Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 17, 2024
Date Accepted: Feb 4, 2025
Public awareness and attitudes toward the use of artificial intelligence in pathology research and practice: results from a nationally representative UK survey.
ABSTRACT
Background:
This last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in healthcare. One of the most promising areas of research, and potential clinical utility, is in pathology. Whilst the value of using AI in pathology to improve efficiency and accuracy of diagnosis cannot be underestimated, there are several challenges in the development and implementation of such technologies, notably public support for the use of AI to assist in a pathological diagnosis and support for the use of healthcare data and tissues to train pathology algorithms.
Objective:
To investigate public awareness and attitudes towards the use of AI in pathology research and practice.
Methods:
A sample nationally representative of the UK population was recruited via Prolific (n = 1518) and a cross-sectional online mixed methods survey assessed public awareness and attitudes towards the use of AI in pathology
Results:
Quantitative data indicated that awareness was low with only 24% somewhat/moderately aware of AI being developed for use in pathology. Most did not support a diagnosis of cancer (60%) or of biomarkers (46%) being made by AI only. However, the vast majority (97%) supported a diagnosis being made by a pathologist with the assistance of AI. The odds of supporting use of AI in cancer diagnosis and management were higher for men (OR: 1.34). Greater awareness (OR: 1.25), greater trust in data security and privacy protocols (OR: 1.04), and more positive beliefs (OR: 1.27) also increased support, whereas identifying more risks reduced the likelihood of support (OR: 0.80). Three main themes emerged from the qualitative data: Bringing the public alongside; The human in the machine; More hard evidence needed; indicating conditional support for AI in pathology subject to human oversight of AI in decision making; robust oversight measures for data handling and protection; and hard evidence of the benefit and effectiveness of AI.
Conclusions:
There was a low level of awareness of the potential use of AI in pathology, yet respondents were positive and indicated a high level of conditional support for its use. Challenges remain in addressing the concerns of certain demographic populations along with apprehension about the access and use of healthcare data by private organisations.
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