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.

About AI Policy Lab

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Question Zero: Why Responsible AI Begins Before AI Adoption

Tatjana Titareva (AI Policy Lab, Umeå University), Jason Tucker (Institute for Futures Studies & AI Policy Lab, Umeå University), Rachele Carli (AI Policy Lab, Umeå University), Viktoriia Movchan (AI Policy Lab, Umeå University), Virginia Dignum (AI Policy Lab, Umeå University)
Abstract The Question Zero (Q0) Self-Assessment Tool for Responsible AI, developed by the AI Policy Lab at Umeå University, supports organisations in posing foundational questions before adopting AI. Grounded in…

Is Simulated Evidence Still Evidence? A Warrant-Based Policy for Governing Synthetic Data

Christopher Schwartz (AI Policy Lab Fellow)
Executive Summary Generative AI can produce data that looks like a record of the world without being one: a scan with no patient behind it, a measurement of no event….

Fairness inside and out: A situated approach to algorithmic allocation in complex sociotechnical systems

Bertilla Fabris (AI Policy Lab, Department of Computing Science, Umeå University, Umeå, Sweden), Mayesha Tasnim (Civic AI Lab, Socially Intelligent Artificial Systems, Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands). Note: all authors contributed equally to this work.
Abstract This article outlines a framework for modeling and simulating complex sociotechnical systems in which an allocation mechanism acts as the interface (and sometimes a barrier) between the public and…
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