Medical Student Perspectives on the Impact of Artificial Intelligence on the Practice of Medicine
Abstract
Introduction Concerns about radiologists being replaced by artificial intelligence (AI) from the lay media could have a negative impact on medical students' perceptions of radiology as a viable specialty. The purpose of this study was to evaluate United States of America medical students' perceptions about radiology and other medical specialties in relation to AI.Methods An anonymous, web-based survey was sent to 32 radiology interest groups at United States medical schools. The survey was comprised of 6 questions assessing medical student perceptions of AI and its potential impact on radiology and other medical specialties. Responses were voluntary and collected over a 6-month period from November 2017 to April 2018.Results A total of 156 students responded with representation from each year of medical school. Over 75% agreed that AI would have a significant role in the future of medicine. Most (66%) agreed that diagnostic radiology would be the specialty most greatly affected. Nearly half (44%) reported that AI made them less enthusiastic about radiology. The majority of students (57%) obtained their information about AI from online articles. Thematic analysis of free answer comments revealed mostly neutral comments towards AI, however, the negative responses were the strongest and most detailed.Conclusions US medical students believe that AI will play a significant role in medicine, particularly in radiology. However, nearly half are less enthusiastic about the field of radiology due to AI. As the majority receive information about AI from online articles, which may have negative sentiments towards AI's impact on radiology, formal AI education and medical student outreach may help combat misinformation and help prevent the dissuading of medical students who might otherwise consider the specialty.
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Students were apprehensive about GenAI, which may hinder critical thinking and creativity, and the impact of GenAI on job prospects and human values.
“Additionally, students were apprehensive about GenAI, which may hinder critical thinking and creativity, and the impact of GenAI on job prospects (Ghotbi et al., 2022; Gong et al., 2019; Park et al., 2020) and human values (Gillissen et al., 2022; Jha et al., 2022).”
From Students’ voices on generative AI: perceptions, benefits, and challenges in higher education (2023) · cites this paper as Park et al., 2020
The mean respondent years of experience working with AI was only reported in three studies.
“The mean respondent years of experience working with AI was only reported in three studies [7,21,28].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [21]
One study met the NOS criteria for good and 22 studies met the NOS criteria for fair.
“One study met the NOS criteria for good [17] and 22 studies met the NOS criteria for fair [7,8,18–36,37].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [21]
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Emerging Paradigms: Student Perspectives on the Integration of Artificial Intelligence in Education
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Students Are Ready for AI—But Is Medical Education?
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- Authors
- Park, C. J., Yi, P. H., & Siegel, E. L.
- Affiliations
- Pennsylvania State University (US)
- Johns Hopkins University (US)
- University of Maryland Medical Center (US)
- Corresponding author
- Park, Christian J.
- Venue
- Current Problems in Diagnostic Radiology
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 50
- Issue
- 5
- Pages
- 614-619
- ISSN
- 0363-0188 (ISSN-L)
- OpenAlex
- W3037873741
- Cited by
- 167
- References
- 6
- Citations by year
- 2026: 27 · 2025: 35 · 2024: 24 · 2023: 33 · 2022: 20 · 2021: 24 · 2020: 2
- FWCI
- 5.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Current Problems in Diagnostic Radiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
- Social Sciences › Gender Studies › Diversity and Career in Medicine
- Keywords
- artificial intelligence, medical students, perceptions of AI, radiology workforce, specialty choice, artificial intelligence in education, misinformation
- MeSH terms
- Radiologists, Artificial Intelligence, Humans, Radiography, Radiology, Students, Medical, United States
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