2.2 — AI Literacy Scope & SequenceVerify state lawFrontier
What this is
A K-12 articulated scope and sequence for AI literacy — how AI works, when and when not to use it, evaluating AI outputs, algorithmic bias, ethical considerations, and cognitive implications of AI use.
Why it matters
AI literacy is not digital literacy. Students using AI tools without understanding them form habits of uncritical acceptance, lose practice with the underlying skills the tools replace, and miss the cognitive work the assignment was designed to develop. Arizona HB 4005, currently pending in the state legislature, would require K-12 instruction on the ethical, moral, and educational uses of AI beginning in the 2027–28 school year. Comparable proposals are advancing in Hawaii (SB 2212), Florida (HB 1503/SB 1694), and New Jersey (A.4352/S.2862), while New York's Responsible AI Safety and Education Act (signed December 2025) takes a broader regulatory approach. AI literacy needs its own coherent K-12 treatment.
Connects to
The Framework: Condition #2 (Shared Language). ISTE Standard 1.2 (Digital Citizen & AI Literacy).
Maturity levels
Not Started
No AI literacy curriculum. AI addressed only reactively (when something goes wrong). Students rely on peer knowledge and informal exposure.
Emerging
Some AI instruction exists, often in isolated units or elective courses. Not K-12 articulated. Typically focuses on how to use AI tools rather than critical AI literacy.
Established
K-12 scope and sequence documented and grade-band differentiated. Addresses both practical use and critical evaluation. Integrated into existing subjects (ELA, science, social studies, math, arts) rather than taught as a standalone AI class — subject-area teachers share responsibility. Explicitly linked to academic integrity and data privacy curriculum. An exit profile articulates what graduating students should know and be able to do with AI.
Expanding
Scope covers how AI works under the hood, not just how to use it: data, training, bias, model limitations. Developmentally sequenced from concrete K-5 treatment to systemic 9-12 treatment. Subject-specific integration is robust across all content areas. Exit profile is backward-mapped to drive K-8 sequencing. Students engage in AI critique and ethical reasoning, not just tool use. Aligned with state frameworks and emerging legislation (pending HB 4005-style AI instruction mandates in AZ, HI, FL, NJ; broader NY framework already enacted).
Go deeper with
Example resource
AI4K12 — Five Big Ideas (ai4k12.org)
Also consider
TeachAI Toolkit — curriculum resources and implementation guidance
aiEDU — free K-12 curriculum with career-readiness focus
Code.org AI courses — introductory and intermediate AI units