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Data in the Making: Development and Implementation of Communicative AI Systems in Higher Education Institutions

PhD projekt of Paula Goerke

The dissertation examines the complex processes of data creation and processing in the development of communicative AI systems within higher education institutions. Based on the premise that it is crucial to examine not only the effects of technological systems but also to understand their underlying algorithms and architectures, and building on Bowker (2005) and Gitelman (2013), who argue that data is constructed rather than found (“Data is made, not found”), the research analyzes how hybrid figurations emerge in universities through the intertwining of data practices, system development, and institutional frameworks.

The research focuses on four central questions: Who makes which data-related decisions in the development of communicative AI systems? How is data collected, processed, and implemented in software development? What gaps emerge between intended and actual data usage? And how is communicative AI governed through institutional governance structures?

Drawing on critical perspectives from Selwyn et al. (2023), Bates et al. (2020), and Baecker (2019) regarding questions of responsibility, justice, and transparency in AI systems, the dissertation contributes to critical discussions about responsible AI development. Particular attention is paid to questions of fairness, transparency, and accountability in the integration of AI systems into educational contexts. The work provides empirical insights into the sociotechnical realities of AI development in higher education and demonstrates how institutional structures and data practices influence the design and implementation of communicative AI systems.

The study reveals how organizational and sociotechnical circumstances directly influence AI system development, from data selection for model training to governance structures that shape development processes. By examining these “data in the making” processes informed by Kitchin (2021) and the understanding of co-evolutionary relationships between data and development, the dissertation offers valuable perspectives for future implementation approaches and contributes to theory building in informatics by understanding data and algorithms not merely as technological artifacts, but as phenomena embedded in and shaped by figurations.

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• Paula Goerke