Citizen Trust in AI-Based Public Services: The Mediating Role of Transparency and Accountability

Farzana Akter; Ahsan Kabir

doi:10.37899/mjdpp.v3i3.411

Authors

Farzana Akter Department of Public Administration, University of Dhaka, Dhaka, Bangladesh
Ahsan Kabir Department of Public Administration, University of Dhaka, Dhaka, Bangladesh

DOI:

https://doi.org/10.37899/mjdpp.v3i3.411

Keywords:

Accountability, Artificial Intelligence, Citizen Trust, Digital Government, Public Administration

Abstract

The rapid adoption of artificial intelligence in public administration has transformed the delivery of government services while raising concerns regarding transparency, accountability, and citizen trust. This study examines the influence of AI-based public services on citizen trust by investigating the mediating roles of transparency and accountability. A quantitative cross-sectional survey design was employed using simulated data from 420 respondents, and the proposed relationships were analyzed through Partial Least Squares Structural Equation Modeling. The findings reveal that AI-based public services significantly enhance transparency, accountability, and citizen trust. Transparency demonstrates the strongest mediating effect, indicating that explainable and open AI systems are essential for strengthening public confidence in digital government services. Accountability also plays a significant role by ensuring institutional responsibility and procedural fairness. The study contributes to the growing literature on AI governance by proposing an integrated framework linking governance mechanisms with citizen trust. The findings provide practical insights for policymakers seeking to develop transparent, accountable, and citizen-centered AI-enabled public services that support sustainable digital government transformation.

References

Agrawal, G. (2024). Accountability, trust, and transparency in AI systems from the perspective of public policy: Elevating ethical standards. In AI healthcare applications and security, ethical, and legal considerations (pp. 148-162). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-7452-8.ch009

Ahmed, S. S. (2025). Algorithmic Discrimination and the Law: Regulating Bias in AI Decision-Making. Pakistan Journal of Humanities & Social Sciences. https://doi.org/10.52131/pjhss.2025.v13i4.3086

Al-Dulaimi, A. O. M., & Mohammed, M. A. A. W. (2026). Legal responsibility for errors caused by artificial intelligence (AI) in the public sector. International Journal of Law and Management, 68(4), 695-722. https://doi.org/10.1108/IJLMA-08-2024-0295

Ali, H. (2026). Digital Transformation in Public Administration: Enhancing Efficiency, Transparency, and Service Delivery. Research Consortium Archive, 4(2), 1460-1476. https://doi.org/10.5281/zenodo.20827926

Androutsopoulou, M., Carayannis, E. G., Askounis, D., & Zotas, N. (2025). Towards AI-enabled cyber-physical infrastructures—challenges, opportunities, and implications for a data-driven egovernment theory, policy, and practice. Journal of the Knowledge Economy, 1-38. https://doi.org/10.1007/s13132-025-02726-5

Aoki, N., Tatsumi, T., Naruse, G., & Maeda, K. (2024). Explainable AI for government: Does the type of explanation matter to the accuracy, fairness, and trustworthiness of an algorithmic decision as perceived by those who are affected? Government Information Quarterly, 41(4), 101965. https://doi.org/10.1016/j.giq.2024.101965

Bansal, D., & Bose, S. K. (2026). Governing the digital age: Ethical principles, transparency, accountability, and human oversight in information technology law toward a sustainable regulatory framework. International Journal of Business and Management (IJBM), 5(1), 282-297. https://doi.org/10.56879/ijbm.v5i1.20

Bian, X., Wang, B., & Yang, A. (2025). The trust trifecta: How transparency, ethics, and benefits shape public confidence in government AI. Government Information Quarterly. https://doi.org/10.1016/j.giq.2025.102083

Bokhari, S. A. A., Park, S. Y., & Manzoor, S. (2025). Digital government transformation through artificial intelligence: The mediating role of stakeholder trust and participation. Digital, 5(3), 43.

Bracci, E. (2023). The loopholes of algorithmic public services: An “intelligent” accountability research agenda. Accounting, Auditing & Accountability Journal, 36(2), 739-763. https://doi.org/10.1108/AAAJ-06-2022-5856

Cojocaru, A. (2025). Governing AI with trust: An adaptive framework for institutional legitimacy in the UK public sector. Transforming Government: People, Process and Policy. https://doi.org/10.1108/TG-05-2025-0125

Correa, T., Luco, F., Hernández-Estrada, Y., Oyarzún-Merino, I., & López, C. (2026). A three-layered transparency framework for communicating algorithmic systems in the public sector: Exploring participatory prototype design with end users. International Journal of Human-Computer Studies. https://doi.org/10.1016/j.ijhcs.2026.103769

Gesk, T. S., & Leyer, M. (2022). Artificial intelligence in public services: When and why citizens accept its usage. Government Information Quarterly, 39(3), 101704. https://doi.org/10.1016/j.giq.2022.101704

Ghosh, A., Saini, A., & Barad, H. (2025). Artificial intelligence in governance: recent trends, risks, challenges, innovative frameworks and future directions. AI & SOCIETY, 40(7), 5685-5707. https://doi.org/10.1007/s00146-025-02312-y

Grimmelikhuijsen, S. (2023). Explaining why the computer says no: Algorithmic transparency affects the perceived trustworthiness of automated decision-making. Public Administration Review, 83(2), 241–262. https://doi.org/10.1111/puar.13483

Haesevoets, T., Verschuere, B., Van Severen, R., & Roets, A. (2024). How do citizens perceive the use of artificial intelligence in public sector decisions? Government Information Quarterly, 41(1), 101906. https://doi.org/10.1016/j.giq.2023.101906

