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Artificial intelligence vs. public administrators: Public trust, efficiency, and tolerance for errors

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  • Bao, Haixu
  • Liu, Wenfei
  • Dai, Zheng

Abstract

This study develops and empirically examines an integrative systems framework of public trust in artificial intelligence (AI) in the public sector, grounded in Luhmann's theory of systemic trust. Through a methodologically rigorous survey experiment, we manipulated administrator/AI capabilities across computational-audit and conversational-advisory scenarios to investigate context-dependent trust dynamics. Findings reveal significant variation in public trust across usage contexts, with respondents demonstrating higher trust in AI for computational tasks, while preferring human administrators for conversational settings. Notably, our results challenge conventional assumptions about AI trust fragility, as evidence of AI mistakes did not engender disproportionate distrust relative to naturally imperfect humans. The study further demonstrates that improved efficiency can mitigate context-specific distrust stemming from AI errors in computational scenarios, though this effect was not observed in conversational contexts. By elucidating these nuanced, context-dependent dynamics of public trust towards algorithmic governance, this research contributes to both theoretical understanding and practical implementation. It provides policymakers with targeted, evidence-based guidance for cultivating appropriate trust when embedding AI technologies in the public sector through context-sensitive design approaches and governance practices. Future research should explore contingent formulations of public trust and its evolution across AI system lifecycles within diverse cultural and institutional environments.

Suggested Citation

  • Bao, Haixu & Liu, Wenfei & Dai, Zheng, 2025. "Artificial intelligence vs. public administrators: Public trust, efficiency, and tolerance for errors," Technological Forecasting and Social Change, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:tefoso:v:215:y:2025:i:c:s0040162525001337
    DOI: 10.1016/j.techfore.2025.124102
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    1. Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K, 2019. "Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda," International Journal of Information Management, Elsevier, vol. 48(C), pages 63-71.
    2. Diana C. Mutz & Robin Pemantle & Philip Pham, 2019. "The Perils of Balance Testing in Experimental Design: Messy Analyses of Clean Data," The American Statistician, Taylor & Francis Journals, vol. 73(1), pages 32-42, January.
    3. Omrani, Nessrine & Rivieccio, Giorgia & Fiore, Ugo & Schiavone, Francesco & Agreda, Sergio Garcia, 2022. "To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    4. 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.
    5. Dagmara Lewicka & Agnieszka Freda Zakrzewska-Bielawska, 2022. "Trust and distrust in interorganisational relations—Scale development," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-28, December.
    6. Sako, Mari & Helper, Susan, 1998. "Determinants of trust in supplier relations: Evidence from the automotive industry in Japan and the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 34(3), pages 387-417, March.
    7. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    8. Chin, Tachia & Li, Qi & Mirone, Francesco & Papa, Armando, 2025. "Conflicting impacts of shadow AI usage on knowledge leakage in metaverse-based business models: A Yin-Yang paradox framing," Technology in Society, Elsevier, vol. 81(C).
    9. Gaines, Brian J. & Kuklinski, James H. & Quirk, Paul J., 2007. "The Logic of the Survey Experiment Reexamined," Political Analysis, Cambridge University Press, vol. 15(1), pages 1-20, January.
    10. Grinin, Leonid & Grinin, Anton & Korotayev, Andrey, 2022. "COVID-19 pandemic as a trigger for the acceleration of the cybernetic revolution, transition from e-government to e-state, and change in social relations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    11. Frens Kroeger, 2019. "Unlocking the treasure trove: How can Luhmann’s theory of trust enrich trust research?," Journal of Trust Research, Taylor & Francis Journals, vol. 9(1), pages 110-124, January.
    12. Shin-Cheng Yeh & Ai-Wei Wu & Hui-Ching Yu & Homer C. Wu & Yi-Ping Kuo & Pei-Xuan Chen, 2021. "Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-34, August.
    13. Lingling Gao & Kerem Aksel Waechter, 2017. "Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation," Information Systems Frontiers, Springer, vol. 19(3), pages 525-548, June.
    14. Anton Korinek & Joseph E. Stiglitz, 2018. "Artificial Intelligence and Its Implications for Income Distribution and Unemployment," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 349-390, National Bureau of Economic Research, Inc.
    15. Richard Williams, 2006. "Generalized ordered logit/partial proportional odds models for ordinal dependent variables," Stata Journal, StataCorp LLC, vol. 6(1), pages 58-82, March.
    16. Yong Qin & Zeshui Xu & Xinxin Wang & Marinko Skare, 2024. "Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1736-1770, March.
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