Six Territories for Disciplinary AI Literacy
Source: Nick Potkalitsky Substack
Author: Nick Potkalitsky
Original source: https://nickpotkalitsky.substack.com/p/six-territories-for-disciplinary
Private backup: the full article text is archived in the private repository at archives/articles/nickpotkalitsky-substack-com-six-territories-for-disciplinary.source.md. It is not published on the public Quartz site.
Summary
Nick Potkalitsky argues that AI literacy cannot be taught as a generic portable skill; it must be embedded in disciplinary learning so students develop the knowledge and judgment needed to interrogate AI outputs. He maps six territories for K-16 disciplinary AI literacy: epistemology, knowledge asymmetry, instructional architecture, assessment, disciplinary authenticity and transfer, and professional development/infrastructure. The article’s central concern is that AI can generate polished disciplinary-looking products while bypassing the epistemic practices that give a field meaning.
Big ideas
Claims
- AI literacy only works when it is connected to subject-area knowledge
- Subject-specific AI literacy frameworks are useful maps, not final answers
Key evidence and examples
- District leaders in Central Ohio are designing workshops around discipline-specific AI literacy embedded in subject-area instruction.
- More than 200 educators at an Ohio School Boards Association roundtable showed interest in AI use that preserves intellectual agency.
- The article distinguishes how AI disrupts process and product differently in history, math, science, and literary studies.
- Potkalitsky names “epistemic displacement”: AI can produce accurate outputs without modeling the knowledge-making labor of a discipline.
- Assessment must move toward process documentation, disciplinary justification, revision, and comparison with AI output.
Education relevance
This is highly relevant to K-12 AI literacy, curriculum design, teacher professional development, assessment redesign, and disciplinary pedagogy.