Charmaine Distor, Research Consultant at UNU-EGOV, participated in the 10th edition of the Data for Policy Conference, held from 8 to 10 September 2026 at Universitat Pompeu Fabra in Barcelona, Spain.
Under the theme “Governance of/with AI: Implications for Data, Infrastructure, and Tech Sovereignty”, the conference brought together around 200 participants from 44 countries to discuss emerging challenges and opportunities at the intersection of data, artificial intelligence, and public governance.
On behalf of the UNU-EGOV research team – Soumaya Ben Dhaou, Catarina Fontes, Tupokigwe Isagah and Alia Yofira Karunian – Charmaine Distor presented their ongoing research project “Beyond the Black Box: Expert Perspectives on Fair AI in Urban Governance.” The project is being developed within the framework of the International Telecommunication Union (ITU) United for Smart Sustainable Cities (U4SSC) FAIR Cities Working Group.
The research explores how fairness can be operationalized in urban AI systems and embedded throughout the entire AI lifecycle, rather than being treated as a final compliance requirement. Drawing on expert interviews and focus group discussions, the study examines the governance mechanisms needed to ensure that AI systems used in cities are transparent, accountable, context-sensitive, and aligned with public values.
Among the project's initial findings, the team identified several key challenges for the responsible deployment of AI in urban contexts. These include the need to address structural bias in datasets through stronger approaches to algorithmic fairness, improve transparency and traceability in AI systems beyond technical documentation, and consider questions of digital sovereignty when applying AI models developed outside local contexts.
The findings also highlight the importance of establishing clear frameworks for human oversight and accountability, mitigating the risks associated with over-reliance on automated systems, and incorporating security safeguards throughout the design and deployment process. Furthermore, it emphasizes the need for meaningful and accessible mechanisms that allow citizens to question and contest automated decisions that affect them.
A central takeaway emerging from the research is that fair AI should be treated as an integral component of the entire AI lifecycle, shaping the design, development, deployment, and governance of AI systems from the outset.
The Data for Policy Conference featured 123 research contributions selected through a competitive peer-review process, alongside keynote sessions, plenary discussions, and Digital Statecraft debates. The event provided an important platform for researchers, policymakers, and practitioners to exchange perspectives on the future governance of data and artificial intelligence.
As the project moves forward, the research team will conduct a second round of coding analysis and continue developing a full research paper. The findings will also contribute to the forthcoming ITU-U4SSC FAIR Cities Working Group report and a series of city case studies scheduled for publication later this year.
