AI literacy and assessment integrity need separate workstreams

Current synthesis

Schools need to separate two related but different jobs: helping students learn to use AI well, and redesigning assessment so teachers can still see what students understand. Separate AI Literacy and Assessment Integrity Schools should separate AI literacy work from assessment integrity work

AI literacy asks students to practice judgment, prompting, verification, metacognition, and reflection with AI, not simply avoid AI or use it as a shortcut. AI literacy should teach critical doing with AI AI literacy takes system capacity, not just tool access

Assessment integrity asks schools to gather reliable evidence of thinking through process, conversation, visible reasoning, performance, and teacher observation instead of trusting final products by themselves. In an AI world, assessment should focus on watching students think AI has made unsupervised take-home essays unreliable evidence

The two workstreams should inform each other, but merging them too quickly can make AI literacy feel like cheating prevention and make assessment reform feel like tool training. Separate AI Literacy and Assessment Integrity AI-assisted homework requires redesign, not just policing

For district work, this means teams should plan AI literacy instruction, assessment redesign, teacher learning, policy, and tool governance as coordinated but distinct parts of a long-term redesign project. District AI work is a long-term redesign project District AI implementation needs living guidance and teacher-led redesign

Build AI literacy lessons that teach students how to use, question, verify, and reflect on AI use.
Build assessment systems that make student thinking visible before, during, and after AI-supported work.
Avoid using every AI literacy conversation as a cheating conversation.
Avoid treating every assessment-integrity problem as a student behavior problem.