Public Trust in Automated Decision Systems
Keywords:
public trust, automated decisions, procedural fairness, accountability, institutionsAbstract
This interdisciplinary review examines public trust in automated decision systems. The organizing question is how competence, procedural fairness, transparency, recourse, and institutional legitimacy shape warranted trust. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to treating acceptance or adoption as equivalent to justified trust. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in public-sector and socially consequential automation.
References
- Araujo, T., Helberger, N., Kruikemeier, S., & Vreese, C. H. D. (2020). In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI & Society, 35(3), 611-623. https://doi.org/10.1007/s00146-019-00931-w
- Azevedo-Sa, H., Jayaraman, S. K., Esterwood, C. T., Yang, X. J., Robert, L. P., & Tilbury, D. M. (2020). Real-Time Estimation of Drivers’ Trust in Automated Driving Systems. International Journal of Social Robotics, 13(8), 1911-1927. https://doi.org/10.1007/s12369-020-00694-1
- Engin, Z., & Treleaven, P. (2018). Algorithmic Government: Automating Public Services and Supporting Civil Servants in using Data Science Technologies. The Computer Journal, 62(3), 448-460. https://doi.org/10.1093/comjnl/bxy082
- Kuziemski, M., & Misuraca, G. (2020). AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings. Telecommunications Policy, 44(6), 101976. https://doi.org/10.1016/j.telpol.2020.101976
- Kyriakidis, M., Happee, R., & Winter, J. C. F. D. (2015). Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transportation Research Part F Traffic Psychology and Behaviour, 32, 127-140. https://doi.org/10.1016/j.trf.2015.04.014
- Licht, K. D. F., & Licht, J. D. F. (2020). Artificial intelligence, transparency, and public decision-making. AI & Society, 35(4), 917-926. https://doi.org/10.1007/s00146-020-00960-w
- Lăzăroiu, G., Neguriţă, O., Grecu, I., Grecu, G., & Mitran, P. C. (2020). Consumers’ Decision-Making Process on Social Commerce Platforms: Online Trust, Perceived Risk, and Purchase Intentions. Frontiers in Psychology, 11, 890. https://doi.org/10.3389/fpsyg.2020.00890
- Robinson, S. C. (2020). Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI). Technology in Society, 63, 101421. https://doi.org/10.1016/j.techsoc.2020.101421
- Ryan, M. (2020). In AI We Trust: Ethics, Artificial Intelligence, and Reliability. Science and Engineering Ethics, 26(5), 2749-2767. https://doi.org/10.1007/s11948-020-00228-y
- Winfield, A. F. T., & Jirotka, M. (2018). Ethical governance is essential to building trust in robotics and artificial intelligence systems. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, 376(2133), 20180085. https://doi.org/10.1098/rsta.2018.0085
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Convergence in Science and Society

This work is licensed under a Creative Commons Attribution 4.0 International License.