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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 10, 2019
Date Accepted: May 31, 2020

The final, peer-reviewed published version of this preprint can be found here:

Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media

Gao S, He L, Chen Y, Li D, Lai K

Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media

J Med Internet Res 2020;22(7):e16649

DOI: 10.2196/16649

PMID: 32673231

PMCID: 7385634

Public Perception of Artificial Intelligence in Medical Care: A Social Media Content Analysis

  • Shuqing Gao; 
  • Lingnan He; 
  • Yue Chen; 
  • Dan Li; 
  • Kaisheng Lai

ABSTRACT

Background:

High-quality medical resources are in high demand worldwide, and the application of artificial intelligence (AI) in medical care may help alleviate the crisis related to this shortage. The healthy development of the medical AI industry depends to a certain extent on whether we have a comprehensive understanding of the public’s views on medical AI. However, public opinion about AI in medical care remains unclear.

Objective:

Using social media, the purpose of this study is to explore the public perception of AI in medical care, including (1) specific topics that the public is concerned about, (2) public attitudes toward AI in medical care and the reasons for them, and (3) public opinion on whether AI can replace human doctors.

Methods:

Through an application programming interface, we collected a dataset from the Sina Weibo platform comprising more than 16 million users and crawled all their public posts from January to December 2017. Based on this dataset, we identified 2,315 posts related to AI in medical care and classified them through content analysis.

Results:

We found three types of topics across the platform: (1) technology and application (42.63%), (2) industry development (30.50%), and (3) impact on society (26.87%). In terms of public attitudes, 59.41%, 34.41%, and 6.17% of the posts expressed positive, neutral, and negative attitudes, respectively. Immaturity of AI technology companies and distrust in them were the two main reasons for the negative attitudes. In terms of public attitudes toward replacing human doctors with AI, 47.50% and 32.50% of the posts expressed that AI would completely or partially replace human doctors, respectively, while 20.00% of the posts expressed that AI would not replace human doctors. Immaturity and inability of medical AI to provide humanistic care were the main reasons for the belief that AI will not completely replace human doctors.

Conclusions:

Our findings indicate that people are most concerned about AI technology and applications, and the public generally has a positive attitude toward medical AI. However, the proportion of those who hold a neutral or opposing attitude toward AI applied in medicine should not be neglected. Lack of trust in AI and the absence of the humanistic care factor are important reasons why people have a negative attitude toward medical AI. We suggest that practitioners may need to pay more attention to promoting the credibility of technology companies and meeting patients’ emotional needs instead of focusing merely on technical issues.


 Citation

Please cite as:

Gao S, He L, Chen Y, Li D, Lai K

Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media

J Med Internet Res 2020;22(7):e16649

DOI: 10.2196/16649

PMID: 32673231

PMCID: 7385634

Per the author's request the PDF is not available.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.