Lay individuals' perceptions of artificial intelligence (AI)-empowered healthcare systems

被引:1
|
作者
Zhang Z. [1 ]
Genc Y. [1 ]
Xing A. [2 ]
Wang D. [3 ]
Fan X. [4 ]
Citardi D. [1 ]
机构
[1] School of Computer Science and Information Systems, Pace University, New York, NY
[2] Department of Statistics, Florida State University, Tallahassee, FL
[3] IBM Research, X, Cambridge, MA
[4] Institute of Software, Chinese Academy of Sciences, Beijing
关键词
acceptability; artificial intelligence; diagnostic results; healthcare; trust;
D O I
10.1002/pra2.326
中图分类号
学科分类号
摘要
With the recent advances in Artificial Intelligence (AI) technology, patient-facing applications have started embodying this novel technology to deliver timely healthcare information and services to the patient. However, little is known about lay individuals' perceptions and acceptance of AI-driven, patient-facing health systems. In this study, we conducted a survey with 203 participants to investigate their perceptions about using AI to consult information related to their diagnostic results and what factors influence their perceptions. Our results showed that despite the awareness and experience of patient-facing AI systems being low amongst our participants, people had a generally positive attitude towards such systems. A majority of participants indicated a high level of comfortability and willingness to use health AI systems, and agreed AI could help them comprehend diagnostic results. Several intrinsic factors, such as education background and technology literacy, play an important role in people's perceptions of using AI to comprehend diagnostic results. In particular, people with high technology and health literacy, and education levels had more experiences with using AI and tended to trust AI outputs. We conclude this paper by discussing the implications of this work, with an emphasis on enhancing the trustworthiness of AI and bridging the digital divide. © 2020, John Wiley and Sons Inc. All rights reserved.
引用
收藏
相关论文
共 50 条
  • [31] Medical students' perceptions of an artificial intelligence (AI) assisted diagnosing program
    Robleto, Emely
    Habashi, Ali
    Kaplan, Mary-Ann Benites
    Riley, Richard L.
    Zhang, Chi
    Bianchi, Laura
    Shehadeh, Lina A.
    MEDICAL TEACHER, 2024, 46 (09) : 1180 - 1186
  • [32] Navigating ASEAN region Artificial Intelligence (AI) governance readiness in healthcare
    Tun, Hein Minn
    Naing, Lin
    Malik, Owais Ahmed
    Rahman, Hanif Abdul
    HEALTH POLICY AND TECHNOLOGY, 2025, 14 (02)
  • [33] Clinical audit of an artificial intelligence (AI) empowered smile simulation system: a prospective clinical trial
    Adel, Samar M.
    Bichu, Yashodhan M.
    Pandian, Srirengalakshmi Muthuswamy
    Sabouni, Waddah
    Shah, Chandani
    Vaiid, Nikhillesh
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [34] Human Dignity and Artificial Intelligence in Healthcare: A Basis for a Catholic Ethics on AI
    Gozum, Ivan Efreaim A.
    Flake, Chastene Christopher D.
    JOURNAL OF RELIGION & HEALTH, 2024,
  • [35] Artificial Intelligence (AI)
    Kreienberg, Rolf
    Janni, Wolfgang
    Vetter, Klaus
    GYNAKOLOGE, 2021, 54 (07): : 468 - 470
  • [36] 'AI, Artificial Intelligence'
    Mendelsohn, F
    TLS-THE TIMES LITERARY SUPPLEMENT, 2001, (5139): : 20 - 20
  • [37] ARTIFICIAL INTELLIGENCE (AI)
    Robb, Hannah
    AUSTRALIAN LAW JOURNAL, 2024, 98 (03):
  • [38] ARTIFICIAL INTELLIGENCE (AI)
    Layne, Armand
    INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT, 2005, 13 (03): : 179 - 181
  • [39] Surveying current perceptions of artificial intelligence among pediatric healthcare professionals
    Simek, Kelsey A.
    Husain, Ameena N.
    Vesoulis, Zachary A.
    Sullivan, Brynne A.
    Barry, James S.
    Mcadams, Ryan M.
    Moreira, Alvaro G.
    JOURNAL OF PERINATOLOGY, 2024,
  • [40] Patients' Perceptions of Integrating AI into Healthcare: Systems Thinking Approach
    Wang, Bijun
    Asan, Onur
    Mansouri, Mo
    2022 IEEE INTERNATIONAL SYMPOSIUM ON SYSTEMS ENGINEERING (ISSE), 2022,