Public Perceptions of Artificial Intelligence and Robotics in Medicine
To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling. A survey was conducted on a convenience sample of...
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| Veröffentlicht in: | Journal of endourology Jg. 34; H. 10; S. 1041 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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01.10.2020
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| ISSN: | 1557-900X, 1557-900X |
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| Abstract | To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling.
A survey was conducted on a convenience sample of visitors to the MN Minnesota State Fair (
= 264). 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 to compare confidence in human and computer-based diagnosis.
The median age of participants was 45 (interquartile range 28-59), 58% were female (
= 154)
42% male (
= 110), 69% had completed at least a bachelor's degree, 88% were Caucasian (
= 233)
12% ethnic minorities (
= 31) and were from 12 states, mostly from the Upper Midwest. Participants had nearly equal trust in AI
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 that an AI could make medical diagnoses (
= 9.32e-06). Though 55% of respondents (
= 145) reported that they were uncomfortable with automated robotic surgery, the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already happening. Almost all (94%,
= 249) stated that they would be willing to pay for a review of medical imaging by an AI if available.
Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally express concern with surgical AI, but they mistakenly believe that it is already being performed. As AI applications increase in medical practice, health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented. |
|---|---|
| AbstractList | Objective: To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling. Subjects and Methods: A survey was conducted on a convenience sample of visitors to the MN Minnesota State Fair (n = 264). 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 to compare confidence in human and computer-based diagnosis. Results: The median age of participants was 45 (interquartile range 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, mostly 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 that an AI could make medical diagnoses (p = 9.32e-06). Though 55% of respondents (n = 145) reported that they were uncomfortable with automated robotic surgery, the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already happening. Almost all (94%, n = 249) stated that they would be willing to pay for a review of medical imaging by an AI if available. Conclusion: Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally express concern with surgical AI, but they mistakenly believe that it is already being performed. As AI applications increase in medical practice, health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented.Objective: To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling. Subjects and Methods: A survey was conducted on a convenience sample of visitors to the MN Minnesota State Fair (n = 264). 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 to compare confidence in human and computer-based diagnosis. Results: The median age of participants was 45 (interquartile range 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, mostly 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 that an AI could make medical diagnoses (p = 9.32e-06). Though 55% of respondents (n = 145) reported that they were uncomfortable with automated robotic surgery, the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already happening. Almost all (94%, n = 249) stated that they would be willing to pay for a review of medical imaging by an AI if available. Conclusion: Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally express concern with surgical AI, but they mistakenly believe that it is already being performed. As AI applications increase in medical practice, health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented. To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling. A survey was conducted on a convenience sample of visitors to the MN Minnesota State Fair ( = 264). 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 to compare confidence in human and computer-based diagnosis. The median age of participants was 45 (interquartile range 28-59), 58% were female ( = 154) 42% male ( = 110), 69% had completed at least a bachelor's degree, 88% were Caucasian ( = 233) 12% ethnic minorities ( = 31) and were from 12 states, mostly from the Upper Midwest. Participants had nearly equal trust in AI 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 that an AI could make medical diagnoses ( = 9.32e-06). Though 55% of respondents ( = 145) reported that they were uncomfortable with automated robotic surgery, the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already happening. Almost all (94%, = 249) stated that they would be willing to pay for a review of medical imaging by an AI if available. Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally express concern with surgical AI, but they mistakenly believe that it is already being performed. As AI applications increase in medical practice, health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented. |
| Author | Heller, Nick Weight, Christopher Stai, Bethany Tejpaul, Resha McSweeney, Sean Edgerton, Zach Regmi, Subodh Kalapara, Arveen Peterson, Matt Rickman, Jack Papanikolopoulos, Nikolaos Blake, Paul Vasdev, Ranveer Rosenberg, Joel |
| Author_xml | – sequence: 1 givenname: Bethany surname: Stai fullname: Stai, Bethany organization: Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 2 givenname: Nick surname: Heller fullname: Heller, Nick organization: Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 3 givenname: Sean surname: McSweeney fullname: McSweeney, Sean organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 4 givenname: Jack surname: Rickman fullname: Rickman, Jack organization: Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 5 givenname: Paul surname: Blake fullname: Blake, Paul organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 6 givenname: Ranveer surname: Vasdev fullname: Vasdev, Ranveer organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 7 givenname: Zach surname: Edgerton fullname: Edgerton, Zach organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 8 givenname: Resha surname: Tejpaul fullname: Tejpaul, Resha organization: Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 9 givenname: Matt surname: Peterson fullname: Peterson, Matt organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 10 givenname: Joel surname: Rosenberg fullname: Rosenberg, Joel organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 11 givenname: Arveen surname: Kalapara fullname: Kalapara, Arveen organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 12 givenname: Subodh surname: Regmi fullname: Regmi, Subodh organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 13 givenname: Nikolaos surname: Papanikolopoulos fullname: Papanikolopoulos, Nikolaos organization: Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA – sequence: 14 givenname: Christopher surname: Weight fullname: Weight, Christopher organization: Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA |
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