mlsanityData to 14 Oct 2026

Long-Term Trends in the Public Perception of Artificial Intelligence

arXiv 1609.04904 ↗First posted 16 Sep 2016cs.CL cs.AI cs.CYcited by 22

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Abstract (arXiv)

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.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Sep 2016.

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Citing papers per year: 2021: 1; 2022: 2; 2023: 3; 2024: 9; 2025: 4; 2026: 3.

22 papers.

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  1. 2024AnthroScore: A Computational Linguistic Measure of Anthropomorphismcited by 27
  2. 2023Automated Claim Matching with Large Language Models: Empowering Fact-Checkers in the Fight Against Misinformationcited by 19
  3. 2022Warmth and competence in human-agent cooperationcited by 11
  4. 2023Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trustcited by 9
  5. 2024Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysiscited by 7
  6. 2023Learning to Prompt in the Classroom to Understand AI Limits: A pilot studycited by 6
  7. 2024How ChatGPT Changed the Media's Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semanticscited by 5
  8. 2024AI on AI: Exploring the Utility of GPT as an Expert Annotator of AI Publicationscited by 4
  9. 2024Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governancecited by 4
  10. 2024Mapping Public Perception of Artificial Intelligence: Expectations, Risk-Benefit Tradeoffs, and Value As Determinants for Societal Acceptancecited by 3
  11. 2026Not all ANIMALs are equal: metaphorical framing through source domains and semantic framescited by 2
  12. 2021AI Risk Skepticismcited by 1
10 more
  1. 2025Making AI Inevitable: Historical Perspective and the Problems of Predicting Long-Term Technological Changecited by 1
  2. 2022Differentially Private Multi-Party Data Release for Linear Regressioncited by 0
  3. 2024Artificial Intelligence in Brazilian News: A Mixed-Methods Analysiscited by 0
  4. 2024Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AIcited by 0
  5. 2024Cultural Dimensions of AI Perception: Charting Expectations, Risks, Benefits, Tradeoffs, and Value in Germany and Chinacited by 0
  6. 2025Trust, Experience, and Innovation: Key Factors Shaping American Attitudes About AIcited by 0
  7. 2025AI Ethics and Social Norms: Exploring ChatGPT's Capabilities From What to Howcited by 0
  8. 2025Developing and Validating the Arabic Version of the Attitudes Toward Large Language Models Scalecited by 0
  9. 2026Whose Voice Counts? Mapping Stakeholder Perspectives on AI Through Public Submissions to the U.S. Governmentcited by 0
  10. 2026Method, Mind, and Morality: How People Make Sense of Artificial Intelligencecited by 0