Professor Virginia Dignum
Director
Maja Fjaestad
Adjunct Associate Professor
Tatyana Sarayeva
Project Coordinator
Tatjana Titareva
Staff Scientist – AI Policy and Governance
Jason Tucker
Adjunct Associate Professor
Viktoria Movchan
Project Coordinator
Rachele Carli
Postdoctoral Fellow
Petter Ericson
Staff scientist
Adam Dahlgren Lindström
Postdoctoral Fellow
Leila Methnani
Doctoral Student
RESEARCH FELLOWS (2024-2025)
Elin Kvist
Associate Professor, Department of Sociology, Umeå University
Project: Negotiating Algorithms: Unions, Trust, and Co-determination in Sweden’s Public Sector
The rapid digitalization and automation of workplaces have significantly transformed job requirements and environments, particularly with the advent of artificial intelligence (AI), machine learning, and robotics. Algorithmic management (AM), which supports or replaces managerial decision-making, is increasingly prevalent across various sectors, including the public sector. This study examines the implementation of AM in Sweden’s public sector, focusing on its unique demands and challenges. Despite the potential for increased efficiency and productivity, AM poses significant social, structural, and organizational challenges, particularly in a highly regulated environment that values transparency, accountability, and democratic ideals.
Sweden’s robust industrial relations system, characterized by strong unions and high levels of union membership, plays a crucial role in negotiating the conditions and effects of AM. This research aims to understand how AM can be integrated into public sector organizations without compromising the work environment. It explores the necessary frameworks for co-determination and collective bargaining and identifies the new competencies and skills required by social partners to address AM-related challenges.
The study employs a two-pronged approach: interviews with social partners, including employers and employee representatives, and a Participatory Action Research (PAR) study in collaboration with union and workplace representatives. The findings will contribute to a deeper understanding of how AM can enhance collaboration and adaptability while safeguarding the quality of the work environment.
Henry Lopez Vega
Associate Professor, Umeå School of Business, Economics and Statistics
Project: Västerbotten’s AI Ecosystems: Policy Insights
The purpose of this project is to contribute to Västerbotten’s AI strategy development and research the impact of shared ecosystem leadership and AI policy by investigating multilayer challenges—individual, technological, and regulatory. A central components of the region’s strategy involve strengthening its ecosystem to improve the scope of activities in the sparsely populated region of Västerbotten. So far, in collaboration with Digital Impact North and RISE, two workshops have occurred. The objective of these workshops was to understand the challenges with AI policy and draft a policy brief for Västerbotten. In 2025, Henry is devising the mechanisms to enable shared ecosystem leadership for AI implementation and his framework will be further benefit from interactions at two more workshops with policy makers and organizations both regionally and internationally.
Lars Norqvist
Associate Professor, Department of Political Science, Umeå University
Project: AI that Really Matters for the Leaders – AI in Leadership Practices and Processes in Educational Settings
As emerging forces like AI become increasingly prevalent in society, there arises a need to understand better how this may influence educational leaders’ practices and processes. For instance, the matter of autonomy and whether AI enables proactive steering and leadership, grounded in human values and ethical principles, rather than allowing only technology properties to dictate practices and developments. Educational leaders are expected to embrace new technologies, allowing them to dedicate more time to impactful educational leadership for children and young people. Consequently, educational leaders must develop strategies for evaluating and incorporating new technologies into their practices. However, there is a dearth of research on how AI impacts leadership processes directly. This project focuses on AI’s transformative role in leadership practices within educational settings. The interdisciplinary approach aims to unravel the complexities of AI’s impact on leadership autonomy, accountability, and decision-making processes. By employing surveys and innovative forms of group interviews, the research project seeks to provide actionable insights that can inform policy at various governance levels, aiming to bridge theoretical constructs with practical applications in educational leadership.
Nicole Tong
Fulbright Schuman Grantee, Stanford University
Project: Addressing Gender Bias in the Design of AI Systems
Gender bias in artificial intelligence systems has emerged as a critical concern, with documented cases of algorithmic discrimination against marginalized groups in various domains including recruitment, credit scoring, and healthcare. This paper examines the root causes of gender bias in AI systems, focusing particularly on the role of training datasets and the lack of female representation in AI development. The analysis reveals that biased outcomes stem from multiple factors: unrepresentative data due to women’s limited access to technology, historical prejudices embedded in training data, and text-based gender biases in source materials. To address these issues, we argue that current regulatory frameworks are insufficient and proposes several solutions, including the implementation of feminist perspectives in AI development, increased female representation in the tech industry, and specific regulatory measures such as data augmentation and bias control training. Achieving gender equality in AI systems requires both technical solutions and structural changes in the field’s demographics.
INTERNS (2024-2025)
Dorcas Nyamwaya, The Kenya School of Law
Emaan Khan, University of California
Kevin Harerimana, Carnegie Mellon University Africa. Project: How can AI-driven Educational Systems be Designed to Ensure Accessibility for Diverse Socioeconomic Backgrounds and Students with Disabilities?
Tay Warner-Mackintosh, Philosophy (MA), the University of Edinburgh. Project: Intersections between AI and Homelessness in Scotland.
Tuva Falk, Civil Engineer Programme, Interaction and Design, Umeå University. Project: Designing Responsible AI: The Power of User-Selected Metrics.
CONTACT US
For inquiries regarding the AI Policy Lab, please contact us at contact@aipolicylab.se
AI Policy Lab 