Tor Rolfsen Grønsund

Adjunct assistant professor
Image of Tor Rolfsen Grønsund
Norwegian version of this page
Visiting address Gaustadalléen 23 B Ole Johan Dahls hus 0373 OSLO
Postal address Postboks 1080 Blindern 0316 OSLO

Research interests

My research focuses on the sociotechnical implications of digital technology relating to data, algorithmic, and surveillance phenomena. I'm primarily trained within information systems (IS) and interpretative qualitative research, but my work also is influenced by science and technology studies (STS) and systems science as well as ethnographical and critical research traditions. In my dissertation work, I'm interested in how configurations of humans and algorithms evolve as organizations adopt artificial intelligence (AI) capabilities; how data travel across domains and contexts; how global trade participants leverage data as strategic asset, and how they manipulate satellites and data to protect commercial and political interests. My research interests include:

  • human-AI collaboartion and new forms of interaction and organizing between humans and algorithms, e.g., human-in-the-loop, augmentation, alignment
  • methods and design of human feedback mechanisms in AI/ML systems
  • the power, politics, and strategic implications of global datafication
  • how data both are constructed and construct truths in AI/ML systems
  • the social consequences of AI/ML-powered classification and categorization


In my teaching, I'm passionate about inspiring an entrepreneurial mindset to help bring useful solutions to real-world problems. I prefer taking an experimental, processual, and practice-based approach, and draw on uncertainty as a defining concept of entrepreneurship. Since 2011, my course design originally combined lean startup and business model approaches to new product and market development, and integrates with elements from design thinking, effectuation, affordance theory, jobs-to-be-done, and disruptive innovation in addition to classical strategy and innovation literature.

I'm excited right now about the recent progress in language AI (NLP, deep learning, transformers, LLM's) where domain-adaptation and fine-tuning through humans in the loop emerge as perhaps the operating model of a new wave of startups and data-first companies.

Courses (responsible)

  • ENT4000I - From idea to business (S14-)
  • ENT1000 - Entrepreneurship (F10-F18)

Courses (contributor)

  • ITLED4290 - Technology and innovation management (S15-)


  • Best IS Publication 2020, Association of Information Systems, 2021.
  • Best Paper 2020, Journal of Strategic Information Systems, 2021.
  • Shortlisted outstanding teacher in Norway, Morgenbladet 2016.


  • PhD candidate, Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo
  • MSc, Innovation and entrepreneurship (major in Informatics), Faculty of Mathematics and Natural Sciences, University of Oslo
  • BA, Information Science, Faculty of Social Sciences, University of Bergen
Tags: information systems, datafication, artificial intelligence, human-AI collaboration, AI strategy

Selected publications

Grønsund, T. (2021). Assembling Algorithmic Decision-Making under Uncertainty: The Case of 'Edge Cases' in an Open Data Environment. In Proceedings of the 54th Hawaii International Conference on System Sciences (p. 5657).

Grønsund, T., & Aanestad, M. (2020). Augmenting the algorithm: Emerging human-in-the-loop work configurations. The Journal of Strategic Information Systems29(2), 101614.

Published July 8, 2011 2:21 PM - Last modified Aug. 11, 2022 3:21 PM

Research groups