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Matthew Gould, NHSX: Regulating AI in health and care

Matthew Gould, Chief Executive Officer at NHSX and a group of senior leaders from regulators recently held a roundtable meeting to discuss AI in healthcare and how the organisation is set to regulate the field.

In a blog post published this week, Gould said “Doing AI right means putting a set of rules around it that will make sure it is done safely, in a way that respects patients’ privacy and keeps the confidence of citizens and staff.”

“Some of those rules already exist – like the 2018 Data Protection Act, for example, which put GDPR into UK law. But there are gaps, lots of regulators on the pitch, and a lack of clarity on both standards and roles.”

“The prize – if we can get this right – is making the UK a world leader in AI for health, giving the NHS the benefits of this new technology safely, reducing the burden on its staff and improving outcomes for patients.”

As part of the blog post, Gould announced some of the agreements that came from the round table meeting with senior leaders:

  • clarity of role, in which MHRA is responsible for regulating the safety of AI systems; HRA for overseeing the research to generate evidence; NICE for assessing their value to determine whether they should be deployed; CQC to ensure that providers are following best practice in using AI; with others playing important roles on particular angles (like the ICO and National Data Guardian on privacy);
  • a joined up approach, in which innovators do not have to navigate between lots of different bodies and sets of rules.  So we will aim to set up a single platform, bringing all the regulatory strands together to create a single point of contact, advice and engagement.  And we will work closely with colleagues across the devolved nations, to make sure that we are joined up across the UK as well;
  • a joined-up regulatory sandbox for AI, which  brings together all the sandbox initiatives in different regulators, and gives innovators a single, end-to-end safe space to develop and test their AI systems;
  • sufficient capability to assess AI systems at the scale and pace required.  This either needs to be in-house in the relevant regulators, particularly MHRA, or through designated organisations working to clear standards set by those regulators and accredited by them;
  • quick progress on working out how we handle Machine Learning.  We know it’s difficult, but we need to develop a proposal, test it, iterate, and keep iterating. There is a lot of brilliant thinking around the world on this – we will gather it, convene experts, practitioners and regulators, and get moving.  As this is – at this stage – a question of policy, we will lead it from NHSX in the first instance before passing a plan to regulators to implement;
  • communication with clinicians, innovators and – crucially – the public.  We need to keep explaining what we are doing, so people with views, expertise and concerns can feed them in rather than feel there is a secret process being done to them.

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