Can AI fix the NHS: Pathways to responsible healthcare AI
Venue
Seminar Room 2, Chrystal Macmillan Building and on ZoomDescription
Part of the Controversies in the Data Society 2025 series
A cross-disciplinary series of public lectures and discussion on AI and the datafication of society
AI has potential to transform healthcare, however the use of emergent technologies in that area remains contested. Not only is the promise of AI contested, but how potential benefits might be delivered in the context of digitalisation of the health services. This session focuses on innovation in the NHS and the technical, political, organisational and professional challenges of large scale implementation of computer systems, including the latest promises of AI.
In this session, we hear perspectives from two of our leading scholars on social dimensions of information technology innovation – Professor Robin Williams, Science, Technology and Innovation Studies (STIS); and Professor Stuart Anderson, School of Informatics.
Speakers
Professor Robin WIlliams
Director of the Institute for the Study of Science, Technology and Innovation, STIS, University of Edinburgh
Domesticating AI in medical diagnosis
Robin Williams is Professor of Social Research on Technology in Science, Technology and Innovation Studies (STIS) at the University of Edinburgh, and Director of the Institute for the Study of Science, Technology and Innovation. His research focuses on the social shaping of technology, highlighting the influence of a variety of actors on the design, implementation and use of ICT. In collaboration with Kathrin Creswell (Usher Institute) he led the independent evaluation of NHS England’s flagship Global Digital Exemplar programme. He is Co-I on the UKRI Research Node on Trustworthy Autonomous Systems Governance and Regulation and UKRI Centre for Doctoral Training on Biomedical AI. His current research focuses on the digital transformation of health and social care and on the safe and sustainable deployment of artificial intelligence in medicine.
- Reading
Robin Williams, S, Anderson, K. Cressell, M. Kannelønning, H. Mozaffar & X. Yang (2024), Domesticating AI in medical diagnosis, Technology in Society
Professor Stuart Anderson
Personal Chair in Dependable Systems, School of Informatics, University of Edinburgh
Stuart Anderson is Professor of Dependable Systems in the School of Informatics. He works on the design and analysis of complex systems and how we ensure they are fit for purpose. Stuart is particularly interested in socio-technical systems, resilience of such systems and how social science and informatics provide a unique perspective on the conception, design, deployment and operation of computer-based systems.
Challenges of Achieving Systemic Adoption of AI in the NHS
AI is touted as a panacea for health systems that are under increasing stress arising from population ageing, ever-increasing costs and innovation in treatments. AI is a generic technology that thrives at scale and has an insatiable demand for high-quality data, and many of the benefits claimed for AI in health and care depend on achieving systemic adoption of the technology. In this talk we consider the challenges of systemic adoption for the NHS considering organisational, infrastructural, regulatory, ethical and operational factors illustrated by examples drawn from deployments in the NHS.
- Recommended Reading
H. Ozalp, P. Ozcan, D. Dinckol, M. Zachariadis, and A. Gawer, ‘“Digital Colonization” of Highly Regulated Industries: An Analysis of Big Tech Platforms’ Entry into Health Care and Education’, California Management Review, May 2022, doi: 10.1177/00081256221094307.
M. Coeckelbergh, ‘Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability’, Sci Eng Ethics, vol. 26, no. 4, pp. 2051–2068, Aug. 2020, doi: 10.1007/s11948-019-00146-8.
S. Gilbert, S. Anderson, M. Daumer, P. Li, T. Melvin, and R. Williams, ‘Learning From Experience and Finding the Right Balance in the Governance of Artificial Intelligence and Digital Health Technologies’, J Med Internet Res, vol. 25, p. e43682, Apr. 2023, doi: 10.2196/43682.