AI Literacy for All: Adjustable Interdisciplinary Socio-technical Curriculum

AI literacy requires a balanced, interdisciplinary approach beyond traditional technical training. The paper argues that effective AI education must combine technical and non-technical learning outcomes, moving away from curricula that focus solely on mathematical foundations and programming skills to include critical evaluation of AI technologies in broader socio-technical contexts.

Four core pillars should structure AI education for all levels: understanding AI's technical scope and dimensions, learning to interact responsibly with generative AI tools like ChatGPT, understanding ethical and responsible AI issues, and grasping the social and future implications of AI technology.

Generative AI tools have fundamentally changed what AI literacy means. The paper notes that most previous conceptualizations of AI literacy were established before public release of tools like ChatGPT, indicating that curricula must be updated to address how people actually interact with AI in everyday contexts, not just how it's built.

AI literacy should be accessible across all education levels, not just for technical specialists. By emphasizing an "adjustable" curriculum, the paper suggests that foundational AI understanding is necessary for everyone—from K-12 students to working professionals—to make informed decisions about and critically evaluate AI's role in society.

Responsible AI requires understanding socio-technical implications alongside technical capabilities. The curriculum explicitly prioritizes ethical considerations and social impacts as core learning outcomes, recognizing that responsible AI adoption depends on broader stakeholder understanding, not just technical expertise.