unwavering confidence in human judgment, illustrating a dichotomy in trust orientations. This investigation illuminates the complex dynamics of trust in the era of digital technology, making a significant contribution to the ongoing discourse on AI’s societal integration and underscoring vital considerations for future AI development and policymaking.

Suggested Citation

  • Michael Gerlich, 2024. "Exploring Motivators for Trust in the Dichotomy of Human—AI Trust Dynamics," Social Sciences, MDPI, vol. 13(5), pages 1-20, May.
    • Handle: RePEc:gam:jscscx:v:13:y:2024:i:5:p:251-:d:1389024
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2076-0760/13/5/251/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2076-0760/13/5/251/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nuno Ligeiro & Ivo Dias & Ana Moreira, 2024. "Recruitment and Selection Process Using Artificial Intelligence: How Do Candidates React?," Administrative Sciences, MDPI, vol. 14(7), pages 1-17, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    2. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    3. Latinovic, Zoran & Chatterjee, Sharmila C., 2022. "Achieving the promise of AI and ML in delivering economic and relational customer value in B2B," Journal of Business Research, Elsevier, vol. 144(C), pages 966-974.
    4. Shengliang Zhang & Chaoying Huang & Xiaodong Li & Ai Ren, 2022. "Understanding Impacts of Service Robots with the Revised Gap Model," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    5. Teck Ming Tan & Saila Saraniemi, 2023. "Trust in blockchain-enabled exchanges: Future directions in blockchain marketing," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 914-939, July.
    6. Cambra-Fierro, Jesús & Polo-Redondo, Yolanda & Trifu, Andreea, 2021. "Short-term and long-term effects of touchpoints on customer perceptions," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    7. Ayat Sami ODEIBAT, 2021. "The Effect Of Technology Evolution On The Future Of Jobs," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 17, pages 57-67, June.
    8. Poushneh, Atieh, 2021. "Impact of auditory sense on trust and brand affect through auditory social interaction and control," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    9. Mandler, Timo & Sezen, Burcu & Chen, Jieke & Özsomer, Ayşegül, 2021. "Performance consequences of marketing standardization/adaptation: A systematic literature review and future research agenda," Journal of Business Research, Elsevier, vol. 125(C), pages 416-435.
    10. Chunlin Yuan & Shuman Wang & Yue Liu, 2023. "AI service impacts on brand image and customer equity: empirical evidence from China," Journal of Brand Management, Palgrave Macmillan, vol. 30(1), pages 61-76, January.
    11. Yihua Wu & Muhammad Farrukh & Ali Raza & Fanchen Meng & Imtiaz Alam, 2021. "Framing the evolution of the corporate social responsibility and environmental management journal," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(4), pages 1397-1411, July.
    12. Laith T. Khrais, 2020. "Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce," Future Internet, MDPI, vol. 12(12), pages 1-14, December.
    13. Ertugrul Uysal & Sascha Alavi & Valéry Bezençon, 2022. "Trojan horse or useful helper? A relationship perspective on artificial intelligence assistants with humanlike features," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1153-1175, November.
    14. Lee, Kuo-Wei & Li, Chia-Ying, 2023. "It is not merely a chat: Transforming chatbot affordances into dual identification and loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    15. Li, Chia-Ying & Zhang, Jin-Ting, 2023. "Chatbots or me? Consumers’ switching between human agents and conversational agents," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    16. Jana Holthöwer & Jenny Doorn, 2023. "Robots do not judge: service robots can alleviate embarrassment in service encounters," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 767-784, July.
    17. Abhijit Guha & Dhruv Grewal, 2022. "How robots will affect the future of retailing," AMS Review, Springer;Academy of Marketing Science, vol. 12(3), pages 245-252, December.
    18. Chen, Nuoya & Mohanty, Smaraki & Jiao, Jinfeng & Fan, Xiucheng, 2021. "To err is human: Tolerate humans instead of machines in service failure," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    19. Roggeveen, Anne L. & Grewal, Dhruv & Karsberg, John & Noble, Stephanie M. & Nordfält, Jens & Patrick, Vanessa M. & Schweiger, Elisa & Soysal, Gonca & Dillard, Annemarie & Cooper, Nora & Olson, Richard, 2021. "Forging meaningful consumer-brand relationships through creative merchandise offerings and innovative merchandising strategies," Journal of Retailing, Elsevier, vol. 97(1), pages 81-98.
    20. Ding, Bin & Li, Yameng & Miah, Shah & Liu, Wei, 2024. "Customer acceptance of frontline social robots—Human-robot interaction as boundary condition," Technological Forecasting and Social Change, Elsevier, vol. 199(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jscscx:v:13:y:2024:i:5:p:251-:d:1389024. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.