Public Perceptions of Artificial Intelligence and Robotics in Medicine

Abstract

Objective To understand better the public perception and comprehension with medical technology such as artificial intelligence and robotic surgery. Additionally, to identify sensitivity to, and comfort with, the use of AI and robotics in medicine a in order to ensure acceptability and quality of counseling and to guide future development. Subjects and Methods A survey was conducted on a convenience sample of visitors to the Minnesota State Fair (n = 264). The survey investigated participant beliefs on the capabilities of AI and robotics in medicine and their comfort with such technology. Participants were randomized to receive one of two similar surveys. In the first a diagnosis was made by a physician and in the second by an AI application in order to compare confidence in human and computer-based diagnosis. Results The median age of participants was 45 (IQR 28-59), 58% were female (n=154) vs. 42% male (n=110), 69% had completed at least a bachelor’s degree, 88% were Caucasian (n=233) vs. 12% ethnic minorities (n=31) and were from 12 states in the US with most from the Upper Midwest. Participants had nearly equal trust in AI vs. physician diagnoses, however, they were significantly more likely to trust an AI diagnosis of cancer over a doctor’s diagnosis when responding to the version of the survey that suggested an AI could make medical diagnosis (p = 9.32e-06). Though 55% of respondents (n=145) reported they were uncomfortable with automated robotic surgery the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already being performed. Almost all (94%) stated they would be willing to pay for an AI to review their medical imaging, if available. Conclusion Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally expressed concern with surgical AI, but mistakenly believe it is already happening. As AI applications make their way into medical practice, health care providers should be cognizant of patient misconceptions and the sensitivity that patients have to how such technology is represented.

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