{
  "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.",
  "authors": [
    {
      "affiliations": [
        "The Alan Turing Institute, London, UK"
      ],
      "name": "Saba Esnaashari"
    },
    {
      "affiliations": [
        "The Alan Turing Institute, London, UK"
      ],
      "name": "Youmna Hashem"
    },
    {
      "affiliations": [
        "The Alan Turing Institute, London, UK"
      ],
      "name": "John Francis"
    },
    {
      "affiliations": [
        "University of Bath, Bath, UK"
      ],
      "name": "Deborah Morgan"
    },
    {
      "affiliations": [
        "The Alan Turing Institute, London, UK"
      ],
      "name": "Anton Poletaev"
    },
    {
      "affiliations": [
        "Zug Institute for Blockchain Research (ZIBR), University of Lucerne, Lucerne, Switzerland"
      ],
      "name": "Jonathan Bright"
    }
  ],
  "title": "Exploring doctors’ perspectives on generative-AI and diagnostic-decision-support systems",
  "uid": "05b3eeac-538d-5b30-8b28-711aeb9f3a23"
}