Long-Term Trends in the Public Perception of Artificial Intelligence

By Ethan Fast, Eric Horvitz. AAAI Conference on Artificial Intelligence, 2016

433 citations recorded by the source corpus.

Analyses of text corpora over time can reveal trends in beliefs, interest, and sentiment about a topic. We focus on views expressed about artificial intelligence (AI) in the New York Times over a 30-year period. General interest, awareness, and discussion about AI has waxed and waned since the field was founded in 1956. We present a set of measures that captures levels of engagement, measures of pessimism and optimism, the prevalence of specific hopes and concerns, and topics that are linked to discussions about AI over decades. We find that discussion of AI has increased sharply since 2009, and that these discussions have been consistently more optimistic than pessimistic. However, when we examine specific concerns, we find that worries of loss of control of AI, ethical concerns for AI, and the negative impact of AI on work have grown in recent years. We also find that hopes for AI in healthcare and education have increased over time.

Subfields: Cognitive Neuroscience, Safety Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/f35672f107fad36ddb958854aa5f71817e0575c6

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Citations in the corpus

Initial validation of the general attitudes towards Artificial Intelligence Scale (2020, positive): “In contrast, Fast and Horvitz (2017) analysed news reports in the New York Times on AI over three decades, and noted increased reporting from 2009, with a general increase in optimism in the reporting, yet also with marked increases in concerns (e.g. loss of control, ethical issues, impact on work).”
The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust (2022, background): “…information technologies, with different perceived advantages, concerns, and risks (e.g., Anderson et al., 2018; Carrasco et al., 2019; Cave et al., 2019; Edelman, 2019; Fast & Horvitz, 2017; Royal Society Working Group, 2017, Stephanidis et al., 2019; Triberti et al., 2021; Zhang & Dafoe, 2019).”
What is AI Literacy? Competencies and Design Considerations (2020, methodology): “The sentiment of discussion about AI has become more optimistic over time, although coverage of certain issues has become pessimistic recently (e.g. impact on work, loss of control of AI, ethical concerns) [57].”
Artificial Intelligence and the Public Sector—Applications and Challenges (2018, background): “While, the social debate about AI and impacts on society has become more intense and has rather moved toward a positive end in recent years, certain concerns such as losing control over AI, ethical worries, and the negative impact on workforce have increased (Fast & Horvitz, 2017).”
What to expect when you’re expecting robots: Futures, expectations, and pseudo-artificial general intelligence in UK news (2020, background): “Despite the established literature on coverage of emerging technologies, seven decades of scholarship on AI, and strong evidence that news coverage of artificial intelligence has increased recently (Fast and Horvitz, 2017), there remain few systematic or empirical studies of media coverage of AI.”
Talking AI into Being: The Narratives and Imaginaries of National AI Strategies and Their Performative Politics (2021, background): “Here, business actors feature much more often in AI reporting than other stakeholders (Brennen, Howard, and Nielsen 2018; Chuan, Tsai, and Cho 2019; Fast and Horvitz 2017).”
Transparency in artificial intelligence (2020, background): “On the one hand, AI indeed is a contested concept that lacks clear consensus, both in computer science (Monett, Lewis & Thórisson, 2020), law (Martinez, 2019) and the public perception (Fast & Horvitz, 2017).”