Critical AI Literacy: Preparing Learners for Algorithmic Societies

Khodabin, Melika; Sharifi Poor Bgheshmi, Mohammad Sharif; Movahedzadeh, Forough

doi:10.22059/jcss.2024.102582

Critical AI Literacy: Preparing Learners for Algorithmic Societies

Document Type : Original article

Authors

¹ Department of South-East Asian and Oceanarium Studies, Faculty of World Studies, University of Tehran, Tehran, Iran.

² Department of Civil Engineering, Islamic Azad University, Qeshm Branch, Iran

³ Department of Journalism, Allameh Tabataba'i University, Tehran, Iran.

10.22059/jcss.2024.102582

Abstract

This study highlights the urgent need to redefine media literacy frameworks to address AI-generated content, algorithmic bias, data privacy, and ethical considerations. Key findings reveal a consensus on core competencies, including critical evaluation of AI outputs, understanding algorithmic transparency, and fostering ethical engagement with AI technologies. However, challenges such as fragmented definitions of AI literacy, lack of standardized curricula, and unequal access to resources persist. The review underscores the importance of multidisciplinary collaboration to develop inclusive, adaptive pedagogical models that bridge technical and sociocultural dimensions. Innovative approaches, such as experiential learning and arts-integrated methodologies, show promise in cultivating critical AI literacy. The study calls for longitudinal research, cross-cultural studies, and policy initiatives to ensure equitable and effective integration of AI literacy into education, empowering individuals to navigate and shape AI-mediated digital societies responsibly.

Keywords

References

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