IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v32y2022i4d10.1007_s12525-022-00594-4.html
   My bibliography  Save this article

Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions

Author

Listed:
  • René Riedl

    (University of Applied Sciences Upper Austria
    Johannes Kepler University Linz)

Abstract

Artificial intelligence (AI) refers to technologies which support the execution of tasks normally requiring human intelligence (e.g., visual perception, speech recognition, or decision-making). Examples for AI systems are chatbots, robots, or autonomous vehicles, all of which have become an important phenomenon in the economy and society. Determining which AI system to trust and which not to trust is critical, because such systems carry out tasks autonomously and influence human-decision making. This growing importance of trust in AI systems has paralleled another trend: the increasing understanding that user personality is related to trust, thereby affecting the acceptance and adoption of AI systems. We developed a framework of user personality and trust in AI systems which distinguishes universal personality traits (e.g., Big Five), specific personality traits (e.g., propensity to trust), general behavioral tendencies (e.g., trust in a specific AI system), and specific behaviors (e.g., adherence to the recommendation of an AI system in a decision-making context). Based on this framework, we reviewed the scientific literature. We analyzed N = 58 empirical studies published in various scientific disciplines and developed a “big picture” view, revealing significant relationships between personality traits and trust in AI systems. However, our review also shows several unexplored research areas. In particular, it was found that prescriptive knowledge about how to design trustworthy AI systems as a function of user personality lags far behind descriptive knowledge about the use and trust effects of AI systems. Based on these findings, we discuss possible directions for future research, including adaptive systems as focus of future design science research.

Suggested Citation

  • René Riedl, 2022. "Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2021-2051, December.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:4:d:10.1007_s12525-022-00594-4
    DOI: 10.1007/s12525-022-00594-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-022-00594-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12525-022-00594-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    2. Sutter, Matthias & Kocher, Martin G., 2007. "Trust and trustworthiness across different age groups," Games and Economic Behavior, Elsevier, vol. 59(2), pages 364-382, May.
    3. Scott Thiebes & Sebastian Lins & Ali Sunyaev, 2021. "Trustworthy artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 447-464, June.
    4. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    5. Gefen, David, 2000. "E-commerce: the role of familiarity and trust," Omega, Elsevier, vol. 28(6), pages 725-737, December.
    6. Maranda McBride & Lemuria Carter & Celestine Ntuen, 2012. "The impact of personality on nurses' bias towards automated decision aid acceptance," International Journal of Information Systems and Change Management, Inderscience Enterprises Ltd, vol. 6(2), pages 132-146.
    7. Geoff Walsham, 1995. "The Emergence of Interpretivism in IS Research," Information Systems Research, INFORMS, vol. 6(4), pages 376-394, December.
    8. Cornelia Sindermann & René Riedl & Christian Montag, 2020. "Investigating the Relationship between Personality and Technology Acceptance with a Focus on the Smartphone from a Gender Perspective: Results of an Exploratory Survey Study," Future Internet, MDPI, vol. 12(7), pages 1-17, June.
    9. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    10. Marc T. P. Adam & Henner Gimpel & Alexander Maedche & René Riedl, 2017. "Design Blueprint for Stress-Sensitive Adaptive Enterprise Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(4), pages 277-291, August.
    11. Bawack, Ransome Epie & Wamba, Samuel Fosso & Carillo, Kevin Daniel André, 2021. "Exploring the role of personality, trust, and privacy in customer experience performance during voice shopping: Evidence from SEM and fuzzy set qualitative comparative analysis," International Journal of Information Management, Elsevier, vol. 58(C).
    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. Roman Lukyanenko & Wolfgang Maass & Veda C. Storey, 2022. "Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1993-2020, December.

    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. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
    3. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.
    4. Issa Helmi & Lakkis Hussein & Dakroub Roy & Jaber Jad, 2023. "Examining User Engagement and Experience in Agritech," International Journal of Contemporary Management, Sciendo, vol. 59(2), pages 17-32, June.
    5. Niklas Kühl & Max Schemmer & Marc Goutier & Gerhard Satzger, 2022. "Artificial intelligence and machine learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2235-2244, December.
    6. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    7. Katharina Steininger & René Riedl & Friedrich Roithmayr & Peter Mertens, 2009. "Fads and Trends in Business and Information Systems Engineering and Information Systems Research – A Comparative Literature Analysis," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 1(6), pages 411-428, December.
    8. Julia Brasse & Hanna Rebecca Broder & Maximilian Förster & Mathias Klier & Irina Sigler, 2023. "Explainable artificial intelligence in information systems: A review of the status quo and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-30, December.
    9. Fabian Kosse & Thomas Deckers & Pia Pinger & Hannah Schildberg-Hörisch & Armin Falk, 2020. "The Formation of Prosociality: Causal Evidence on the Role of Social Environment," Journal of Political Economy, University of Chicago Press, vol. 128(2), pages 434-467.
    10. Ahmed Ibrahim Alzahrani & T. Ramayah & Nalini Suppiah & Osama Alfarraj & Nasser Alalwan, 2020. "Modeling Blog Usage From a Developing Country Perspective Using Structural Equation Modeling (SEM)," SAGE Open, , vol. 10(3), pages 21582440209, July.
    11. Hugh-Jones, David & Ooi, Jinnie, 2023. "Where do fairness preferences come from? Norm transmission in a teen friendship network," European Economic Review, Elsevier, vol. 157(C).
    12. Dumpe Maira, 2015. "Online Marketing Issues of Real Estate Companies: A Case of Latvia," Baltic Journal of Real Estate Economics and Construction Management, Sciendo, vol. 3(1), pages 130-139, December.
    13. Fehr, Ernst & Glätzle-Rützler, Daniela & Sutter, Matthias, 2013. "The development of egalitarianism, altruism, spite and parochialism in childhood and adolescence," European Economic Review, Elsevier, vol. 64(C), pages 369-383.
    14. Delina, Radoslav & Vajda, Viliam & Bednár, Peter, 2007. "Trusted operational scenarios - Trust building mechanisms and strategies for electronic marketplaces," MPRA Paper 20243, University Library of Munich, Germany.
    15. Vlad Rosca, 2015. "Customer attitudes towards buying e-books: Perspectives from a Romanian publishing house," Journal of Community Positive Practices, Catalactica NGO, issue 4, pages 105-111.
    16. Sembada, Agung Y. & Koay, Kian Yeik, 2021. "How perceived behavioral control affects trust to purchase in social media stores," Journal of Business Research, Elsevier, vol. 130(C), pages 574-582.
    17. Katharina Werner & Ahmed Skali, 2023. "Violent Conflict and Parochial Trust: Lab-in-the-Field and Survey Evidence," HiCN Working Papers 404, Households in Conflict Network.
    18. Michael Vössing & Niklas Kühl & Matteo Lind & Gerhard Satzger, 2022. "Designing Transparency for Effective Human-AI Collaboration," Information Systems Frontiers, Springer, vol. 24(3), pages 877-895, June.
    19. Gary Charness & Marie-Claire Villeval, 2009. "Cooperation and Competition in Intergenerational Experiments in the Field and the Laboratory," American Economic Review, American Economic Association, vol. 99(3), pages 956-978, June.
    20. Maik Hesse & Timm Teubner & Marc T. P. Adam, 2022. "In Stars We Trust – A Note on Reputation Portability Between Digital Platforms," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 349-358, June.

    More about this item

    Keywords

    Artificial Intelligence (AI); Big Five traits; Machine learning (ML); Personality; Review; Trust; Trust propensity;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    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:spr:elmark:v:32:y:2022:i:4:d:10.1007_s12525-022-00594-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.