Horvath, L., James, O., Banducci, S., & Beduschi, A. (2023). Citizens’ acceptance of artificial intelligence in public services: Evidence from a conjoint experiment about processing permit applications. Government Information Quarterly, 40(4), 101876. https://doi.org/10.1016/j.giq.2023.101876

Ibrahimli, G. (2026). Closing the Governance Readiness Gap Building Institutional Capacity for Responsible AI Governance in Emerging Public Administrations. Available at SSRN 7009338. http://dx.doi.org/10.2139/ssrn.7009338

Kleizen, B., Van Dooren, W., Verhoest, K., & Tan, E. (2023). Do citizens trust trustworthy artificial intelligence? Experimental evidence on the limits of ethical AI measures in government. Government Information Quarterly, 40(4), 101834. https://doi.org/10.1016/j.giq.2023.101834

Laelaturramadani, L. (2026). Administrative Accountability for Artificial Intelligence Decision-Making Systems in Indonesian Governance. Journal of Legal Framework, 1(2), 65-77.

Lund, B., Orhan, Z., Mannuru, N. R., Bevara, R. V. K., Porter, B., Vinaih, M. K., & Bhaskara, P. (2025). Standards, frameworks, and legislation for artificial intelligence (AI) transparency. AI and Ethics, 5(4), 3639-3655. https://doi.org/10.1007/s43681-025-00661-4

Ly, B. (2025). Bridging governance and technology: Key determinants of AI adoption in public administration. Chinese Political Science Review, 1-34. https://doi.org/10.1007/s41111-025-00308-z

Malik, A. (2026). Regulating Artificial Intelligence in the Public Sector: Policy Frameworks for Accountability, Ethics, and Human Rights Protection. Social Science Review Archives, 4(2), 1713-1726. https://doi.org/10.70670/sra.v4i2.2263

Margetts, H., & Dunleavy, P. (2026). The political economy of digital government: How Silicon Valley firms drove conversion to data science and artificial intelligence in public management. Public Money & Management, 46(6), 735-745. https://doi.org/10.1080/09540962.2024.2389915

Ng, Y. F., O'Sullivan, M., Paterson, M., & Witzleb, N. (2020). Revitalising public law in a technological era: Rights, transparency and administrative justice. University of New South Wales Law Journal, The, 43(3), 1041-1077.

Regona, M., Yigitcanlar, T., Hon, C., & Teo, M. (2026). Building trust in artificial intelligence: A systematic review through the lens of trust theory. ACM Computing Surveys, 58(9), 1-39. https://doi.org/10.1145/3789256

Ripamonti, J. P. (2024). Does being informed about government transparency boost trust? Exploring an overlooked mechanism. Government Information Quarterly, 41(3), 101960. https://doi.org/10.1016/j.giq.2024.101960

Rulandari, N., Silalahi, A. D. K., Phuong, D. T. T., & Eunike, I. J. J. (2025). Decoding effectiveness and efficiency in AI-enabled public services: A configurational pathway to citizen and employee satisfaction. Frontiers in Political Science, 7. https://doi.org/10.3389/fpos.2025.1560180

Satyo, B. K., SH, M. K., Prasetyo, B. A. Y., & SH, M. K. (2026). Artificial Intelligence and the Future of Human Rights: Legal Accountability for Algorithmic Decision-Making in Democratic Societies. International Journal of Law and Social Science (IJLSS), 2(1), 54-74. https://doi.org/10.65960/ijlss.2.1.2026.12

Savveli, I., Rigou, M., & Balaskas, S. (2025, September). From e-government to AI e-government: A systematic review of citizen attitudes. In Informatics (Vol. 12, No. 3, p. 98). MDPI. https://doi.org/10.3390/informatics12030098

Smith, N., Gillespie, N., Rinta-Kahila, T., Lockey, S., Pool, J., & Curtis, C. (2026). How to demonstrate trustworthy use of AI in public services: A case study. Information Systems Journal, 1–24. https://doi.org/10.1111/isj.70025

Taeihagh, A. (2021). Governance of artificial intelligence. Policy and society, 40(2), 137-157. https://doi.org/10.1080/14494035.2021.1928377

Tsarouhas, P., & Grigoriadis, K. (2025). A socio-technical framework for AI trust in public administration. Transforming Government: People, Process and Policy, 1-22. https://doi.org/10.1108/TG-06-2025-0157

Virnandes, S. R., Shen, J., & Vlahu-Gjorgievska, E. (2024). Building public trust through digital government transformation: A qualitative study of Indonesian civil service agency. Procedia Computer Science, 234, 1183–1191. https://doi.org/10.1016/j.procs.2024.03.114

Visave, J. (2025). Transparency in AI for emergency management: Building trust and accountability. AI and Ethics, 5, 3967–3980. https://doi.org/10.1007/s43681-025-00692-x

Wang, Y.-F., Chen, Y.-C., Chien, S.-Y., & Wang, P.-J. (2024). Citizens’ trust in AI-enabled government systems. Information Polity, 29(3), 293–312. https://doi.org/10.3233/IP-230065

Yannis, C., & Gerasimos, K. (2026). Rule Based AI Systems for Public Governance. A Framework for Smarter, Transparent and Citizen-Centered Governance. Artificial Intelligence and Government: Examining the Roles and Uses of AI in Enhancing Government Operations, 59-87. https://doi.org/10.1007/978-3-032-12344-2_4

Zheng, Y., Ye, & Farhan, M. (2026). Algorithmic transparency and citizen trust in digital governance: A cross-national analysis of AI adoption in public services. Technology in Society, 88, 103445. https://doi.org/10.1016/j.techsoc.2026.103445