Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia.

Journal: Journal of Alzheimer's disease : JAD
PMID: 39956979

Abstract

Digital health innovations hold diagnostic and therapeutic promise but may be subject to biases for underrepresented groups. We explored perceptions of using artificial intelligence (AI) diagnostics for dementia through a focus group as part of the Automated Brain Image Analysis for Timely and Equitable Dementia Diagnosis (ABATED) study. Qualitative feedback from a diverse public engagement group indicated that cultural variations in trust and acceptability of AI diagnostics may be an unrecognised source of real-world inequity. Efforts focused on the adoption of AI diagnostics in memory clinic pathways should aim to recognise and account for this issue.

Authors

  • Avinash Chandra
    Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
  • Kaviya Senthilvel
    School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.
  • Rifah Anjum
    Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
  • Ijeoma Uchegbu
    Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK; Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, Queen Mary University of London, London, UK.
  • Laura J Smith
    Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
  • Helen Beaumont
    AINOSTICS LTD, 3 Hardman Square, Spinningfields, Manchester, UK.
  • Reshma Punjabi
    ABATED Study Lay Steering Committee Member, UK.
  • Samina Begum
    ABATED Study Lay Steering Committee Member, UK.
  • Charles R Marshall
    Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK; Neurology Department, Barts Health NHS Trust, London, UK. Electronic address: charles.marshall@qmul.ac.uk.

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