Co-create contextualized AI literacy policies via multi-stakeholder task forces with phased roadmaps¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The brief recommends that districts address AI literacy gaps through comprehensive institutional strategies prioritizing infrastructure and human capacity. AI task forces that bring together educators, administrators, learners, and families can "develop coherent and contextualized AI policies" covering data privacy, security, bias mitigation, and tool evaluation standards, building community buy-in. Task forces should also develop institutional roadmaps with a clear vision, strategies, and phased implementation plans, keeping humans in the loop as AI is designed, adopted, and used.

Design Implications¶

Context¶

Requirements¶

• Effective AI literacy policies require input from those who will implement and be affected by them

Constraints¶

• The brief states successful implementations require adaptation to local contexts, resources, and community needs rather than a one-size-fits-all approach

Target Learners¶

• District and school communities, including PK-12 learners, educators, leaders, and families

Target Learning Goals¶

• Systems-level responsible AI integration and coherent AI literacy implementation across schools and districts

Related Strategies¶

• Establish comprehensive institutional AI governance frameworks including task forces, roadmaps, and transparent policies
• Foster communities of practice for AI governance instead of rigid top-down policies
• Districts should build community-shared visions, evaluation infrastructure, and policies for procuring and using AI edtech
• School districts adopting AI should follow a five-step roadmap: engage communities, apply and develop policies, provide professional development, create supportive learning environments, and monitor and evaluate AI use
• Four strategic recommendations for supporting AI literacy across settings
• Engage community constituents through multiple input methods as the first step in POG development
• Coordinate cross-sector efforts to address AI literacy gaps, focusing on vulnerable workers lacking foundational digital literacy
• Legislators should pass consumer-protection legislation and create a regulatory agency governing AI education products
• Adopt AI incrementally in waves from simple to complex tasks, on free-tier tools, with mandatory multi-step human review before any document is issued
• Embed anticipatory governance in institutional strategy via Chief AI Officers, AI task forces, faculty AI-literacy development, and student co-design mechanisms
• Build institutional AI literacy and transparent risk-communication governance for agentic AI browsers
• Co-design and validate context-aware AI through DBIR blended with user-centered design in privacy-preserving enclaves
• Bridge the AI intention-practice gap through digital infrastructure, professional development, and supportive institutional policies
• Staged institutional implementation: audit interactions, map to teaming levels, build AI literacy, co-design, and evaluate iteratively
• Phased implementation of AI in nursing education: simulation for emergency care, adaptive platforms for at-risk learners, automated formative feedback, and multi-site pilots
• Staged readiness strategy: establish policy clarity and faculty capacity-building before ambitious AI-enabled or online scale-up
• Combine bottom-up co-design with top-down executive sponsorship, cross-unit collaboration and dedicated R&D capacity to embed institutional GenAI

Examples¶

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Key Sources¶

• Digital Promise. (2025). AI Literacy in PK-12 Education. https://digitalpromise.dspacedirect.org/items/19fd2afb-0811-4e48-90d9-0ad6c9887a1a