Citizen Trust and Digital Governance Transformation: Ethical Challenges and Artificial Intelligence Governance in the Public Sector

Sukwan Hanafi; Achmad Nurmandi; Herman Lawelai; Mohammad Younus

doi:10.31000/jgcs.v10i2.16509

Authors

Sukwan Hanafi Department of Government Affairs and Administration, Universitas Muhammadiyah Yogyakarta , Jusuf Kalla School of Government, Universitas Muhammadiyah Yogyakarta
Achmad Nurmandi Department of Government Affairs and Administration, Universitas Muhammadiyah Yogyakarta , Jusuf Kalla School of Government, Universitas Muhammadiyah Yogyakarta
Herman Lawelai Department of Government Studies, Universitas Muhammadiyah Buton
Mohammad Younus Department of Product Research and Software Development, TPL Logistics Pvt Ltd, Karachi

DOI:

https://doi.org/10.31000/jgcs.v10i2.16509

Abstract

The study explores the development of academic research on citizen trust in AI-enabled public governance, with a particular emphasis on ethical considerations, explainable AI, and digital transformation of government. Data were collected from the Scopus database using a scientometric approach and analyzed using Biblioshiny in RStudio to perform bibliometric mapping. The study revealed the publication patterns, leading authors, leading countries, highly cited papers, research issues, and collaborative networks from 2021 to 2025. The data indicate a significant increase in publications, reflecting growing academic interest in transparency, accountability, and trust in public-sector AI applications. The intellectual structure of the field was shaped by key research themes, including artificial intelligence, explainable artificial intelligence, AI governance, and trust. The United States, Germany, the United Kingdom, the Netherlands, and China have been the main donating countries to scientific production. The findings also reveal that explainability, ethical governance, institutional legitimacy, and algorithmic transparency are important elements for increasing citizen trust and facilitating the uptake of AI-based public services. This paper contributes to the literature by providing a comprehensive assessment of global research trends and future directions for trustworthy, inclusive, and citizen-centric digital government.

Studi ini mengeksplorasi perkembangan penelitian akademis tentang kepercayaan warga terhadap pemerintahan publik yang didukung oleh AI, dengan penekanan khusus pada pertimbangan etis, AI yang dapat dijelaskan, dan transformasi digital pemerintah. Data dikumpulkan dari basis data Scopus menggunakan pendekatan scientometric dan dianalisis dengan menggunakan Biblioshiny di RStudio untuk melakukan pemetaan bibliometrik. Studi ini mengungkap pola publikasi, penulis terkemuka, negara terkemuka, makalah yang banyak dikutip, isu penelitian, dan jaringan kolaboratif dari tahun 2021 hingga 2025. Data tersebut menunjukkan peningkatan signifikan dalam publikasi, yang menunjukkan minat akademis yang semakin besar dalam transparansi, akuntabilitas, dan kepercayaan dalam aplikasi AI sektor publik. Struktur intelektual bidang ini dibentuk oleh tema-tema penelitian utama seperti kecerdasan buatan, kecerdasan buatan yang dapat dijelaskan, tata kelola AI, dan kepercayaan. Amerika Serikat, Jerman, Inggris Raya, Belanda, dan China telah menjadi negara-negara utama yang menyumbang pada produksi ilmiah. Temuan tersebut juga mengungkapkan bahwa keterjelasan, tata kelola etis, legitimasi institusional, dan transparansi algoritmik adalah elemen penting untuk meningkatkan kepercayaan warga dan memfasilitasi penerapan layanan publik berbasis AI. Makalah ini memberikan kontribusi pada literatur dengan menyediakan penilaian komprehensif tentang tren penelitian global dan arah masa depan untuk pemerintahan digital yang dapat dipercaya, inklusif, dan berpusat pada warga

References

Alrawahna, A. S., Alzghoul, A., & Awad, H. (2025). The Impact of Artificial Intelligence on Public Sector Decision-Making: Benefits, Challenges, and Policy Implications. International Review of Management and Marketing , 15(5), 125–138. https://doi.org/10.32479/irmm.19419

Askr, H., Elgeldawi, E., Aboul, H., & Yaseen, E. (2023). Deep learning in drug discovery : an integrative review and future challenges. In Artificial Intelligence Review (Vol. 56, Issue 7). Springer Netherlands. https://doi.org/10.1007/s10462-022-10306-1

