Policy presence
University of North Carolina at Chapel Hill has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
Chapel Hill, United States
University of North Carolina at Chapel Hill
Record status
Review: Agent reviewed
Policy profile
Review: Machine candidate
AI disclosure
University of North Carolina at Chapel Hill has 2 source-backed public claims for ai disclosure; deterministic analysis status: recommended.
Coursework
University of North Carolina at Chapel Hill has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
University of North Carolina at Chapel Hill has 4 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
University of North Carolina at Chapel Hill has 3 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
No source-backed public claim about academic-integrity treatment of AI use is present in this profile.
The current public tracker record does not contain claim evidence about AI use under academic integrity, misconduct, dishonesty, plagiarism, or cheating rules.
Approved tools
University of North Carolina at Chapel Hill has 2 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
University of North Carolina at Chapel Hill has 1 source-backed public claim for named ai services; deterministic analysis status: restricted.
Teaching guidance
University of North Carolina at Chapel Hill has 5 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of North Carolina at Chapel Hill has 2 source-backed public claims for research guidance; deterministic analysis status: restricted.
Security and procurement
University of North Carolina at Chapel Hill has 1 source-backed public claim for security and procurement; deterministic analysis status: restricted.
AI tools
No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.
Evidence-backed claims
7 reviewed evidence-backed public claim
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 reviewed
Normalized value: sensitive-information-requires-iso-dgog-approval
Original evidence
Evidence 1Do 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.
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 reviewed
Normalized value: student-right-to-instructor-review-of-ai-generated-grade
Original evidence
Evidence 1Students 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.
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 reviewed
Normalized value: public-ai-inputs-treated-as-public-disclosure
Original evidence
Evidence 1Uploading 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.
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 reviewed
Normalized value: ai-grading-approved-systems-and-faculty-accountability
Original evidence
Evidence 1Faculty 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.
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 reviewed
Normalized value: research-community-guidance
Original evidence
Evidence 1This 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.
Teaching
UNC-Chapel Hill says faculty should clearly explain when and how AI tools are used in assessment evaluation, including what comes from AI and what comes from instructor judgment.
Review: Agent reviewed
Normalized value: Faculty should disclose AI use in assessment evaluation and distinguish AI-supported evaluation from instructor judgment.
Original evidence
Evidence 1Faculty should clearly explain to students when and how AI tools are used in support of assessment evaluation. Students should understand which parts of their evaluation come from AI and which come from the instructor's own judgment.
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 reviewed
Normalized value: faculty-syllabus-ai-use-guidance
Original evidence
Evidence 1Conveying 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.
Localized display only
The same page's syllabus starter language tells students to follow specific AI guidelines in the syllabus and check with the instructor if unsure.
Candidate claims
0 machine or needs-review claim
Official sources
4 source attribution
Developing AI Guidance for Faculty - Generative AI at UNC
ai.unc.edu
Guidance for Faculty Use of AI in Grading and Assessment
ai.unc.edu
Research Generative AI Usage Guidance - Generative AI at UNC
ai.unc.edu
Staff Generative AI Usage Guidance - Generative AI at UNC
ai.unc.edu