Research Agenda
My research concentrates on three empirical areas. These are algorithmic markets, professional work and ethics, and public-sector AI governance. I draw on economic sociology, science and technology studies, and the sociology of professions to analyze how algorithmic systems are made workable and legitimate in markets, organizations, and public institutions.
Workstreams #
Algorithmic Markets
How do algorithmic systems take root in some market contexts and not in others, and what does this mean for people's life chances?
- Uneven algorithmization and the dynamics that shape why some algorithms take root in organizations and reshape fields, while others fail to gain traction.
- A focus on markets that shape people's life chances, including insurance, credit, and the financial sector.
- Particular attention to moral markets, where legitimation is a central principle of market exchange relations.
Professional Work, Ethics, and Authority
How do professional cultures and ethical frameworks shape algorithmic practice, and how is AI reshaping professional expertise and boundaries?
- How professional cultures and ethical frameworks shape practice within algorithmic markets.
- How AI and generative AI alter professional expertise, shift professional boundaries, and reshape collaboration within organizations and markets.
- Empirical focus on data scientists as a novel profession, operating in more fluid and less institutionalized ways than established professions.
Public-Sector AI Governance
How do states orchestrate AI development, and how do public-private coalitions enable AI to scale beyond pilot projects?
- The infrastructures, coalitions, and agreements between private and public actors that shape the co-constitution of technology and society.
- How states orchestrate the development and scaling of AI systems beyond pilot projects.
- How Nordic countries and other AI middle powers establish visions of a common good and shape what an AI society can become.
Research Pipeline #
- ProjectInfrastructuring public-sector AI, where I analyze state orchestration of AI initiatives
- ArticleA research article on the comparative study of Nordic national AI initiatives
- PolicyConsultative expert work at EIOPA and co-authoring a report on data use in insurance
- ProjectInsurance infrastructures of risk management at the nexus of banks and public authorities, focusing on severe-weather events
- ProjectState orchestration of AI development in Denmark
- MethodsMethodological work on studying AI orchestration as infrastructure, and its relationship to controversy studies
Methods #
My projects use mixed methods including interviews, ethnographic observation, document analysis, and quantitative techniques such as statistical modelling, network analysis, and multiple correspondence analysis.