Bijona Troqe defends her doctoral thesis, “Human-AI Decision-Making: A Phenomenon-Driven Study in Personalized Medicine“, at Linköping University on September 22.
Abstract
Artificial intelligence (AI) is increasingly being integrated into organizational decision-making, creating new forms of human-AI collaboration. Yet, little is known about how human-AI decision-making unfolds in practice, particularly in complex contexts such as personalized medicine.
This thesis explores human-AI decision-making as an organizational process situated in complex contexts. Using a phenomenon-driven approach and embedded case studies from personalized medicine and data-driven healthcare in Sweden, it examines how humans and AI jointly shape decision-making.
The findings contribute to a multi-level understanding of human-AI decision-making that moves beyond viewing AI as a decision support tool. At the organizational level, AI reshapes attention, search processes, decision premises and routines. At the interactional level, AI becomes meaningful through ongoing sensemaking as actors interpret its outputs and incorporate them into organizational action. At the individual level, AI transforms how professional judgment is formed, exercised, and legitimized, while its outputs are interpreted through existing professional and organizational frames.
Overall, the thesis shows that human-AI decision-making is distributed, situated, and context dependent. It highlights the importance of recognizing fluid human-AI roles and critically reflecting on how AI shapes organizational attention and decision-making in complex environments.
Supervisors
– Nicolette Lakemond, Professor, Department of Management and Engineering, Linköping University
– Gunnar Holmberg, Adjunct Professor, Department of Management and Engineering, Linköping University
– Besma Glaa, Associate Professor, Department of Management and Engineering, Linköping University
Opponent
– Anna Essén, Associate Professor, Department of Entrepreneurship, Stockholm School of Economics
