Pieces of an AI

Dato: Onsdag, 4. December 2024

Tid: 14:00-16:00

Sted: Campus Odense, lokale U28a

Tilmelding: Åbent event, tilmelding ikke nødvendig

Pieces of an AI

Professor Dorthe Brogård Kristensen, Department of Business Management, SDU

Europe’s health workforce crisis is often likened to a “ticking bomb”, due to the convergence of challenges, including post-COVID budget constraints, an aging population, shortages of healthcare workers, and an overall health workforce crisis, posing a threat to long-term stability. In response to this complex scenario, policymakers view AI technologies as a potential solution for better data-driven decisions and optimizing the welfare and healthcare sector. The hope and promises are that AI systems can alleviate workloads and increase efficiency.

This lecture will present a case study focusing on the implementation of AI in radiology, specifically in breast cancer screening. The aim is to analyse the arrangement of human/ machinic forms of expertise and the emerging frictions and challenges. Despite the prevailing optimistic portrayal of AI in media and political discourse, the actual implementation reality is considerably more complex. While AI solutions are seen as crucial and inevitable, the arguments are accompanied by considerable, often unexplored uncertainties. AI systems operate and produce outputs and decisions in ways that appear obscure (Burrell 2016). Moreover, studies indicate that contrary to popularised images of a future where AI replaces human workers, automated systems require human assistance and workarounds to function, even though this human labour is often rendered invisible (Bruun & Krause 2022; Ruckenstein & Turunen 2020). Against this backdrop, the paper aims to piece together different parts of this complex reality, encompassing interpretations of clinical evidence, as well as skills, workflow and institutional decision-making and management. 

References

Amoore, L. (2023). Machine learning political orders. Review of International Studies, 49(1): 20-36.

Bruun, M. & Krause-Jensen, J. (2022). Inside Technology Organisations: Imaginaries of Digitalisation 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 & society, 3(1): 1-12.

Ruckenstein, M. & Turunen, L. L. M. (2020). Re-humanizing the platform: Content moderators and the logic of care. New media & society, 22(6): 1026-1042.