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Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis

Journal Article


Abstract


  • Background: Healthcare is a rapidly expanding area of application for Artificial Intelligence (AI). Although there is considerable excitement about its potential, there are also substantial concerns about the negative impacts of these technologies. Since screening and diagnostic AI tools now have the potential to fundamentally change the healthcare landscape, it is important to understand how these tools are being represented to the public via the media. Methods: Using a framing theory approach, we analysed how screening and diagnostic AI was represented in the media and the frequency with which media articles addressed the benefits and the ethical, legal, and social implications (ELSIs) of screening and diagnostic AI. Results: All the media articles coded (n = 136) fit into at least one of three frames: social progress (n = 131), economic development (n = 59), and alternative perspectives (n = 9). Most of the articles were positively framed, with 135 of the articles discussing benefits of screening and diagnostic AI, and only 9 articles discussing the ethical, legal, and social implications. Conclusions: We found that media reporting of screening and diagnostic AI predominantly framed the technology as a source of social progress and economic development. Screening and diagnostic AI may be represented more positively in the mass media than AI in general. This represents an opportunity for health journalists to provide publics with deeper analysis of the ethical, legal, and social implications of screening and diagnostic AI, and to do so now before these technologies become firmly embedded in everyday healthcare delivery.

Publication Date


  • 2020

Citation


  • Frost, E. K., & Carter, S. M. (2020). Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis. BMC Medical Informatics and Decision Making, 20(1). doi:10.1186/s12911-020-01353-1

Scopus Eid


  • 2-s2.0-85097407408

Volume


  • 20

Issue


  • 1

Abstract


  • Background: Healthcare is a rapidly expanding area of application for Artificial Intelligence (AI). Although there is considerable excitement about its potential, there are also substantial concerns about the negative impacts of these technologies. Since screening and diagnostic AI tools now have the potential to fundamentally change the healthcare landscape, it is important to understand how these tools are being represented to the public via the media. Methods: Using a framing theory approach, we analysed how screening and diagnostic AI was represented in the media and the frequency with which media articles addressed the benefits and the ethical, legal, and social implications (ELSIs) of screening and diagnostic AI. Results: All the media articles coded (n = 136) fit into at least one of three frames: social progress (n = 131), economic development (n = 59), and alternative perspectives (n = 9). Most of the articles were positively framed, with 135 of the articles discussing benefits of screening and diagnostic AI, and only 9 articles discussing the ethical, legal, and social implications. Conclusions: We found that media reporting of screening and diagnostic AI predominantly framed the technology as a source of social progress and economic development. Screening and diagnostic AI may be represented more positively in the mass media than AI in general. This represents an opportunity for health journalists to provide publics with deeper analysis of the ethical, legal, and social implications of screening and diagnostic AI, and to do so now before these technologies become firmly embedded in everyday healthcare delivery.

Publication Date


  • 2020

Citation


  • Frost, E. K., & Carter, S. M. (2020). Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis. BMC Medical Informatics and Decision Making, 20(1). doi:10.1186/s12911-020-01353-1

Scopus Eid


  • 2-s2.0-85097407408

Volume


  • 20

Issue


  • 1