Panel 41

More-than-human medicine? Unpacking the use of Artificial Intelligence (AI) technologies in healthcare settings

Organizers: Manuela Perrotta (1); Alina Geampana (2); Francesco Miele (3)

1: Queen Mary University of London, United Kingdom; 2: Dutham University, United Kingdom; 3: University of Trieste

Topics: Health policies, governance and practices in a postpandemic era; Technoscientific promises, imaginaries and expectations; Algorithmic knowledge, media ecologies and artificial intelligence; Innovation imaginaries, practices and policies

Keywords: medicine, Artificial intelligence, algorithms, biomedical research, healthcare

During the past few years, the (potential) use of Artificial intelligence (AI) technologies in different medical fields has been at the forefront of public debates and conversations. The dominant narrative is imbued of over-optimistic expectations that see algorithmic technologies as able to resolve uncertainties surrounding medical diagnosis and treatment. Central to these narratives is an emphasis on the large amount of data such technologies can process and analyse. However, heightened expectations may often lead to disappointment. The purportedly value-neutral nature of algorithmic technologies has been sharply criticised by the STS literature emphasising their opacity and inscrutability. In addition, studies exploring the use of AI in medical practice have shown that complex dynamics are involved in the delegation of decision-making to algorithms and the reconfigurations needed for new technologies to become embedded in medical work.

Drawing on these premises, this panel aims to explore the multiple and interconnected ways in which AI and algorithmic technologies are contributing to transformations in healthcare and medical expertise. Therefore, we invite (empirical, theoretical, and/or methodological) contributions looking to unpack the use of AI technologies in healthcare practice. Contributions exploring the following topics are especially welcome:

  • The integration of AI to support diagnosis and treatment
  • The relationship between AI and biomedical research and innovation
  • The regulation and governance of AI in biomedical research and innovation
  • The tensions between the introduction of AI in medicine and evidence-based medicine
  • Ethical issues arising from the introduction of AI in medical practice
  • The role of AI in shaping expectations about the future of medicine
  • Implications and consequences of popular narratives of AI systems as outperforming human expertise
  • Engagement of patient groups in the development and use of AI in medicine
  • Digital health technologies, data generation, and transparency of algorithms