Regulating AI/ML-enabled medical devices in the UK

Phoebe Li, Robin Williams, Stephen Gilbert, Stuart Anderson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The recent achievements of Artificial intelligence (AI) open up opportunities for new tools to assist medical diagnosis and care delivery. However, the optimal process for the development of AI is through repeated cycles of learning and implementation that may pose challenges to our existing system of regulating medical devices. Product developers face the tensions between the benefits of continuous improvement/deployment of algorithms and of keeping products unchanged to collect evidence for safety assurance processes. The challenge is how to balance potential benefits with the need to assure their safety. Governance and assurance requirements that can accommodate the live or near-live machine learning (ML) approach will be needed soon, as it is an approach likely to soon be of high importance in healthcare and in other fields of application. We have entered a phase of regulatory experimentation with various novel approaches emerging around the world. The process of social learning is not only about the application of AI but also about the institutional arrangements for its safe and dependable deployment, including regulatory experimentation, likely within sandboxes. This paper will reflect on the discussions from two recent Chatham House workshops on regulating AI in software as a medical device (SaMD), hosted by the UKRI/EPSRC project on 'Trustworthy Autonomous Systems: Regulation and Governance' node, with a special focus on the recent regulatory attempts in the UK and internationally.
Original languageEnglish
Title of host publicationTAS '23
Subtitle of host publicationProceedings of the First International Symposium on Trustworthy Autonomous Systems
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9798400707346
Publication statusPublished - 11 Jul 2023
Event1st International Symposium on Trustworthy Autonomous Systems, TAS 2023 - Edinburgh, United Kingdom
Duration: 11 Jul 202312 Jul 2023

Publication series

NameACM International Conference Proceeding Series


Conference1st International Symposium on Trustworthy Autonomous Systems, TAS 2023
Country/TerritoryUnited Kingdom

Keywords / Materials (for Non-textual outputs)

  • Artificial Intelligence (AI)
  • Artificial Intelligence-enabled Medical Device (AIeMD)
  • autonomous systems
  • regulation
  • Software as a Medical Device (SaMD)


Dive into the research topics of 'Regulating AI/ML-enabled medical devices in the UK'. Together they form a unique fingerprint.

Cite this