Science and Technology Studies Department, Rensselaer Polytechnic Institute, Troy, New York, USA.
OMICS. 2020 May;24(5):286-299. doi: 10.1089/omi.2019.0078. Epub 2019 Jul 16.
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 -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 , 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.
人工智能(AI)是数字健康领域的热门话题,因为自动化系统正在整个医疗保健系统中得到采用。由于它们仍然具有灵活性,因此新兴技术可以通过媒体的描述以及公众对科学的参与来进行重大塑造。在这种情况下,我们研究了这样一种观点,即对 AI 的负面新闻媒体报道——特别是据称使用了电影中的图像——是公众对 AI 担忧的原因。这种观点被认为是 AI 科学家和技术开发人员与记者和更广泛的公众进行有意义接触的潜在障碍。我们将这种风险感知氛围命名为“终结者综合征”——并不是因为它起源于同名电影,而是因为这种未经检查的信念可能会在公众对 AI 的广泛参与开始之前就终止。本研究采用定量和定性方法,检验了新闻媒体对 AI 的报道是负面的假设。我们使用 Google Cloud Natural Language API Sentiment Analysis 工具对 1956 年至 2018 年跨越六十年的新闻数据进行了情感分析。与新闻媒体对 AI 的负面报道中的说法相反,我们发现现有证据并不支持这一说法。最后,我们就当前的 AI 风险感知状态进行了创新政策相关的讨论,并探讨了批判性社会科学为数字健康、生命科学和社会中的负责任的 AI 创新提供了什么。