Artificial intelligence (AI) awareness (2019–2025): A systematic literature review using the SPAR-4-SLR protocol

Artificial intelligence (AI) awareness (2019–2025): A systematic literature review using the SPAR-4-SLR protocol

Artificial intelligence is rapidly transforming society, necessitating comprehensive understanding of stakeholder awareness across cognitive, behavioral, and ethical dimensions. This systematic review examines the evolution of AI awareness research and identifies critical knowledge gaps for future i...

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Bibliographic Details
Main Authors: Zhu Yuxuan, Wan Mohd Hirwani Wan Hussain
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Social Sciences and Humanities Open
Subjects:
AI awareness
Human-AI collaboration
Behavioral theory
Cross-cultural AI
SPAR-4-SLR
Online Access:http://www.sciencedirect.com/science/article/pii/S2590291125005984
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Summary:Artificial intelligence is rapidly transforming society, necessitating comprehensive understanding of stakeholder awareness across cognitive, behavioral, and ethical dimensions. This systematic review examines the evolution of AI awareness research and identifies critical knowledge gaps for future investigation. Using the SPAR-4-SLR protocol augmented by the Seven Research Gaps framework, we analyzed 71 peer-reviewed papers from 2019 to 2025 through integrated theoretical lenses. Results reveal overwhelming emphasis on workforce dynamics in developed regions, with 61 % of studies concentrated in China and the United States, while consumers, investors, and emerging economies remain neglected. We establish AI awareness as a dynamic consciousness process preceding technology adoption behavioral decisions and identify ''job insecurity'' as a dominant theme, alongside systematic ethical deficits in 83 % of studies. Geographic bias toward technologically advanced countries and disciplinary fragmentation limit research generalizability. The findings necessitate international AI governance frameworks, mandatory literacy programs, and standardized assessment tools to ensure equitable global AI adoption and bridge existing technological divides.
ISSN:2590-2911

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