Literature DB >> 31313979

Sentiment Analysis of the News Media on Artificial Intelligence Does Not Support Claims of Negative Bias Against Artificial Intelligence.

Colin Garvey1, Chandler Maskal1.   

Abstract

Artificial intelligence (AI) is a hot topic in digital health, as automated systems are being adopted throughout the health care system. Because they are still flexible, emerging technologies can be shaped significantly by media representations as well as public engagement with science. In this context, we examine the belief that negative news media coverage of AI-and specifically, the alleged use of imagery from the movie Terminator-is to blame for public concerns about AI. This belief is identified as a potential barrier to meaningful engagement of AI scientists and technology developers with journalists and the broader public. We name this climate of risk perception the "Terminator Syndrome"-not because of its origins in the movie of the same name per se, but because such unchecked beliefs can terminate broad public engagement on AI before they even begin. Using both quantitative and qualitative approaches, this study examined the hypothesis that the news media coverage of AI is negative. We conducted a sentiment analysis of news data spanning over six decades, from 1956 to 2018, using the Google Cloud Natural Language API Sentiment Analysis tool. Contrary to the alleged negative sentiment in news media coverage of AI, we found that the available evidence does not support this claim. We conclude with an innovation policy-relevant discussion on the current state of AI risk perceptions, and what critical social sciences offer for responsible AI innovation in digital health, life sciences, and society.

Keywords:  AI and risk; artificial intelligence (AI); digital health; public engagement; risk governance; technology policy

Mesh:

Year:  2019        PMID: 31313979     DOI: 10.1089/omi.2019.0078

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  2 in total

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

Authors:  Emma K Frost; Stacy M Carter
Journal:  BMC Med Inform Decis Mak       Date:  2020-12-10       Impact factor: 2.796

2.  Promoting engagement with quality communication in social media.

Authors:  Matteo Cinelli; Antonio Peruzzi; Ana Lucía Schmidt; Roberta Villa; Enrico Costa; Walter Quattrociocchi; Fabiana Zollo
Journal:  PLoS One       Date:  2022-10-13       Impact factor: 3.752

  2 in total

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