Informatics Seminar Series
Spring Quarter 2023

Friday, May 12, 2023

“Confronting Differential Power in Data – Designing Futures of Public Technologies”

Naja Holten Møller
Associate Professor, Department of Computer Science
University of Copenhagen

Data tracking in the workplace is transforming society and the relationship between the public sector, its employees and the people whom it serves. Understanding the mechanisms for when public sector employees deem tracking of their work acceptable is critical for supporting public technology development, the associated decision-making processes and the resulting changes in the organization of work. After all, in the datafied public sector, both citizens and public servants can be seen as “caseworkers”. My research into the datafication of work is immediately relevant for understanding how human- and democratic values can become at risk if we do not attend to the fact that usage of data as a basis for automation and AI can be a rather vague reflection of reality. A responsible approach to technology design for the public sector, I argue, including the use of AI and automation, lies in the acknowledgement of the potential risks (e.g., bias) both at the level of large datasets and due to individual decisions (e.g., caseworkers and other street-level bureaucrats) that come to form the “ground truth” for the subjects of decisions on public services.

Naja Holten Møller is an expert on Computer-Supported Cooperative Work (CSCW) in complex, professional work domains. Her research unfolds through a deep engagement with issues of responsibility, friction and the enactment of fairness in technology use- and design. Her work draws on participatory- and empirical methods in theoretical CSCW and HCI. It explores how adaptive data-driven technologies introduce continual forms of change for bureaucracies and public decision-, but also for citizens and others who engage with these work processes. In this context, her work raises questions about the role of professional discretion as automation is introduced to decision-making. Recently, she has turned her attention to the challenges and opportunities opened up by the use of large datasets and algorithms to optimize work in the future workplace. She is the founder of the Confronting Data Co-lab (

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