Pioneering Research in and for AI Policy

Building interdisciplinary and cross-sectorial bridges, developing the tools to understand and govern from a human-centered perspective.

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Image: Mattias Pettersson
Image: Viktoria Movchan

The AI Policy Lab at Umeå University is dedicated to conducting pioneering, fundamental research in the field of artificial intelligence that transcends traditional boundaries.


Our focus is to develop and implement innovative methods and engage in diverse activities that facilitate knowledge exchange.
Our approach is to be swift-footed in responding to immediate challenges within AI Policy, while simultaneously engaging in critical analysis and thoughtful reflection on long-term directions and implications.

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Unequal AI Readiness: Why Digital Inequality Matters for Governing Generative AI in African Universities

Olila Steven (Digital Governance & DPI Researcher, Arizona State University)
1. The Policy Problem Generative artificial intelligence (GenAI) is moving into African higher education faster than many universities can develop coherent rules for its use. Students and staff are already…

Operationalising AI Ethical Principles in Higher Education with the UNESCO Recommendation on the Ethics of Artificial Intelligence by Policy Makers and Global Universities

Tatjana Titareva (AI Policy Lab, Umeå University), Grace Thomson (Center for AI and Digital Policy (CAIDP)), Irēna Barkāne (University of Latvia), Assel Csonka-Stambekova (Independent Researcher), Yixin Dai (Tsinghua University), Chris Glass (Boston College), Fatima Roumate (Mohammed V University in Rabat), Benjamin Selznick (James Madison University)
Executive summary The rapid use of artificial intelligence (AI) tools in higher education creates new governance challenges. Universities worldwide face growing concerns about safety, privacy, unfair algorithms and threats to…

Didactics before tools: Redesigning teaching and assessment in the age of generative AI

Eva Mårell-Olsson (Department of Education, Umeå University), Tatjana Titareva (AI Policy Lab, Department of Computing Science, Umeå University)
Abstract Research and policy have become good at naming the cognitive risks that generative AI (GenAI) poses to learning. Namely, detrimental cognitive offloading, metacognitive laziness, and the illusion of competence. What this…
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