Ai literacy in the public sphere: a theory-informed exploratory study

Existing research on Artificial Intelligence (AI) literacy primarily focuses on educational, STEM, business, and institutional settings. A research gap exists in terms of how AI concepts are framed in the public sphere. This study analyzes seventeen (N=17) TED talks from 2020 to 2025 to explore how experts publicly communicate core ideas related to AI. It draws upon a four-factor model of AI literacy that includes the dimensions of knowing and understanding, using and applying, creating and evaluating, and AI ethics. Thematic analysis is used to examine how these four dimensions are reflected in public-facing expert discourse. Results showed that in addition to the four core factors, there were two additional identifiable themes: reflect on and critique AI, and advocacy and lifelong learning. Themes and subthemes are illustrated with examples and quotes capturing how speakers convey key ideas and concerns. This study provides novel insights on how expert-led discourse on AI contributes to deepening public AI literacy.

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Publication Details

Journal
Journal of Artificial Intelligence Machine Learning and Neural Network
Published
2025-11-19
DOI
https://doi.org/10.55529/jaimlnn.52.24.34
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
Controls
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article

Ai literacy in the public sphere: a theory-informed exploratory study

1 citations
Journal of Artificial Intelligence Machine Learning and Neural Network
Ethics and Social Impacts of AI
2.37
article

Ai literacy in the public sphere: a theory-informed exploratory study

article en
1 citations

Abstract

Existing research on Artificial Intelligence (AI) literacy primarily focuses on educational, STEM, business, and institutional settings. A research gap exists in terms of how AI concepts are framed in the public sphere. This study analyzes seventeen (N=17) TED talks from 2020 to 2025 to explore how experts publicly communicate core ideas related to AI. It draws upon a four-factor model of AI literacy that includes the dimensions of knowing and understanding, using and applying, creating and evaluating, and AI ethics. Thematic analysis is used to examine how these four dimensions are reflected in public-facing expert discourse. Results showed that in addition to the four core factors, there were two additional identifiable themes: reflect on and critique AI, and advocacy and lifelong learning. Themes and subthemes are illustrated with examples and quotes capturing how speakers convey key ideas and concerns. This study provides novel insights on how expert-led discourse on AI contributes to deepening public AI literacy.

Journal of Artificial Intelligence Machine Learning and Neural Network(52)
Global Green Synergy (Malaysia) (MY)
Openalex Percentile: Top 8%
Ethics and Social Impacts of AI
2.37
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