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GenAI Uses and Challenges in Society: A Macro-Level Analysis

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Publicat a:International Journal of Technology, Knowledge and Society vol. 22, no. 1 (2025), p. 99-125
Autor principal: Aminee, Ajmal
Altres autors: Taylor, Joseph
Publicat:
Common Ground Research Networks
Matèries:
Transparency
Accessibility
Internet
Digital literacy
Moral education
Higher education
Marginality
Health services
Generative artificial intelligence
Cultural sensitivity
Fluency
Policy making
Ethics
Adoption
Explainable artificial intelligence
Statistical analysis
Teachers
Mitigation
Access
Infrastructure
Artificial intelligence
Trust
Data analysis
Health care
Hypotheses
Education
Minority groups
Low income groups
Quantitative analysis
Social groups
Educational attainment
Accés en línia:Citation/Abstract
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Resum:Generative Artificial Intelligence (GenAI) is transforming professional, educational, and societal domains, yet its adoption remains uneven, particularly among marginalized and underrepresented groups. This study addresses two core questions: (1) How does GenAI adoption differ across social and demographic groups, and what role does digital literacy play? (2) How can culturally responsive and explainable AI design foster trust, accessibility, and ethical use? Using a mixed-method survey of 542 participants, the study evaluated two hypotheses: first, that adoption rates are lower among marginalized groups due to limited infrastructure and digital literacy; and second, that culturally adaptive, transparent AI systems increase trust and equitable usage. Findings support both hypotheses. Participants aged 26 to 35 with higher education levels and digital fluency were more likely to use GenAI for professional purposes such as data analysis and content generation. In contrast, individuals from lower-income or less-educated backgrounds reported limited access, lower confidence, and heightened ethical concerns. Statistical analysis confirmed a strong correlation between digital literacy and trust in GenAI, while perceived accessibility significantly predicted usage. Ethical and cultural concerns—especially in healthcare, education, and public-sector contexts—emphasized the importance of transparency, explainability, and bias mitigation. This study underscores the urgent need for inclusive GenAI strategies that prioritize equitable access, digital literacy development, and culturally sensitive, explainable design. The findings offer practical insights for global policymakers, developers, and educators working toward responsible and inclusive GenAI integration.
ISSN:1832-3669
DOI:10.18848/1832-3669/CGP/v22i01/99-124
Font:ABI/INFORM Global