Do People Favor Artificial Intelligence Over Physicians? A Survey Among the General Population and Their View on Artificial Intelligence in Medicine

Yfke P Ongena,Marieke Haan,Derya Yakar,Thomas C Kwee

doi:10.1016/j.jval.2021.09.004

Abstract

ObjectivesTo investigate the general population’s view on artificial intelligence (AI) in medicine with specific emphasis on 3 areas that have experienced major progress in AI research in the past few years, namely radiology, robotic surgery, and dermatology. MethodsFor this prospective study, the April 2020 Online Longitudinal Internet Studies for the Social Sciences Panel Wave was used. Of the 3117 Longitudinal Internet Studies For The Social Sciences panel members contacted, 2411 completed the full questionnaire (77.4% response rate), after combining data from earlier waves, the final sample size was 1909. A total of 3 scales focusing on trust in the implementation of AI in radiology, robotic surgery, and dermatology were used. Repeated-measures analysis of variance and multivariate analysis of variance was used for comparison. ResultsThe overall means show that respondents have slightly more trust in AI in dermatology than in radiology and surgery. The means show that higher educated males, employed or student, of Western background, and those not admitted to a hospital in the past 12 months have more trust in AI. The trust in AI in radiology, robotic surgery, and dermatology is positively associated with belief in the efficiency of AI and these specific domains were negatively associated with distrust and accountability in AI in general. ConclusionsThe general population is more distrustful of AI in medicine unlike the overall optimistic views posed in the media. The level of trust is dependent on what medical area is subject to scrutiny. Certain demographic characteristics and individuals with a generally positive view on AI and its efficiency are significantly associated with higher levels of trust in AI.

Highlights

Artificial intelligence (AI), which refers to a wide variety of computer-executed tasks that simulate human intelligence, will improve and reshape the future of healthcare tremendously.[1,2,3,4] AI in healthcare, which includes mostly the fields of machine learning and robotics,[1,2,3,4] is rapidly evolving and numerous applications have shown their potential value
From an existing scale on general trust in the implementation of AI in radiology,[15] we developed 3 new scales focusing on trust in the implementation of AI in radiology, robotic surgery, and dermatology
A repeated-measures ANOVA showed a significant effect of the specialty area—that is, radiology, surgery, or dermatology (F [2, 4832] 162.2; P,.010)—on trust in AI

Summary

Introduction

Artificial intelligence (AI), which refers to a wide variety of computer-executed tasks that simulate human intelligence, will improve and reshape the future of healthcare tremendously.[1,2,3,4] AI in healthcare, which includes mostly the fields of machine learning (the use of computer algorithms to perform specific tasks) and robotics,[1,2,3,4] is rapidly evolving and numerous applications have shown their potential value. Recent machine learning studies have shown to either equal or even outperform radiologists in the diagnosis of breast cancer on screening mammography, and dermatologists’ performance in the detection of skin cancer.[5,6,7,8] Parallel to this, many examples of effective robotics-assisted surgery and newer techniques with autonomous robotic systems are underway.[9,10,11] Up until now, the technical development of AI systems has been at the center of attention. Involving the public will set practical conditions on how to put these new promising technologies into effect. This will help predict how people will accept new technology, which provides a feedback loop to developers, thereby increasing the participation of the population.[14]

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