Six Territories for Disciplinary AI Literacy

Source: Nick Potkalitsky Substack
Author: Nick Potkalitsky
Original source: https://nickpotkalitsky.substack.com/p/six-territories-for-disciplinary

Published: 2025-11-19
Source type: essay
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.

Pull quotes

AI Literacy Must Be Disciplinary-Specific

“AI literacy must be disciplinary-specific, embedded within subject-area instruction where students simultaneously build content knowledge and critical AI capabilities.”

Epistemic Displacement

“AI doesn’t just assist with disciplinary work; it performs the epistemic labor that constitutes disciplinary thinking.”

Knowledge and Agency

“Students with strong disciplinary grounding approach AI as a testable claim generator. Students without that grounding approach AI as an authoritative oracle.”

The Real Integration Question

“The question isn’t whether to integrate AI. It’s whether we’ll do so in ways that build or bypass disciplinary capabilities.”

Big ideas

• AI literacy has to be taught inside real subjects
• District AI work is a long-term redesign project

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.

Durability note

This is durable as a map of disciplinary AI literacy concerns, even if the named territories need revision as classroom practice and AI capabilities mature.

My notes