Participatory Methodology to Assess the Impacts of Artificial Intelligence in urban contexts
Submitted: 2025-05-07
|Accepted: 2026-05-07
|Published: 2026-05-19
Copyright (c) 2026 Gabriela Munares Sanchez, Rebeca Lucas, Maite Ferrando, Empar Soriano
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Downloads
Keywords:
artificial intelligence, social impact assessment, participatory methodology, urban services, public services, smart cities
Supporting agencies:
This work has been supported by the European Commission, under the frameworkprogrammeDigital Europe (DIGITAL-2022-CLOUD-AI-02-TEF-SMART), Grant Agreement number 10110072
Abstract:
This paper presents a novel methodology for assessing the social impact of Artificial Intelligence (AI) solutions in urban environments, developed within the framework of the CITCOM.ai project, cofinanced by European Union. As cities increasingly adopt AI technologies to enhance public services, a systematic approach to evaluating their societal implications becomes essential. Our methodology addresses the dual challenge of AI's context-specific impacts and rapidly evolving applications through a reflexive participatory process grounded in the European Commission's Assessment List for Trustworthy Artificial Intelligence (ALTAI). We detail a roadmap for conducting Artificial Intelligence Impact Assessments (AIIA) that engages diverse stakeholder groups in identifying potential impacts and developing Key Performance Indicators (KPIs) for monitoring. The methodology builds upon existing frameworks while addressing current gaps in impact assessment practices. We validate our approach through a participatory workshop involving 26 stakeholders in Valencia, Spain, focusing on three urban service domains: Mobility, Tourism, and Waste Management
References:
Antsaklis, P. (2020). Autonomy and metrics of autonomy. Annual Reviews in Control, 49, 15-26. https://doi.org/10.1016/j.arcontrol.2020.05.0
Bosch, P., Jongeneel, S., Rovers, V., Neumann, H.-M., Airaksinen, M., & Huovila, A. (2017). CITYkeys indicators for smart city projects and smart cities. https://globalgbc.org/wp-content/uploads/2022/08/01015_CITYkeystheindicatorsAutosaved
Doteveryone. (2019, abril). Consequence Scanning. tech-transformed.org. https://doteveryone.org.uk/wp-content/uploads/2021/02/Consequence-Scanning-Agile-Event-Manual-TechTransformed-Doteveryone-2.pdf
European Commission. (2020). The Assessment List for Trustworthy Artificial Intelligence (ALTAI) for self assessment. Publications Office. https://data.europa.eu/doi/10.2759/002360
European Commission & High Level Expert Group on Artificial Intelligence. (2019). Ethics guidelines for trustworthy AI.Publications Office. https://data.europa.eu/doi/10.2759/346
European Commission. Joint Research Centre. (2020). AI Watch, artificial intelligence in public services: Overview of the use and impact of AI in public services in the EU. Publications Office. https://data.europa.eu/doi/10.2760/039619
GDPR.EU. (2025, agosto 29). Art. 9 GDPR Processing of special categories of personal data[European project]. General Data Protection Regulation (GDPR). https://gdpr.eu/article-9-processing-special-categories-of-personal-data-prohibited/
OECD. (2022). OECD Framework for the Classification of AI systems(OECD Digital Economy Papers No. 323; OECD Digital Economy Papers, Vol. 323). https://doi.org/10.1787/cb6d9eca-en
Patton, M. Q. (2002). Qualitative research & evaluation methods(3. ed.,). Sage.
Pira, M. (2021). A novel taxonomy of smart sustainable city indicators. Humanities and Social Sciences Communications, 8(1), 197. https://doi.org/10.1057/s41599-021-00879-7
Platform for the Information Society (ECP). (2018). Artificial Intelligence Impact Assessment. Colofon. https://ecp.nl/wp-content/uploads/2019/01/Artificial-Intelligence-Impact-Assessment-English.pdf
Ryan, M., & Gregory, A. (2019). Ethics of Using Smart City AI and Big Data: The Case of Four Large European Cities. The ORBIT Journal, 2(2), 1-36. https://doi.org/10.29297/orbit.v2i2.110
Schütz, F., Heidingsfelder, M. L., & Schraudner, M. (2019). Co-shaping the Future in Quadruple Helix Innovation Systems: Uncovering Public Preferences toward Participatory Research and Innovation. She Ji: The Journal of Design, Economics, and Innovation, 5(2), 128-146. https://doi.org/10.1016/j.sheji.2019.002
The World Café Community Foundation. (2025, agosto 29). World Cafe Method. The World Cafe. https://theworldcafe.com/key-concepts-resources/world-cafe-method/
U4SSC. (2017). Collection Methodology for Key Performance Indicators for Smart Sustainable Cities. https://unece.org/fileadmin/DAM/hlm/documents/Publications/U4SSC-CollectionMethodologyforKPIfoSSC-2017.pdf
UNEP. (2020). Guidelines for Social Life Cycle Assessment of Products and Organizations 2020. United Na-tions Environment Programme (UNEP).
UNESCO. (2023). Ethical impact assessment. A tool of the Recommendation on the Ethics of Artificial Intelligence. UNESCO. https://doi.org/10.54678/YTSA7796
Van Noordt, C., & Misuraca, G. (2020). Evaluating the impact of artificial intelligence technologies in public services: Towards an assessment framework. Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance, 8-16. https://doi.org/10.1145/3428502.3428504