The dissertation challenges three common beliefs about artificial intelligence. First, it disputes the view of AI as autonomously learning from data, instead emphasizing the human effort and creativity involved in making AI systems work. Second, it critiques the digital-centric view of AI by drawing attention to the material culture in which AI is embedded—highlighting the role of physical objects, bodily practices, and infrastructure. Third, it questions the assumption that AI is primarily aimed at automating or augmenting knowledge work, showing instead that AI can reconfigure even menial roles in ways that make them central to organizational knowledge production.
Rather than seeing AI as an autonomous, digital tool for automating expertise, Tomislav proposes understanding AI as a sociomaterial system shaped by the practices, artifacts, and bodies involved in its development and use. This perspective foregrounds human learning, the role of physical and sensory practices, and the co-constitution of technologies and organizational roles. It enables us to see AI not as a fixed product, but as an evolving apparatus that reshapes knowledge, labor, and meaning in context-specific ways.
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