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Administrative Sciences
Article . 2024 . Peer-reviewed
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Administrative Sciences
Article . 2024
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Article . 2024 . Peer-reviewed
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Public Anxieties About AI: Implications for Corporate Strategy and Societal Impact

Authors: Michael Gerlich;

Public Anxieties About AI: Implications for Corporate Strategy and Societal Impact

Abstract

This research critically examines the underlying anxieties surrounding artificial intelligence (AI) that are often concealed in public discourse, particularly in the United Kingdom. Despite an initial reluctance to acknowledge AI-related fears in focus groups, where 86% of participants claimed no significant concerns, further exploration through anonymous surveys and interviews uncovered deep anxieties about AI’s impact on job security, data privacy, and ethical governance. The research employed a mixed-methods approach, incorporating focus groups, a survey of 867 participants, and 53 semi-structured interviews to investigate these anxieties in depth. The study identifies key sources of concern, ranging from the fear of job displacement to the opacity of AI systems, particularly in relation to data handling and the control exerted by corporations and governments. The analysis reveals that anxieties are not evenly distributed across demographics but rather shaped by factors such as age, education, and occupation. These findings point to the necessity of addressing these anxieties to foster trust in AI technologies. This study highlights the need for ethical and transparent AI governance, providing critical insights for policymakers and organisations as they navigate the complex socio-technical landscape that AI presents.

Keywords

AI, AI anxiety, JF20-2112, societal perception, AI regulation, trust, ddc:350, public anxieties, ethical AI, Political institutions and public administration (General), artificial intelligence

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Top 10%
Top 10%
gold