Evaluation of Public Services Through the Lens of Digital Ethics

Authors

DOI:

https://doi.org/10.59490/dgo.2025.1033

Keywords:

digital ethics, humanistic, AI ethics, ethical concerns, LLM, NLP

Abstract

The rapidly growing popularity of digital services requires robust frameworks to identify and address associated ethical concerns. This paper presents a structured framework for assessing ethical concerns of digital services, offering a scalable and adaptable tool to assess concerns, including data misuse, cybersecurity, transparency, inequality, and sustainability. The framework employs a customized Delphi method to gather diverse expert insights, translating them into quantifiable metrics through a mathematical model. These metrics inform structured surveys, generating actionable outputs, including visual summaries, static recommendations, and AI-driven insights. To illustrate the framework’s application, we detail its implementation in the context of electronic voting (e-voting). By addressing key ethical challenges, mainly privacy, transparency, and inclusivity, this use case demonstrates the framework’s utility in analyzing complex digital services. The study highlights the importance of balancing technological innovation with ethical accountability, providing a practical approach to ensuring transparency and trust in public digital services.

Downloads

Download data is not yet available.

References

Andreasyan, N., Buson, D., Rüst, J., Portmann, E., & Terán, L. (2024). Theoretical framework of digital ethics concerns for public services: Electronic voting use case. 2024 Tenth International Conference on eDemocracy & eGovernment (ICEDEG), 1–9.

Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L. (2018). Artificial intelligence and the ’good society’: The us, eu, and uk approach. Science and engineering ethics, 24. DOI: https://doi.org/10.1007/s11948-017-9901-7.

Dalkey, N., & Helmer, O. (1963). An experimental application of the delphi method to the use of experts. Management Science, 9(3), 458–467.

Döringer, S. (2021). ‘the problem-centred expert interview’. combining qualitative interviewing approaches for investigating implicit expert knowledge. International journal of social research methodology, 24(3), 265–278.

Druliac, H., Bardsley, M., Riches, C., Dunn, C., Harrison, L., Roy, B., & Hao, F. (2024). On the feasibility of e2e verifiable online voting–a case study from durga puja trial. Journal of Information Security and Applications, 81, 103719.

Dubai, S. (2023). Ai system ethics self-assessment tool [Last accessed: 2025-01-17]. [link]

Enguehard, C. (2014). Ethics and electronic voting. ETHICOMP 2014-Liberty and Security in an Age of ICTs. Fowler Jr, F. J., & Cosenza, C. (2009). Design and evaluation of survey questions. The SAGE handbook of applied social research methods, 2, 375–412.

Gritzalis, D. A. (2002). Principles and requirements for a secure e-voting system. Computers & Security, 21(6), 539–556.

Hakimi, L., Eynon, R., & Murphy, V. A. (2021). The ethics of using digital trace data in education: A thematic review of the research landscape. Review of Educational Research, 91(5), 671–717.

Hardebolle, C., Macko, V., Ramachandran, V., Holzer, A., & Jermann, P. (2023). Digital ethics canvas: A guide for ethical risk assessment and mitigation in the digital domain. European Society for Engineering Education (SEFI). DOI: https://doi.org/10.21427/9wa5-zy95.

Hart, R. (2024). Clearview ai fined over 30 million usd for facial recognition database [Accessed: 2025-04-10]. Forbes. [link]

Huang, P.-h., Kim, K.-h., & Schermer, M. (2022). Ethical issues of digital twins for personalized health care service: Preliminary mapping study. Journal of Medical Internet Research, 24(1), e33081.

Joisten, K., Thiemer, N., Renner, T., Janssen, A., & Scheffler, A. (2022). Focusing on the ethical challenges of data breaches and applications. 2022 IEEE International Conference on Assured Autonomy (ICAA), 74–82. DOI: https://doi.org/10.1109/ICAA52185.2022.00018.

Kacprzyk, J., & Yager, R. R. (2001). Linguistic summaries of data using fuzzy logic. International Journal of General System, 30(2), 133–154.

Kukreja, S., Kumar, T., Purohit, A., Dasgupta, A., & Guha, D. (2024). A literature survey on open source large language models. Proceedings of the 2024 7th International Conference on Computers in Management and Business, 133–143. DOI: https://doi.org/10.1145/3647782.3647803.

Lauer, T. W. (2004). The risk of e-voting. Electronic Journal of E-government, 2(3), pp169–178.

Linstone, H. A., Turoff, M., et al. (1975). The delphi method. Addison-Wesley Reading, MA.

Lukianets, N., Nekrutenko, V., & Pavaloiu, A. (2021). Openethicsai/canvas: The open ethics canvas v1.0.1 [Accessed: 2025-01-16]. DOI: https://doi.org/10.5281/zenodo.5211845.

