Burlington, United States

University of Vermont

Record status

Policy statusReviewed evidence-backed recordReview: Agent reviewedClaim coverage10 reviewedEvidence-backed claims10Reviewed10Candidate0Official sources7Source languageenPublic JSON/api/public/v1/universities/university-of-vermont.json

Policy profile

Coverage score100/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence76%

AI disclosure

University of Vermont has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence71%Evidence1Sources1

AI tools

Derived tool records1

AI tools

University of Vermont

Tool
AI tools
About
Not specified
Access
Not specified
Cost
Not specified
Availability
Unknown
Review
Agent reviewed
Sources

Evidence-backed claims

10 reviewed evidence-backed public claim

Academic Integrity

UVM's Code of Academic Integrity states that work generated by artificial intelligence is not considered created by the student and is not permitted unless the instructor expressly states otherwise.

Review: Agent reviewedConfidence95%

Normalized value: AI-generated work not permitted unless expressly stated by instructor.

Original evidence

Evidence 1
Students may not claim as their own work any portion of academic work that was not created by the student. Work generated by artificial intelligence is not considered to be created by the student and is not permitted unless expressly stated by the instructor.

Academic Integrity

UVM's Code of Academic Integrity says course expectations may vary by instructor and students must understand expectations for each assignment and course.

Review: Agent reviewedConfidence93%

Normalized value: Course expectations may vary by instructor.

Original evidence

Evidence 1
Please note: Course expectations may vary from instructor to instructor. All students have an obligation to ensure a clear understanding of the expectations associated with each particular assignment and each particular course in which the student is enrolled.

Privacy

UVM's approved AI tools page says approved AI applications are approved by data risk level, and a tool approved for one risk level is not approved for higher-risk data.

Review: Agent reviewedConfidence93%

Normalized value: Approved AI tools are limited by UVM data risk level.

Original evidence

Evidence 1
Individual tools are approved for use with data at various risk levels – Low, Moderate, High, or Restricted – as defined in the UVM Data Classification Matrix When a service is listed as approved for a risk level, that means it is not approved for higher risk levels. For example, if a service is approved for “Low to High Risk”, that means it is not approved for Restricted data such as Protected Health Information or Controlled Unclassified Information.

Security Review

UVM's approved AI tools page lists general AI tools such as ChatGPT, Claude, and Gemini as public-information-only unless another use case goes through Contract Review.

Review: Agent reviewedConfidence92%

Normalized value: General AI tools are public information only unless Contract Review covers the use case.

Original evidence

Evidence 1
All other general AI tools (ChatGPT, Claude, Gemini, etc.) Public information only Any use cases other than Public Information require Contract Review Free or purchased NOTE: Consider using already purchased tools such as Microsoft Copilot before purchasing other tools

Teaching

UVM's faculty AI guidance says there is not a mandated one-size-fits-all classroom AI approach and tells faculty to clearly communicate how their AI stance shapes course policies and assignments.

Review: Agent reviewedConfidence90%

Normalized value: No mandated one-size classroom AI approach; faculty should communicate course AI stance.

Original evidence

Evidence 1
Because of this, there isn’t a mandated, one-size-fits-all approach to AI in the classroom and, accordingly, classroom practices with AI vary. This flexibility allows you to start with your stance on AI and tailor your course appropriately—but it also means designing policies and assignments for students who are left grappling with different expectations from class to class. Each of us has an obligation to clearly communicate to students about how and why our stance on AI and other technology has shaped the course, its content, its assignment and/or its policies.

Research

UVM Graduate College AI guidance tells graduate researchers not to share confidential, proprietary, or IP-sensitive data or information with an open-source AI engine.

Review: Agent reviewedConfidence90%

Normalized value: Graduate AI guidance warns against sharing confidential, proprietary, or IP-sensitive information with open AI engines.

Original evidence

Evidence 1
Don’t share any data or information that are confidential, proprietary, or have IP implications to an open-source AI engine. Confidentiality and security of data voluntarily input to a Large Language Model (LLM) depends on the policies and practices of platform.

Ai Tool Treatment

UVM's student AI guidance tells students that the key course-context question is what the instructor has said about AI use, and that students should check syllabi and assignment instructions.

Review: Agent reviewedConfidence88%

Normalized value: Students should follow instructor, syllabus, and assignment AI expectations.

Original evidence

Evidence 1
For students, the most important question to ask in a course context is “what has my instructor said about the ways AI tools can be used in this class or assignment?” Expectations and opportunities will differ from class to class, as each set of assignments is carefully designed toward particular learning goals. Students should talk with their instructors, pay attention to policies on the syllabus, and note how assignment instructions reference technology use.

Research

UVM Graduate College AI guidance says students should seek guidance on AI platform use in class assignments, theses, dissertations, and other academic or professional writing.

Review: Agent reviewedConfidence88%

Normalized value: Graduate students should clarify AI use expectations for assignments, theses, dissertations, and professional writing.

Original evidence

Evidence 1
Students should seek guidance for the use of AI platforms in class assignments, theses, dissertations, and other genres of writing that are part of their academic and professional portfolios. Clear communication as to when and how AI can be used in academic writing will limit the risk of inadvertent misuse of AI tools.

Academic Integrity

UVM Libraries' student guide tells students to have a plan for giving credit when using generative AI and notes that APA, MLA, and Chicago have guidelines for citing generative AI.

Review: Agent reviewedConfidence84%

Normalized value: Students should plan attribution for generative AI use.

Original evidence

Evidence 1
Have a plan for giving credit. APA Style, MLA Style, and Chicago Style all have guidelines for citing generative AI. Your instructor may also ask for an appendix that includes the prompts that you provided to ChatGPT or the full transcript of your interaction.

Source Status

UVM Libraries' student guide states that UVM does not currently have a policy on ChatGPT, while instructors may have assignment-specific policies on how ChatGPT may or may not be used.

Review: Agent reviewedConfidence82%

Normalized value: UVM Libraries states no current UVM ChatGPT policy; instructor policies may apply.

Original evidence

Evidence 1
The University of Vermont does not currently have a policy on the use of ChatGPT. However, instructors may have their own policies on how ChatGPT may or may not be used in classroom assignments. If your instructor doesn't have a written policy or hasn't stated whether generative AI can be used for assignments, ask.

Candidate claims

0 machine or needs-review claim

Official sources

7 source attribution

Guidelines for Faculty | Artificial Intelligence | The University of Vermont

uvm.edu

Snapshot hash
d3d3764dca281ec2818ab14fa2ccb501a20c6a59d61d96546f2f8ddaf220851f

Guidelines for Students | Artificial Intelligence | The University of Vermont

uvm.edu

Snapshot hash
d270869dc6761c9d763e04a0ff9b468b4e8b0ffa93f5f8abe70a560875765b94

Change log

Last checkedMay 26, 2026Last changedMay 26, 2026Open change log

Corrections

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