Chapter 6: Measuring user-centricity in AI-enabled European public services: a proposal for enabling maturity models
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User-centricity, formally introduced in 2009 by the European Commission, is one of the underlying approaches to European public services. However, despite being a consolidated practice in the Member States, measuring all the user-centric principles for designing and delivering public services is difficult. This study introduces a framework embedding an innovative approach to measuring user centricity in AI enabled public services. The underlying perspective is that user centricity principles may be disaggregated into a list of single AI-enabled functionalities easier to measure, paving the way for adopting maturity models. The proposed framework contributes to the existing literature and adds an innovative method highlighting to what extent AI-based technologies reinforce the user-centricity of digital public services. A test on a small sample of public services provides the first feedback on the framework’s usability.

  • AI Watch.

  • Alzahrani, L., Al-Karaghouli, W., and Weerakkody, V. (2017). Analysing the critical factors influencing trust in e-government adoption from citizens’ perspective: A systematic review and a conceptual framework. International Business Review, 26(1), 164–175.

  • Andersen, K. N., Medaglia, R., Vatrapu, R., Henriksen, H. Z., and Gauld, R. (2011). The forgotten promise of e-government maturity: Assessing responsiveness in the digital public sector. Government Information Quarterly, 28(4), 439–445.

  • Andrus, M., and Villeneuve, S. (2022). Demographic-reliant algorithmic fairness: Characterising the risks of demographic data collection in the pursuit of fairness. arXiv preprint arXiv:2205.01038.

  • Balatsas-Lekkas, A., and Grenman, K. (2021). Baseline survey report: Identifying current approaches to user-centricity assessment of digital public services. European Union.

  • Berntzen, L. (2013). Citizen-centric eGovernment Services. In The Sixth International Conference on Advances in Human-oriented and Personalised Mechanisms, Technologies, and Services (CENTRIC) (pp. 132–136).

  • Bruno, I., Lobo, G., Covino, B. V., Donarelli, A., Marchetti, V., Panni, A. S., and Molinari, F. (2020, September). Technology readiness revisited: A proposal for extending the scope of impact assessment of European public services. In Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance (pp. 369–380).

  • Bruno, I., Schiavone Panni, A., Marchetti, V., Molinari, F., and Valente Covino, B. (2020). A Multi-dimensional Framework to Evaluate the Innovation Potential of Digital Public Services: A Step Towards Building an Innovative Public Services Observatory in the EU (No. JRC121672). Joint Research Centre (Seville site).

  • Buhmann, A., and Fieseler, C. (2022). Deep learning meets deep democracy: Deliberative governance and responsible innovation in artificial intelligence. Business Ethics Quarterly, 1–34.

  • Desouza, K. C., Dawson, G. S., and Chenok, D. (2020). Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector. Business Horizons, 63(2), 205–213.

  • EURAXESS. About Technology Readiness Level,

  • European Commission. (2009). Ministerial declaration on eGovernment,

  • European Commission. (2017). Ministerial Declaration on eGovernment – the Tallinn Declaration, European Union,

  • European Commission. (2020a). Berlin Declaration on Digital Society and Value-based Digital Government,

  • European Commission. (2020b). eGovernment Benchmark 2020: eGovernment that Works for the People,

  • European Commission, Directorate-General for Communications Networks, Content and Technology. (2021a). eGovernment Benchmark 2021: Entering a New Digital Government Era: Insight Report, Publications Office,

  • European Commission, Directorate-General for Communications Networks, Content and Technology. (2021b). eGovernment Benchmark: Method Paper 2020–2023, Publications Office.

  • European Commission, Digital Economy and Society Index (DESI). (2021a). Released on 12 November 2021, retrievable at

  • European Commission, Digital Economy and Society Index (DESI). (2021b). Methodological Note, retrievable at

  • European Commission, Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts, Brussels, 21.4.2021 COM(2021) 206 final 2021/0106 (COD).

  • European Commission and CapGemini. (2019). eGovernment Benchmark 2019: Empowering Europeans through Trusted Digital Public Services. Insight Report, Publications Office of the European Union, ISBN: 9789276110248

  • Gugliotta, A., Niglia, F., and Schina, L. (2013, June). An user-centric check of the available e-government services in Europe. In 13th European Conference on eGovernment ECEG 2013 (pp. 230–239). Como, Italy: Department of Theoretical and Applied Sciences, University of Insubria.