Baas, J., Schotten, M., Plume, A., Côté, G., & Karimi, R. (2020). Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1), 377–386. https://doi.org/10.1162/qss_a_00019

Bean, E., Burleigh, C., Haskell, C., Burris-Melville, T., Payne, J., & Pathak, B. (2025). Eavesdropping on UNESCO AI Policy, Leadership, and Ethics. Journal of Leadership Studies, 18(4), 98–110. https://doi.org/10.1002/jls.70007

Bhatia, M., & Kumar, V. (2025). Artificial Intelligence in Digital Twin Technology: Scientometric Insights on Architecture, Applications, and Tools. IEEE Internet of Things Journal, 12(16), 32653–32675. https://doi.org/10.1109/JIOT.2025.3575476

Bian, X., Wang, B., & Yang, A. (2025). The trust trifecta: How transparency, ethics, and benefits shape public confidence in government AI. Government Information Quarterly, 42(4). 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). https://doi.org/10.3390/digital5030043

Cheng, J., & Zeng, J. (2023). Shaping AI’s Future? China in Global AI Governance. Journal of Contemporary China, 32(143), 794–810. https://doi.org/10.1080/10670564.2022.2107391

Erman, E., & Furendal, M. (2024). Artificial Intelligence and the Political Legitimacy of Global Governance. https://doi.org/10.1177/00323217221126665

Fadrial, R., Freddy Simanjuntak, H. T. R., Wirman, W., & Wibowo, W. S. (2024). FOSTERING TRUST THROUGH BYTES: UNRAVELLING THE IMPACT OF E-GOVERNMENT ON PUBLIC TRUST IN INDONESIAN LOCAL GOVERNMENT. Interdisciplinary Journal of Information, Knowledge, and Management, 19. https://doi.org/10.28945/5317

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

Helberger, N., & Diakopoulos, N. (2023). ChatGPT and the AI Act. Internet Policy Review, 12(1). https://doi.org/10.14763/2023.1.1682

Icasiano, C. D. A., & Taeihagh, A. (2021). Governance of the Risks of Ridesharing in Southeast Asia: An In-Depth Analysis. Sustainability, 13(11), 6474. https://doi.org/10.3390/su13116474

Jaspers, S., & Migchelbrink, K. (2023). How citizen coproducers cope with public value creation conflicts: a survey experiment. International Journal of Public Sector Management, 36(3), 236–252. https://doi.org/10.1108/IJPSM-04-2022-0089

Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100074

Knoll, B., Pitlik, H., & Rode, M. (2023). TV Consumption Patterns and the Impact of Media Freedom on Political Trust and Satisfaction with the Government. Social Indicators Research, 169(1–2), 323–340. https://doi.org/10.1007/s11205-023-03160-3

Langer, M., Oster, D., Speith, T., Hermanns, H., Kästner, L., Schmidt, E., Sesing, A., & Baum, K. (2021). What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research. Artificial Intelligence, 296. https://doi.org/10.1016/j.artint.2021.103473

Latupeirissa, J. J. P., Dewi, N. L. Y., Prayana, I. K. R., Srikandi, M. B., Ramadiansyah, S. A., & Pramana, I. B. G. A. Y. (2024). Transforming Public Service Delivery: A Comprehensive Review of Digitization Initiatives. Sustainability (Switzerland) , 16(7), 16072818. https://doi.org/10.3390/su16072818

Laux, J., Wachter, S., & Mittelstadt, B. (2024). Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk. Regulation and Governance, 18(1), 3–32. https://doi.org/10.1111/rego.12512

Liu, H. Y., & Maas, M. M. (2021). ‘Solving for X?’ Towards a problem-finding framework to ground long-term governance strategies for artificial intelligence. Futures, 126. https://doi.org/10.1016/j.futures.2020.102672

Meske, C., Bunde, E., Schneider, J., Gersch, M., Meske, C., Bunde, E., Schneider, J., Gersch, M., & Meske, C. (2022). Explainable Artificial Intelligence : Objectives , Stakeholders , and Future Research Opportunities Opportunities. Information Systems Management, 39(1), 53–63. https://doi.org/10.1080/10580530.2020.1849465