Manchanda, J., Boettcher, L., Westphalen, M., & Jasser, J. (2024). The open source advantage in large language models (llms). arXiv preprint arXiv:2412.12004. [link]

MindsDB. (2024). Which llm to choose: 12 key aspects to consider when building ai solutions [Accessed: 2025-01-23]. [link]

Nabbosa, V., & Kaar, C. (2020). Societal and ethical issues of digitalization. Proceedings of the 2020 international conference on Big Data in Management, 118–124.

Nasa, P., Jain, R., & Juneja, D. (2021). Delphi methodology in healthcare research: How to decide its appropriateness. World journal of methodology, 11(4), 116.

Olszewska, J. I., Systems, Committee, S. E. S., et al. (2022). Ieee/iso/iec international standard–systems and software engineering–life cycle management–part 7000: Standard model process for addressing ethical concerns during system design. ISO/ IEC/IEEE 24748-7000 First edition 2022-11, 1–86. DOI: https://doi.org/10.1109/IEEESTD.2022.9967807.

on AI, E. C. H.-L. E. G. (2020). The assessment list for trustworthy artificial intelligence (altai) [Last accessed: 2025-01-17]. [link]

Ortega, E., Tran, M., & Bandeen, G. (2023). Ai digital tool product lifecycle governance framework through ethics and compliance by design†. 2023 IEEE Conference on Artificial Intelligence (CAI), 353–356. DOI: https://doi.org/10.1109/CAI54212.2023.00155.

Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers.

Pakhnenko, O., Kuan, Z., et al. (2023). Ethics of digital innovation in public administration. Business Ethics and Leadership, 7(1), 113–121.

Poszler, F., Portmann, E., & Lütge, C. (2024). Formalizing ethical principles within ai systems: Experts’ opinions on why (not) and how to do it. AI and Ethics, 1–29.

Robinson, D. G., & Halderman, J. A. (2011). Ethical issues in e-voting security analysis. International Conference on Financial Cryptography and Data Security, 119–130.

Schoentgen, A., & Wilkinson, L. (2021). Ethical issues in digital technologies [conference session]. 23rd Biennial Conference of the International Telecommunications Society (ITS), Gothenburg, Sweden. [link].

Teran, L., Pincay, J., Wallimann-Helmer, I., & Portmann, E. (2021). A literature review on digital ethics from a humanistic and sustainable perspective. 14th International Conference on Theory and Practice of Electronic Governance, 57–64. DOI: https://doi.org/10.1145/3494193.3494295.

The Guardian. (2010). Google admits collecting wi-fi data through street view cars [Accessed: 2025-04-10]. The Guardian. [link]

The Guardian. (2018). Revealed: 50 million facebook profiles harvested for cambridge analytica in major data breach [Accessed: 2025-04-10]. The Guardian. [link]

The Guardian. (2022). Clearview ai fined in uk over facial recognition data collection [Accessed: 2025-04-10]. The Guardian. [link]

Trechsel, A. H., Kucherenko, V. V., & da Silva, F. F. (2016). Potential and challenges of e-voting in the european union (tech. rep. No. 2016/11) (Last accessed: 2025-01-17). European Union Democracy Observatory (EUDO). [link]

UbiOps. (2024). Which llm to choose for your use case [Accessed: 2025-01-23]. [link]

Wallimann-Helmer, I., Terán, L., Portmann, E., Schübel, H., & Pincay, J. (2021). An integrated framework for ethical and sustainable digitalization [ISSN: 2573-1998]. 2021 Eighth International Conference on eDemocracy & eGovernment (ICEDEG), 156–162. DOI: https://doi.org/10.1109/ICEDEG52154.2021.9530972.

Warner, L. M. (2023). Ethics in public service. In Global encyclopedia of public administration, public policy, and governance (pp. 4394–4398). Springer.

Wired. (2012). Google engineer told colleagues street view wi-fi data collection was not a mistake [Accessed: 2025-04-10]. Wired. [link]

Wrede, C., Winands, M., & Wilbik, A. Linguistic summaries as explanation mechanism for classification problems [The 34th Benelux Conference on Artificial Intelligence and the 31th Belgian Dutch Conference on Machine Learning, BNAIC 2022 ; Conference date: 07-11-2022 Through 09-11-2022]. English. In: In The 34th benelux conference on artificial intelligence and the 31th belgian dutch conference on machine learning. The 34th Benelux Conference on Artificial Intelligence and the 31th Belgian Dutch Conference on Machine Learning, BNAIC 2022 ; Conference date: 07-11-2022 Through 09-11-2022. 2022, November.

Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338–353.

Zadeh, L. A. (2008). Is there a need for fuzzy logic? Information Sciences, 178(13), 2751–2779. DOI: https://doi.org/10.1016/j.ins.2008.02.012.

Downloads

Additional Files

Published

2025-05-23 — Updated on 2025-06-05

Versions

How to Cite

Andreasyan, N., Buson, D., Mancera, J., Portmann, E., & Terán, L. (2025). Evaluation of Public Services Through the Lens of Digital Ethics. Conference on Digital Government Research, 26. https://doi.org/10.59490/dgo.2025.1033 (Original work published May 23, 2025)

Conference Proceedings Volume

Section

Research papers