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Evidence-based healthcare innovation in the age of AI

In THIS Institute and Homerton College’s 2025 annual lecture, Niels Peek explores the evolution of AI in healthcare – from early rule-based systems to machine learning and the rapid rise of ambient voice technology.
Yunjung Kim
Yoon Kim
Communications and Engagement Coordinator
Mary Dixon-Woods (left), Director of THIS Institute, and Niles Peek (right), Professor of Data Science and Healthcare Improvement, sit on chairs at the front of the Great Hall at Homerton College, holding microphones and smiling while addressing an audience during Q&A.

Niels Peek, Professor of Data Science and Healthcare Improvement, giving a lecture in front of a wooden podium at THIS Institute and Homerton College's annual lecture.

In April 2025, THIS Institute and Homerton College welcomed guests back to the Great Hall for the second edition of their annual lecture. The evening brought together friends and key stakeholders for a thought-provoking talk by Niels Peek, Professor of Data Science and Healthcare Improvement at THIS Institute, on evidence-based healthcare innovation in the age of AI.

Reflecting on 25 years of progress, Niels explored how AI in healthcare has evolved – from early rule-based systems to modern machine learning and ambient voice technology. He noted that while traditional AI has delivered modest improvements in clinical decision-making, predicting success remains difficult. Meanwhile, the potential of some more recent developments in AI remains largely unproven in practice.

Niels highlighted an important distinction with his area of research: while tech developers focus on high-stakes tasks like diagnosis, many clinicians are looking for support with routine work like summarising consultations. As he put it, meaningful integration of AI into healthcare still lags far behind the number of tools being developed.

It may be some time before the benefits of AI are fully realised in healthcare, and managing the inherent risks may be an ongoing challengeBut if tasks like admin and documentation, that computers are so good at, can support clinicians in doing what they do best – talking to patients and making clinical decisions – good evidence to support the progress of AI is vital.

Scroll down to watch the full lecture recording and more photos from the evening.

Watch the full lecture

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