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Focal points and blind spots of human-centered AI: AI risks in written online media

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  • Marcell Sebestyén

    (Budapest University of Technology and Economics)

Abstract

There is a strong tendency in prevailing discussions about artificial intelligence (AI) to focus predominantly on human-centered concerns, thereby neglecting the broader impacts of this technology. This paper presents a categorization of AI risks highlighted in public discourse, as reflected in written online media accounts, to provide a background for its primary focus: exploring the dimensions of AI threats that receive insufficient attention. Particular emphasis is dedicated to the ignored issues of animal welfare and the psychological impacts on humans, the latter of which surprisingly remains inadequately addressed despite the prevalent anthropocentric perspective of the public conversation. Moreover, this work also considers other underexplored dangers of AI development for the environment and, hypothetically, for sentient AI. The methodology of this study is grounded in a manual selection and meticulous, thematic, and discourse analytical manual examination of online articles published in the aftermath of the AI surge following ChatGPT’s launch in late 2022. This qualitative approach is specifically designed to overcome the limitations of automated, surface-level evaluations typically used in media reviews, aiming to provide insights and nuances often missed by the mechanistic and algorithm-driven methods prevalent in contemporary research. Through this detail-oriented investigation, a categorization of the dominant themes in the discourse on AI hazards was developed to identify its overlooked aspects. Stemming from this evaluation, the paper argues for expanding risk assessment frameworks in public thinking to a morally more inclusive approach. It calls for a more comprehensive acknowledgment of the potential harm of AI technology’s progress to non-human animals, the environment, and, more theoretically, artificial agents possibly attaining sentience. Furthermore, it calls for a more balanced allocation of focus among prospective menaces for humans, prioritizing psychological consequences, thereby offering a more sophisticated and capable strategy for tackling the diverse spectrum of perils presented by AI.

Suggested Citation

  • Marcell Sebestyén, 2025. "Focal points and blind spots of human-centered AI: AI risks in written online media," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-20, December.
    • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-04814-y
    DOI: 10.1057/s41599-025-04814-y
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    References listed on IDEAS

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    1. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    2. Ashlee Humphreys & Rebecca Jen-Hui Wang & Eileen FischerEditor & Linda PriceAssociate Editor, 2018. "Automated Text Analysis for Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1274-1306.
    3. Anne-Laure Ligozat & Julien Lefevre & Aurélie Bugeau & Jacques Combaz, 2022. "Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Life Cycle Assessment of AI Solutions," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    4. Nguyen, Dennis, 2023. "How news media frame data risks in their coverage of big data and AI," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 12(2), pages 1-30.
    5. Leonie N. Bossert & Thilo Hagendorff, 2023. "The ethics of sustainable AI: Why animals (should) matter for a sustainable use of AI," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(5), pages 3459-3467, October.
    6. Mike S. Schäfer & James Painter, 2021. "Climate journalism in a changing media ecosystem: Assessing the production of climate change‐related news around the world," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 12(1), January.
    7. Bossert, Leonie & Hagendorff, Thilo, 2021. "Animals and AI. The role of animals in AI research and application – An overview and ethical evaluation," Technology in Society, Elsevier, vol. 67(C).
    8. Kai Jia & Nan Zhang, 2022. "Categorization and eccentricity of AI risks: a comparative study of the global AI guidelines," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 59-71, March.
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