  • Kim, D. Y., and Grant, G. (2010). E‐government maturity model using the capability maturity model integration. Journal of Systems and Information Technology, 12(3), 230–244.

  • Manzoni, M., Medaglia, R., Tangi, L., Van Noordt, C., Vaccari, L., and Gattwinkel, D. (2022). AI WatchRoad to the adoption of Artificial Intelligence by the Public Sector: A Handbook for Policymakers, Public Administrations and Relevant Stakeholders, EUR 31054 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-76-52131-0, doi:10.2760/693531, JRC129100.

  • Medaglia, R., and Tangi, L. (2022, October). The adoption of Artificial Intelligence in the public sector in Europe: drivers, features, and impacts. In Proceedings of the 15th International Conference on Theory and Practice of Electronic Governance (pp. 10–18).

  • Misuraca, G., and van Noordt, C. (2020). Overview of the use and impact of AI in public services in the EU, EUR 30255 EN. Publications Office of the European Union, Luxembourg. doi, 10, 039619.

  • Molinari, F., van Noordt, C., Vaccari, L., Pignatelli, F., and Tangi, L. (2021). AI Watch. Beyond Pilots: Sustainable Implementation of AI in Public Services, EUR 30868 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-76-42587-8, doi:10.2760/440212, JRC 126665.

  • National Interoperability Framework Observatory (NIFO) – Glossary

  • Ozols, G., and Meyerhoff Nielsen, M. (2018). Connected government approach for customer-centric public service delivery: Comparing strategic, governance and technological aspects in Latvia, Denmark and the United Kingdom.

  • Pinzon, C., Renard, R., and O’Neil, G. (2019). European Interoperability Framework (EIF) – implementation and governance models, DT4EU – European Commission.

  • Public Sector Tech Watch.

  • Renda, A., Arroyo, J., Fanni, R., Laurer, M., Sipiczki, A., Yeung, T., … and Milio, S. (2021). Study to support an impact assessment of regulatory requirements for artificial intelligence in Europe. European Commission: Brussels, Belgium.

  • Ryan, M., and Stahl, B. C. (2021). Artificial intelligence ethics guidelines for developers and users: Clarifying their content and normative implications. Journal of Information, Communication and Ethics in Society, 19(1), 61–86.

  • Saqib, M., and Abdus Salam, A. (2018). Towards user centric e-government. In User Centric E-Government (pp. 161–165). Springer, Cham.

  • Smith, M., and Miller, S. (2022). The ethical application of biometric facial recognition technology. AI & Society, 37(1), 167–175.

  • Tangi, L., Soncin, M., Agasisti, T., and Noci, G. (2021). Exploring e-maturity in Italian local governments: Empirical results from a three-step latent class analysis. International Review of Administrative Sciences, 00208523211012752.

  • Tangi, L., Van Noordt, C., Combetto, M., Gattwinkel, D., and Pignatelli, F. (2022). AI Watch. European landscape on the use of Artificial Intelligence by the Public Sector, Publications Office of the European Union, Luxembourg, doi:10.2760/39336, JRC129301.

  • UserCentriCities (UCC) project, available at

  • Valdés, G., Solar, M., Astudillo, H., Iribarren, M., Concha, G., and Visconti, M. (2011). Conception, development and implementation of an e-Government maturity model in public agencies. Government Information Quarterly, 28(2), 176–187.

  • Verdegem, P., and Verleye, G. (2009). User-centered E-Government in practice: A comprehensive model for measuring user satisfaction. Government Information Quarterly, 26(3), 487–497.

  • Weyerer, J.C., and Langer, P.F. (2019, June). Garbage in, garbage out: The vicious cycle of AI-based discrimination in the public sector. In Proceedings of the 20th Annual International Conference on Digital Government Research (pp. 509–511).

  • World Bank Group. (2018). Indicators of Citizen-Centric Public Service Delivery. World Bank.

  • Zicari, R. V., Brodersen, J., Brusseau, J., Düdder, B., Eichhorn, T., Ivanov, T., ... and Westerlund, M. (2021). Z-Inspection®: A process to assess trustworthy AI. IEEE Transactions on Technology and Society, 2(2), 83–97.

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