University Libraries & Learning Sciences Faculty and Staff Publications
Document Type
Preprint
Publication Date
2025
Abstract
Artificial intelligence has become a pervasive force shaping society, economy, and daily life. Despite widespread media coverage and business adoption, a significant gap persists between superficial awareness and meaningful understanding of AI's principles, ethical dimensions, and societal implications. This paper introduces AI Literacy for All: A Universal Framework, a comprehensive model designed to foster responsible engagement with AI across diverse populations.
The framework integrates five essential components—Technical Knowledge, Ethical Awareness, Critical Thinking, Practical Use, and Societal Impact—each structured into four progressive levels guiding learners from basic awareness to strategic insight. This design balances accessible technical understanding with ethical reasoning, critical evaluation, practical application, and societal awareness, creating a holistic approach that transcends purely technical focus.
Grounded in established educational theories while responsive to contemporary AI developments, the framework addresses key limitations in existing models regarding context-specificity, scope, and adaptability. Its universal design offers flexibility for customization across various settings while maintaining core principles supporting comprehensive understanding.
The paper acknowledges areas for continued development, including assessment methodologies, implementation resources, cultural adaptations, and pedagogical strategies. By providing a structured yet adaptable foundation, this framework supports the development of AI literacy as an essential capability for informed citizenship and responsible innovation in an increasingly AI-influenced world.
Keywords
AI literacy, Artificial Intelligence, Digital Literacy, Ethical AI, Critical thinking, AI competencies, Pedagogy, Framework development
Recommended Citation
Lo, L. S. (2025). AI literacy for all: A universal framework [Preprint]. University of New Mexico Digital Repository.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