Nawafleh, S. (2020). The implementation of e-government and the trust of citizens in public sector performance: The mediating role of service quality. International Journal of Public Sector Performance Management, 6(1), 17–35. https://doi.org/10.1504/IJPSPM.2020.105086

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372. https://doi.org/10.1136/bmj.n71

Patterson, E., & Agarwal, R. (2023). Reducing the gap between rhetoric and reality: Use of Digital Service Standards for public service innovation through digital transformation in Australia. Australian Journal of Public Administration, 82(4), 557–589. https://doi.org/10.1111/1467-8500.12615

Poelzer, G. (2024). The truth or your truth: polarization in Arctic climate change on X (Twitter). Polar Geography, 1–14. https://doi.org/10.1080/1088937X.2024.2402757

Ranerup, A., & Henriksen, H. Z. (2019). Value positions viewed through the lens of automated decision-making: The case of social services. Government Information Quarterly, 36(4). https://doi.org/10.1016/j.giq.2019.05.004

Robles, P., & Mallinson, D. J. (2025). Artificial intelligence technology, public trust, and effective governance. Review of Policy Research, 42(1), 11–28. https://doi.org/10.1111/ropr.12555

Setyarto, D. B., Alimuddin, Mulyaningsih, & Judijanto, L. (2025). The role of e-government in increasing transparency and accountability of public administration in the digital era. Edelweiss Applied Science and Technology, 9(2), 1771–1783. https://doi.org/10.55214/25768484.v9i2.4908

Shayganmehr, M., Kumar, A., Garza-Reyes, J. A., & Zavadskas, E. K. (2023). A framework for assessing trust in e-government services under uncertain environment. Information Technology and People, 36(7), 2718–2755. https://doi.org/10.1108/ITP-01-2021-0096

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

Tallberg, J., Erman, E., Furendal, M., Geith, J., Klamberg, M., & Lundgren, M. (2023). The Global Governance of Artificial Intelligence: Next Steps for Empirical and Normative Research. International Studies Review, 25(3), viad040. https://doi.org/10.1093/isr/viad040

Tsarouhas, P., & Grigoriadis, K. (2025). Building Trust in AI for Public Administration: A Strategic Framework for Transparency, XAI, Participation, and Digital Literacy. ICHORA 2025 - 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings. https://doi.org/10.1109/ICHORA65333.2025.11017116

van der Waa, J., Nieuwburg, E., Cremers, A., & Neerincx, M. (2021). Evaluating XAI: A comparison of rule-based and example-based explanations. Artificial Intelligence, 291. https://doi.org/10.1016/j.artint.2020.103404

Van Nguyen, P., Vrontis, D., Nguyen, L. D. P., Nguyen, T. T. U., & Salloum, C. (2025). Unraveling the Role of Citizens’ Concerns and Cognitive Appraisals in E-Government Adoption: The Impact of Social Media and Trust. Strategic Change, 34(5), 675–688. https://doi.org/10.1002/jsc.2646

Virnandes, S. R., Shen, J., & Vlahu-Gjorgievska, E. (2024). Shaping Trust in Public Service: A Convergent Mixed-methods Investigation of Digital Government Transformation. Proceedings - 28th Pacific Asia Conference on Information Systems, PACIS 2024. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105026554188&partnerID=40&md5=c2c1fe4541147cf54731a9cbc2f42e28

Ye, Y., Yu, P., & Zhang, X. (2024). More trust in central government during the COVID-19 pandemic? Citizens’ emotional reactions, government performance, and trust in governments. International Journal of Disaster Risk Reduction, 108. https://doi.org/10.1016/j.ijdrr.2024.104555

Yeo, W. J., Van Der Heever, W., Mao, R., Cambria, E., Satapathy, R., & Mengaldo, G. (2025). A comprehensive review on financial explainable AI. Artificial Intelligence Review, 58(6). https://doi.org/10.1007/s10462-024-11077-7

Zlateva, P., Steshina, L., Petukhov, I., & Velev, D. (2024). A Conceptual Framework for Solving Ethical Issues in Generative Artificial Intelligence. In T.-B. A.J., C.-A. E., & L.-G. D.A. (Eds.), Frontiers in Artificial Intelligence and Applications (Vol. 381, pp. 110–119). IOS Press BV. https://doi.org/10.3233/FAIA231182