AI and Data Governance Minitrack

Description

The rapid adoption of artificial intelligence and data-driven systems across public administration presents profound challenges for governance, accountability, democratic legitimacy, and the rule of law. From algorithmic decision-making in social protection to predictive analytics in public service delivery, governments worldwide are embedding computational systems into the core functions of the state. Yet these transformations raise fundamental questions: How do data practices shape policy outcomes? What governance frameworks can ensure algorithmic systems serve public value while mitigating systemic bias? How do technical choices, from data aggregation to model specification, become de facto policy decisions? And critically, how do existing legal frameworks accommodate, constrain, or fail to address the distinctive characteristics of algorithmic governance?

Governance regimes struggle to govern inference, prediction and automated decision-making at scale. Constitutional principles of due process, equal protection, and procedural fairness require reinterpretation when applied to algorithmic determinations. Meanwhile, the cross-border nature of AI development and the opacity of proprietary systems challenge traditional regulatory sovereignty.

Following the spirit of the maintrack theme for this year, we invite rigorous empirical, theoretical, and practical contributions examining the governance of AI and data systems in public sector contexts that contribute for a better society. We welcome research that critically examines the sociotechnical dynamics of algorithmic governance, interrogates the assumptions embedded in public sector data infrastructures, analyses evolving managerial and legal frameworks, and proposes institutional arrangements that allow public administrations to responsibly design, test, deploy, and adapt AI systems over time. We are particularly interested in work that bridges technical, managerial, institutional, and legal perspectives, offering insights into how governance arrangements can address the distinctive challenges posed by AI systems, including opacity, scalability, the reproduction of historical inequalities through ostensibly neutral computational processes, and the fundamental tension between algorithmic logic and institutional reasoning. We invite submissions addressing, but not limited to, the following themes:

• Algorithmic auditing, explainability, and transparency requirements
• Institutional mechanisms for AI and data governance
• Balancing transparency demands with operational constraints
• Data governance for AI effectiveness
• Data sharing, interoperability, and cross-institutional coordination
• How data choices shape algorithmic outputs and policy outcomes
• How algorithmic systems reproduce or amplify social dynamics
• Fairness frameworks in public administration
• Case studies of algorithmic and data governance in the public sector
• Democratic legitimacy of algorithmic governance
• Public participation in AI system design and oversight
• AI-mediated transformation of public service delivery
• Procurement, standards, and AI governance mechanisms
• Domain-specific governance: social protection, criminal justice, healthcare, education, urban planning, taxation
• Cross-sector learning and transferability of governance approaches
• Adaptive governance approaches, e.g. sandboxes, pilots, and learning-based regulation

The papers submitted to this minitrack must be new and unpublished. We welcome papers from different settings and sectors in digital government and look more for innovative and creative analyses than best practices. We also give precedence to strong conceptual and empirical analysis (both qualitative and quantitative) over descriptive cases or opinion pieces.

Authors of selected papers will be invited to submit an extended version of their conference paper to the ACM Journal Digital Government Research and Practice after presentation at the conference.

Minitrack Leaders

Gianluca Misuraca is a Senior Scientist at the European Commission's Joint Research Centre where, since 2009, he is conducting research in the area of ICT for governance and social inclusion. Before joining the European Commission Gianluca was a Research Associate at the Ecole Polytechnique Fédérale de Lausanne (EPFL) where between 2005 and 2008 he has been the Managing Director of the Executive Master in eGovernance conducted by EPFL in collaboration with prestigious institutions worldwide. Gianluca's background is economics with focus on the interface between ICTs and public sector innovation. He holds a Diploma of Specialisation in European Union Economics and Law, and in Security Management, an Executive Master in eGovernance and a Ph. D in Management of Technology from EPFL. He is a recognised scholar with many publications in the field of Information Society development.

Luis Felipe Luna-Reyes is a Professor of Public Administration and Policy at the University at Albany and a National Academy of Public Administration Fellow. He has been a Fulbright Scholar and he is currently Faculty Fellow at the Center for Technology in Government. He is also a Research Affiliated at the Universidad de las Americas, Puebla and a member of the Mexican National Research System. His research is at the intersection of Public Administration, Information Systems and Systems Sciences. He uses multi-method approaches to contribute to a better understanding of collaboration and governance processes in the development of information technologies across functional and organizational boundaries in government. He is the author or co-author of more than 100 articles published in leading Journals and Academic Conferences.