Southern Lehigh Poised to Become 10th Lehigh Valley District to Adopt Generative AI Policy

How to Build a Generative AI Policy for Your School District

Districts are moving fast to set guardrails for AI. If you need a policy that is clear, enforceable, and useful in classrooms, start here.

This guide outlines what to include, how to roll it out, and the practical steps that keep teaching, learning, and data safe.

What a strong AI policy covers

• Student use (what's allowed, what's not, and how to cite)
• Staff use (planning, grading, communication, and data handling)
• Academic integrity (definitions, examples, consequences, appeals)
• Classroom guidance (lesson use, disclosure, accessibility, equity)
• Training and support (PD, student orientation, parent education)
• Procurement and IT (vetting tools, DPAs, security, logging)
• Privacy and compliance (FERPA, COPPA, PPRA, record retention)
• Implementation timeline (pilot, evaluation, full adoption, review cycle)
• Appeals and incident response (process and roles)

Set decision principles before the details

Write three to five principles that guide every choice. Examples: prioritize student learning, protect privacy, reduce workload where possible, require human oversight for grading and high-stakes decisions, and favor transparency.

Keep them short. Refer back to them when debates get stuck.

Student use: clear guardrails

• Allowed: brainstorming, outlines, language support, draft feedback, study guides.
• Restricted: submitting AI output as original work without citation, bypassing assessments, generating unsafe or discriminatory content.
• Citation: require a brief "AI assistance" note when AI meaningfully contributes.
• Age and access: align with COPPA for under-13 students; use district-managed tools with data protections.

Staff use: useful but accountable

• Permitted uses: lesson ideas, rubrics, parent communication drafts, differentiation strategies.
• Prohibited: uploading student PII, confidential records, or assessments not meant for public release.
• Human in the loop: staff remain responsible for accuracy, tone, and compliance.
• Disclosure: disclose AI assistance in family-facing materials when it meaningfully shapes content.

Academic integrity: define and apply

• Define misconduct with examples (e.g., "AI-generated text submitted as original work").
• Teach proper use and citation rather than relying on AI detectors for enforcement.
• Include progressive consequences and a clear appeals path.
• Support alternative assessments that reduce misuse (oral defenses, process journals).

Classroom practice that works

• Post a short "AI use in this course" statement on the syllabus and LMS.
• Model prompt quality, verification, and citing sources.
• Offer AI and non-AI paths to the same outcome to support equity and access.
• Coordinate with special education and ELL teams for accommodations.

Privacy and compliance

• Never input PII or sensitive data into public models.
• Use vendors with signed data privacy agreements and clear data retention limits.
• Document how AI outputs are stored, reviewed, and shared.
• Align to FERPA and local laws; train staff on practical scenarios.

U.S. Department of Education: FERPA overview

Procurement and IT checklist

• Data: no training on district data, option to opt-out of model learning.
• Security: SOC 2/ISO documentation, encryption at rest/in transit, admin controls.
• Access: SSO, role-based permissions, audit logs, content filters.
• Contract: DPA, breach notification, uptime SLA, termination and data deletion terms.
• Pilot: start with limited scope, evaluate learning impact, and capture feedback.

NIST AI Risk Management Framework

Training and rollout

• Staff PD: policy overview, hands-on practice, data do's and don'ts, lesson integration.
• Student orientation: what's allowed, how to cite, examples of smart use.
• Families: short guide, sample classroom uses, privacy commitments, contact for questions.

Suggested 90-day timeline

• Days 0-30: draft policy, legal/privacy review, identify pilot tools and classes.
• Days 31-60: run pilot, collect classroom evidence, refine policy language.
• Days 61-90: board approval, staff PD, parent communications, phased rollout.

Communication plan

• Publish the policy, an FAQ, and a one-page quick start.
• Host a short webinar for families; record and post the replay.
• Give principals a script and slides for staff meetings.

Appeals and incident response

• Define roles (teacher, school admin, district lead).
• Use written forms to document incidents and decisions.
• Allow students to present process evidence (notes, drafts, version history).

Sample policy snippets you can adapt

• "Students may use approved AI tools for brainstorming, outlining, and feedback. If AI meaningfully contributes to a submission, include a brief note describing the assistance."
• "Staff must not enter student PII, health information, or confidential materials into public AI tools. District-approved tools with signed DPAs must be used for any work that touches student data."
• "AI outputs must be verified by a human before use in instruction, grading, or communication."

Common pitfalls to avoid

• Over-relying on AI detectors instead of teaching proper use and citation.
• Unclear boundaries between "allowed with citation" and "not allowed."
• Skipping parent communication and student orientation.
• No plan for vendor oversight or data deletion at contract end.

Measure what matters

• Teacher time saved on planning and feedback.
• Student writing volume, revision quality, and citation accuracy.
• Incidents per grading period and resolution time.
• Tool adoption versus support tickets and privacy issues.

Quick-start resources for your team

• AI courses by job role for educators who want practical classroom use cases.
• ChatGPT certification to build confident, responsible use across staff.

How to find peer policies

• Search your state school boards association site for "AI policy" and sample language.
• Review large-district policies for structure and adapt to local context.
• Ask regional IU/ESD/BOCES for vetted templates and privacy addenda.

Start small, write clearly, and ship the first version. A workable policy today beats a perfect policy next semester.