University AI Policy Tracker

Open, evidence-backed AI policy records for public reuse.

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Change log

University of North Carolina at Chapel Hill

Source-check timeline, source snapshot hashes, claim review state, and a diff-style preview of current source-backed claim evidence.

Review: Agent reviewedLast checkedMay 14, 2026Last changedMay 14, 2026Claims6Sources4
University pagePublic JSON

Change summary

Current public record freshness and review state.

University of North Carolina at Chapel Hill currently has 6 source-backed claim records and 4 official source attributions. Latest tracked changed date: May 14, 2026.

This tracker is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.

Claim/evidence diff preview

Diff-style preview built from current public claim/evidence records. Full old/new source diffs require paired historical snapshots.

University of North Carolina at Chapel Hill current policy evidence

Inserted lines represent current public claim and evidence records in the source-backed dataset.

+12-0
11 # University of North Carolina at Chapel Hill AI policy record
2+security_review: UNC-Chapel Hill's administrative generative AI guidance says sensitive information should not be entered into generative AI tools unless the Information Security Office has completed a risk assessment and the Data Governance Oversight Group has approved the tool for sensitive information.
3+Evidence (en-US, 64b070af83d4): Do not enter sensitive information (as defined by the UNC-Chapel Hill Information Classification Standard) into generative AI tools unless the University’s Information Security Office (ISO) has conducted a risk assessment of the generative AI tool and the University’s Data Governance Oversight Group (DGOG) has approved the tool to handle sensitive information.
4+teaching: UNC-Chapel Hill's faculty grading and assessment guidance says students must be able to request a full instructor-led review if they disagree with an AI-generated grade or have concerns about automated feedback.
5+Evidence (en-US, 9c6c27e19c1c): Students must be able to request a full instructor-led review if they disagree with an AI- generated grade or have concerns about automated feedback, without additional scrutiny, justification, or penalty.
6+privacy: UNC-Chapel Hill's research guidance treats entering private or confidential information, research data, grant proposals, or analytical results into public generative AI tools as a public disclosure of that information.
7+Evidence (en-US, 1d0574d903f2): Uploading information (e.g., research data, grant proposals, unpublished manuscripts, or analytical results) to a public AI tool is equivalent to releasing it publicly; thus, before any information from you or another individual is uploaded to a public AI tool, appropriate steps must be taken to ensure that the disclosure of that information is consistent with all rules and laws related to the handling of private information.
8+teaching: UNC-Chapel Hill's faculty grading and assessment guidance says AI systems used for grading or feedback must be institutionally approved and compliant with data security and privacy standards; faculty using GenAI for grading retain full responsibility for evaluative decisions and feedback.
9+Evidence (en-US, 9c6c27e19c1c): Faculty must ensure that any AI system used for grading or feedback is institutionally approved and compliant with data security and privacy standards. Uploading student work to consumer-grade AI platforms not contracted by the university is inconsistent with student privacy laws and university policy.
10+research: UNC-Chapel Hill's research generative AI guidance applies to members of the research community involved in research under the auspices of the University, including faculty, staff, students, guest researchers, collaborators, and consultants.
11+Evidence (en-US, 1d0574d903f2): This guidance applies to all members of the research community, including faculty, staff (SHRA and EHRA non-faculty), students (undergraduate, graduate and professional), guest researchers (e.g., unpaid volunteers, interns, and visiting scholars), collaborators, and consultants involved in research occurring under the auspices of the University.
12+teaching: UNC-Chapel Hill faculty guidance encourages instructors to state course and assignment AI expectations in the syllabus and tells Carolina students to follow the specific AI guidelines in that syllabus.
13+Evidence (en-US, 2e373948ed87): Conveying your stance on students’ use of AI in your course is important; it clarifies your expectations and ensures that any use of AI supports rather than frustrates your learning objectives.

Claim changes

6 claim records

security_review

UNC-Chapel Hill's administrative generative AI guidance says sensitive information should not be entered into generative AI tools unless the Information Security Office has completed a risk assessment and the Data Governance Oversight Group has approved the tool for sensitive information.

Review: Agent reviewedConfidence94%Evidence1Languagesen-US

teaching

UNC-Chapel Hill's faculty grading and assessment guidance says students must be able to request a full instructor-led review if they disagree with an AI-generated grade or have concerns about automated feedback.

Review: Agent reviewedConfidence94%Evidence1Languagesen-US

privacy

UNC-Chapel Hill's research guidance treats entering private or confidential information, research data, grant proposals, or analytical results into public generative AI tools as a public disclosure of that information.

Review: Agent reviewedConfidence93%Evidence1Languagesen-US

teaching

UNC-Chapel Hill's faculty grading and assessment guidance says AI systems used for grading or feedback must be institutionally approved and compliant with data security and privacy standards; faculty using GenAI for grading retain full responsibility for evaluative decisions and feedback.

Review: Agent reviewedConfidence93%Evidence1Languagesen-US

research

UNC-Chapel Hill's research generative AI guidance applies to members of the research community involved in research under the auspices of the University, including faculty, staff, students, guest researchers, collaborators, and consultants.

Review: Agent reviewedConfidence91%Evidence1Languagesen-US

teaching

UNC-Chapel Hill faculty guidance encourages instructors to state course and assignment AI expectations in the syllabus and tells Carolina students to follow the specific AI guidelines in that syllabus.

Review: Agent reviewedConfidence90%Evidence1Languagesen-US

Source snapshots

4 source attributions

Developing AI Guidance for Faculty - Generative AI at UNC

official_guidance checked May 14, 2026

Snapshot hash
2e373948ed876e8ace7da6bd84ba95c4ca94ef56ed402524e0afa9e226cc7caa