Date: Wednesday December 4th 2024
Time: 2:00 p.m.-4:00 p.m.
Place: Odense Campus, room U28a
Register: Open event, no registration required
Pieces of an AI
Teacher Dorthe Brogård Kristensen, Department of Business Management, SDU
The health workforce crisis in Europe is often compared to a “time bomb” due to the convergence of challengesnotably post-COVID budgetary constraints, the aging of the population, the shortage of health professionals and the general crisis of health workers, which pose a threat to long-term stability. In response to this complex scenario, Policymakers see AI technologies as a potential solution for better data-driven decisions and to optimize the social protection and healthcare sector. The hope and promise is that AI systems will be able to alleviate workloads and increase efficiency.
This conference will present a case study focused on AI implementation in radiology, particularly in breast cancer screening. The goal is to analyze the arrangement of forms of human/machine expertise as well as emerging frictions and challenges. Despite the dominant optimistic portrayal of AI in media and political discourse, the actual reality of its implementation is much greater. complex. While AI solutions are considered crucial and inevitable, the debates are accompanied by considerable, often unexplored, uncertainties. AI systems operate and produce results and decisions in ways that seem obscure (Burrell 2016). Additionally, studies indicate that contrary to popularized images of a future where AI replaces human workers, automated systems require human assistance and workarounds to operate, even though this human labor is often rendered invisible (Bruun & Krause 2022; In this context, the article aims to reconstruct different parts of this complex reality, englobal interpretations of clinical evidence, as well as institutional skills, workflow, and decision-making and management.
References
Amooré, L. (2023). Machine learning policy orders. Journal of international studies, 49(1): 20-36.
Bruun, M. and Krause-Jensen, J. (2022). Inside technological organizations: imaginaries of digitalization at work. In The Palgrave Handbook of the Anthropology of Technology. pp. 485-505. Singapore: Springer Nature Singapore.
Burrell, J. (2016). How the machine “thinks”: Understanding opacity in machine learning algorithms. Big data and society, 3(1): 1-12.
Ruckenstein, M. and Turunen, LLM (2020). Rehumanizing the platform: content moderators and the logic of care. New media and society, 22(6): 1026-1042.
