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EVENT Sep 08
ABSTRACT Jun 01
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Call for Abstracts, Full Papers, and Panels for Data for Policy 2026 (DfP’26) (Data for Policy 2026 (DfP’26))

Universitat Pompeu Fabra, Barcelona, Spain
Organization: Data for Policy CIC
Event: Data for Policy 2026 (DfP’26)
Categories: Interdisciplinary, Popular Culture, Aesthetics, Anthropology/Sociology, Classical Studies, Cultural Studies, Environmental Studies, Film, TV, & Media, Food Studies, History, Philosophy
Event Date: 2026-09-08 to 2026-09-10 Abstract Due: 2026-06-01

Data for Policy 2026 (DfP’26) - Governance of/with AI: Implications for Data, Infrastructure, and Tech Sovereignty

Universitat Pompeu Fabra, Barcelona, Spain - 8th & 10th September 2026
Submission Deadline: 01 June 2026

The Conference Chairs warmly invite submissions in the form of abstracts, full papers and panel proposals for Data for Policy 2026 under the following theme: Governance of/with AI: Implications for Data, Infrastructure, and Tech Sovereignty.

The tenth edition of the conference will focus on the reshaping effects of AI in governance and decision making. This year has witnessed a significant paradigm shift, sparking increased interest in and concern regarding AI governance. The development of AI and data infrastructure has become essential amid the ‘AI War’ between the United States and China, the hybrid conflicts in Europe, and the deployment of military technologies in the Middle East. Strategic investments now prioritize access to frontier technologies, the securing of critical minerals, energy production, and key locations for water supply and cooling. AI is challenging not only global economies but also political systems. We have entered an era where AI influences geopolitics, often at the expense of fundamental rights and values.

The theme “Governance of/with AI” addresses the diverse global perspectives on this evolving technology. As AI continues to transform, it presents both unprecedented opportunities and complex challenges; furthermore, emerging developments such as quantum computing heighten existing uncertainties.

This theme calls for a responsible and ethical societal response while fostering debate across multiple disciplines. We invite reflections and evidence-based research that explore and contest these views. Ranging from geopolitical promises to large-scale investments, social consequences, and legal frameworks, AI has become a truly transdisciplinary field. We welcome contributions from engineering, the humanities, and the social sciences that offer transformative perspectives on our collective future.

Submissions are organised into six broad, interdisciplinary, cross-sectoral areas of interest, which form the standard tracks of the conference.

Area 1: Digital & Data-driven Transformations in Governance
Area 2: Technologies & Analytics
Area 3: Policy & Literacy for Data
Area 4: Ethics, Equity, and Trustworthiness
Area 5: Algorithmic Governance
Area 6: Global Challenges and Dynamic Threats

Submission Formats:
•Individual Extended Abstracts: These should present preliminary research, innovative ideas, or emerging perspectives related to the conference theme or other relevant areas of interest.

•Full Papers: We invite comprehensive, well-researched papers or case studies. Full papers will undergo an integrated review process, with the potential for publication in the Data & Policy, peer-reviewed, open-access journal published by Cambridge University Press (2024 Impact Factor: 2.7, Q2 Public Administration; CiteScore: 3.5, Q1 Social Sciences Miscellaneous) following the conference. Read more about the integrated peer review process on this page. https://www.cambridge.org/core/journals/data-and-policy/information/author-instructions/preparing-your-materials#conference

•Panel Proposals: Panel proposals should offer in-depth discussions on key issues aligned with the conference theme. Proposals should aim to provide actionable insights and foster dialogue that reflects both regional and global contexts.

For detailed information on submission types, the conference committee, and important dates, we encourage you to visit our conference website. https://dataforpolicy.org/data-for-policy-2026/

Submission links can be found on this page: https://dataforpolicy.org/2026-submission-guidelines/

We eagerly anticipate receiving your exciting and innovative submissions that will enrich Data for Policy 2026 and contribute to shaping the future of AI-enabled governance. Join us at UPF Barcelona in 2026!

For inquiries or further information about local arrangements and registrations, please contact dfp26@upf.edu

For submissions, please contact team@dataforpolicy.org

with kind regards,

Data for Policy team on behalf of

Manuel Portela, Carlos (Chato) Castillo , Vladimir Estivill-Castro, Migle Laukyte and Antoni Rubi-Puig from Universitat Pompeu Fabra
Data for Policy 2026 (DfP’26) Conference Chairs

Zeynep Engin (Data for Policy CIC), Jon Crowcroft (University of Cambridge and The Alan Turing Institute), and Stefaan Verhulst (New York University)
Data for Policy Conference – General Chairs

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Conference Programme Committee:

Susan Ariel Aaronson, George Washington University, USA
Fola Adeleke, The Global Center on AI Governance, South Africa
Rossella Arcucci, Imperial College London, UK
Omar Isaac Asensio, Georgia Institute of Technology, USA
He Bin, Tongji University, China
Tuba Bircan, Vrije Universiteit Brussel, Belgium
Ana Brandusescu, McGill University, Canada
Ana Maria Bustamante Duarte, Universidad de Los Andes, Colombia
Igor Calzada, University of the Basque Country, Spain
Natalia Carfi, Open Data Charter, Argentina
Lawrence Cheung, The Chinese University of Hong Kong (CUHK), Hong Kong
Joep Crompvoets, KU Leuven, Belgium
Ebinezer Florano, The University of the Philippines, The Philippines
Sarah Giest, Leiden University, The Netherlands
Yang Han, The University of Hong Kong (HKU), Hong Kong
Regina Hu?ková, Pavol Jozef Šafárik University in Košice, Slovakia
Ahmed Dooguy Kora, L’Ecole Supérieure Multinationale des Télécommunications, Senegal
Jacqueline C.K. Lam, University of Hong Kong (HKU), Hong Kong
Victor OK Li, The University of Hong Kong (HKU), Hong Kong
Canhui Liu, University College London, UK
Justin Longo, University of Regina, Canada
Claudia Abreu Lopes, United Nations University, Malaysia
Jock Martin,The European Environment Agency, Denmark
Gianluca Misuraca, AI4Gov, Universidad Politécnica de Madrid, Spain
Francesco Mureddu, The Lisbon Council, Belgium
Ines Neves, Universidade de Porto, Portugal
David, Love Opeyemi, University of Johannesburg, South Africa
Marta Poblet, RMIT University; The Data Tank, Belgium
Paula Rodriguez Müller, European Commission Joint Research Centre (JRC), Belgium
Vania Sena, The University of Sheffield, UK
Sara Thabit, European Commission Joint Research Centre (JRC), Italy
Evren Tok, Hamad Bin Khalifa University, Qatar
Gaby Umbach, Robert Schuman Centre for Advanced Studies, European University Institute, Italy
Genoveva Vargas-Solar, CNRS, France-Mexico
Masaru Yarime, The Hong Kong University of Science and Technology, Hong Kong

https://dataforpolicy.org/data-for-policy-2026/

team@dataforpolicy.org

Data for Policy team