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Artificial Intelligence (AI) refers to computer systems that can perform tasks that typically require human thinking, such as recognizing patterns, generating text or images, translating languages, or making predictions.

In K-12 educational settings, AI can be used to support:

• Brainstorming, drafting, editing, and/or organization.
• Scaffolding, modifying, translating, and/or generating multimodal content for learners with diverse needs.
• Providing practice feedback and/or tutoring supports.
• Assisting with planning, communication, data analysis, and/or administrative tasks.

AI should be understood as part of the ongoing evolution of educational technology. Like calculators, spell-checkers, search engines, and learning management systems before it, AI introduces both instructional opportunities and new responsibilities.

Common Forms of AI

While AI takes many forms in educational settings, this guidance focuses specifically on generative AI, as it is the most accessible to everyday users and increasingly integrated into educational technology platforms.

Note the following distinctions:

• Agentic AI, from “agent”, performs actions on a user’s behalf by carrying out tasks across tools or systems (e.g., gathering information or coordinating multi-step workflows).
• Predictive AI, from “predict”, analyzes patterns in data to identify trends, risks, or likely outcomes (e.g., attendance or engagement indicators).
• Generative AI, from “generate”, produces new content (e.g., text, images, audio, video, or code) by drawing on patterns learned from existing data in response to user input.

The principles offer guidance to promote responsible AI use in the classroom. To ensure students benefit from the powerful capabilities of AI, it must be used as a supportive tool that enhances, but does not replace, authentic learning. Ethical and effective use requires transparency about when and how AI is used and ongoing reflection on the impact of AI on student thinking and engagement. 

1. Build Foundational AI Literacy: Before using AI tools, students should understand how AI works and recognize its opportunities, risks, and limitations. Early learning may emphasize unplugged activities, such as class discussions, before progressing to responsible evaluation, judgment, and guided tool use in later grades.
2. Keep Humans in the Loop: AI output is a starting point, not a conclusion. Final judgment, ethical responsibility, and core idea generation must remain human.  
3. Quality of Input = Quality of Output: AI systems reflect the clarity and specificity of the instructions provided by the user. Think critically about the intended task and the desired outcome and refine prompts accordingly. 
4. Don’t Just Prompt, Provoke: Rather than prompt for a response, prompt to encourage a conversation and provoke thought, creativity, and complex analysis. 
5. Assistance, Not Authority: AI output is fallible and requires independent verification of facts and sources. AI should serve as a tool that aids in the research or creation process, not an ultimate source of truth.  
6. View AI as a Bridge: Reframe AI as a scaffolding tool that helps bridge a skills gap (i.e., technical knowledge, writer's block, complex content, etc.) to help users access and complete challenging tasks. 
7. Reflect and Take Responsibility: Encourage reflection on when AI was helpful, when it failed, and what the unique human contribution was, fostering ownership over work and taking agency over learning. 
8. Prioritize Process Over Products: In assessing artifacts created in collaboration with AI tools, value the human thinking, creativity, and iteration that led to the end product (i.e., prompting, verification, revision, etc.).