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Exploring doctors' perspectives on generative-AI and diagnostic-decision-support systems

  • Saba Esnaashari
  • , Youmna Hashem
  • , John Francis
  • , Deborah Morgan
  • , Anton Poletaev
  • , Jonathan Bright
  • The Alan Turing Institute
  • University of Lucerne

Research output: Contribution to journalArticlepeer-review

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Abstract

This research presents key findings from a project exploring UK doctors' perspectives on artificial intelligence (AI) in their work. Despite a growing interest in the use of AI in medicine, studies have yet to explore a representative sample of doctors' perspectives on, and experiences with, making use of different types of AI. Our research seeks to fill this gap by presenting findings from a survey exploring doctors' perceptions and experiences of using a variety of AI systems in their work. A sample of 929 doctors on the UK medical register participated in a survey between December 2023 and January 2024 which asked a range of questions about their understanding and use of AI systems. Overall, 29% of respondents reported using some form of AI in their practice within the last 12 months, with diagnostic-decision-support (16%) and generative-AI (16%) being the most prevalently used AI systems. We found that the majority of generative-AI users (62%) reported that these systems increase their productivity, and most diagnostic- decision-support users (62%) reported that the systems improve their clinical decision-making. More than half of doctors (52%) were optimistic about the integration of AI in healthcare, rising to 63% for AI users. Only 15% stated that advances in AI make them worried about their job security, with no significant difference between AI and non-AI users. However, there were relatively low reported levels of training, as well as understandings of risks and professional responsibilities, especially among generative-AI users. Just 12% of respondents agreed they have received sufficient training to understand their professional responsibilities when using AI, with this number decreasing to 8% for generative-AI users. We hope this work adds to the evidence base for policy-makers looking to support the integration of AI in healthcare.

Original languageEnglish
Article numbere101371
JournalBMJ Health and Care Informatics
Volume32
Issue number1
DOIs
Publication statusPublished - 23 Jul 2025

Funding

This work was supported by our Funder under Grant EP/W037211/1.

Keywords

  • Artificial intelligence
  • BMJ Health Informatics

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics
  • Health Information Management

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