Participatory Methodology to Assess the Impacts of Artificial Intelligence in urban contexts

Handle

https://riunet.upv.es/handle/10251/235333

Cita bibliográfica

Munares Sanchez, G.; Lucas, R.; Ferrando, M.; Soriano, E. (2026). Participatory Methodology to Assess the Impacts of Artificial Intelligence in urban contexts. Journal of Policy Evaluation. 2:134-189. https://doi.org/10.4995/jpeval.2026.23888

Titulación

Resumen

[EN] 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

Fuente

Journal of Policy Evaluation

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