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Adjudication committee
- Professor Ingunn Ikdahl, University of Oslo (head of committee)
- Professor Stefan Larsson, Lund University (1. opponent)
- Professor Sofia Ranchordás, Tilburg University (2. opponent)
Chair of defence
Vicedean Eirik Østerud
Supervisors
- Professor Malcolm Langford
- Associate Professor Jon Christian F. Nordrum
- Seksjonssjef Rozemarijn van der Hilst-Ytreland
Summary
The Data-Driven Public Sector: A Critical Assessment of its Framing and Implementation
Data-driven public administration refers to using data and AI to improve how governments make decisions and provide services. It's a new and potentially game-changing shift in how public services are delivered, but there are important questions about how this is being done. Who is making the rules around AI and data? How do governments understand what it means to be "data-driven"? My research looks at these issues in Norway, with lessons that could apply to other countries in Europe, especially in the Nordic and Baltic regions.
Norway is an interesting place to study this because it has strong digital infrastructure, handles a lot of public data, and has high public trust in its government—all factors that make it well-positioned to adopt data-driven governance. However, my research shows that there are significant gaps in how the country understands and implements this transformation. While many see the data-driven public sector as revolutionary, it’s important to look beyond the hype and understand the deeper implications.
The Promise and the Risks of Data-Driven Governance
Many countries prioritize data-driven public administration because it promises a more scientific, fact-based approach to solving problems and improving services. It’s seen as a way to handle uncertainty and deliver better public services. However, this shift also comes with risks. Problems like bias in algorithms, increased surveillance, and less democratic control are emerging concerns. These problems aren’t just about technology; they also arise from how these systems are understood and put into practice.
In Norway, I found that the approach to data-driven governance often focuses too much on the technical potential of AI and data, influenced by private-sector thinking. This view tends to ignore important issues like transparency, accountability, and citizen participation. My research suggests that leaders need to go beyond just talking about the potential of data and AI and start thinking critically about their ethical and societal impacts. Citizens, who are often left out of the decision-making process, should also have a say in how these technologies are used.
Additionally, there’s a gap between the high-level policies and the reality of putting these ideas into action. On the ground, practitioners face many challenges that aren’t addressed in policy discussions.
A Need for a Multidisciplinary Approach
The complexities of data-driven governance require expertise from many different fields. It's not something any one discipline can solve alone. My research emphasizes the need for collaboration between law, technology, society, and public administration to tackle these challenges. It’s crucial that researchers, policymakers, and civil society work together to make sure these technologies are used responsibly and that decisions made today don’t harm citizens or weaken trust in the government.
Another key finding of my research is that there’s no shared definition of what "data-driven" actually means. Different people and institutions understand the term in different ways, which creates confusion about how these systems should be applied. This lack of clarity is a serious issue for good governance.
To address this, I propose a framework to help people better understand what data-driven governance is and how it can be applied. This framework can guide discussions and decision-making, helping governments decide whether they want to completely redesign public services or just improve existing ones with data and AI.
Rethinking Public Administration
The current view in Norway, which sees data-driven initiatives as a "magic bullet" for solving problems, oversimplifies the complexities of public administration. A more thoughtful, balanced approach is needed—one that recognizes the challenges of reform and the importance of context.