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Research project

COdesigning Trustworthy Autonomous Diabetes Systems (COTADS)

Project overview

COTADS explored how to increase trust of AI used for diabetes management inside and outside clinical settings during life transitions. AI is expected to provide a crucial role in the management of chronic conditions, yet technology-driven solutions are unlikely to be adopted. AI design must consider the complex medical, lifestyle and socio-technical needs at times of uncertainty and life transitions. COTADS brought together people with diabetes, clinicians, and data scientists in a novel co-design process for diabetes risk stratification. Using co-design, provenance, and explainable AI, we enhanced ways to ensure solutions are understandable, transparent, trustworthy, and beneficial.


Lead researcher

Professor Michael Boniface CEng, FIET

Professorial Fellow in Information Techn

Research interests

  • Artifical intelligence for health systems
  • Human centred interactive systems
  • Federated systems management 
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Other researchers

Dr Chris Duckworth PhD, MSci

Senior Enterprise Fellow

Research interests

  • Artificial Intelligence for Health and Wellbeing
  • Explainable Machine Learning
  • Human Centred Interactive Systems
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Mr Jakub Dylag

Research Engineer
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Collaborating research institutes, centres and groups

Research outputs

Christopher Duckworth, Matthew J. Guy, Anitha Kumaran, Aisling Ann O’Kane, Amid Ayobi, Adriane Chapman, Paul Marshall & Michael Boniface, 2022, Journal of Diabetes Science and Technology
Type: article