Policy presence
University of Rochester has 4 source-backed public claims for policy presence; deterministic analysis status: unclear.
Rochester, United States
University of Rochester
University of Rochester is listed as QS 2026 rank 236. University of Rochester has 4 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
University of Rochester is listed as QS 2026 rank 236. University of Rochester has 4 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of Rochester as an agent-reviewed AI policy record last checked on May 15, 2026 and last changed on May 15, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 4 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-rochester.json. The entity-level confidence is 92%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Privacy claims.
- Evidence includes Teaching claims.
- Evidence includes Research claims.
- Evidence includes Academic integrity claims.
- No specific AI service name is highlighted by the current public claim text.
- Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
- Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
- Privacy, sensitive-data, or security language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page 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.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
University of Rochester has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.
Coursework
University of Rochester has 1 source-backed public claim for coursework; deterministic analysis status: restricted.
Exams
University of Rochester has 2 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
University of Rochester has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
University of Rochester has 1 source-backed public claim for academic integrity; deterministic analysis status: restricted.
Approved tools
University of Rochester has 1 source-backed public claim for approved tools; deterministic analysis status: restricted.
Named AI services
University of Rochester has 1 source-backed public claim for named ai services; deterministic analysis status: restricted.
Teaching guidance
University of Rochester has 2 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Rochester has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.
Security and procurement
University of Rochester has 1 source-backed public claim for security and procurement; deterministic analysis status: restricted.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
4 reviewed evidence-backed public claim
Privacy
University of Rochester Provost guidance says non-public or sensitive University information should not be uploaded into external AI tools unless there is a university agreement with the vendor approved by an AI governance group.
Review: Agent reviewed
Normalized value: external_ai_tools_sensitive_data_restricted
Original evidence
Evidence 1non-public or sensitive University information should never be uploaded into external AI tools--whether free or paid--unless there is a university agreement with the vendor approved by one of the various AI governance groups.
Teaching
University of Rochester Provost guidance says instructors should create written course GenAI policies stating when students must, may, or cannot use GenAI and how use should be verified, disclosed, documented, and attributed.
Review: Agent reviewed
Normalized value: provost_guidance_course_genai_policies
Original evidence
Evidence 1Instructors should create and communicate student GenAI course policies. For each assignment, the policy should state when students must, may, or cannot use GenAI and how they should verify, disclose, document, and attribute any GenAI use.
Research
University of Rochester research guidance frames responsible GenAI use in research around data protection, verification, and transparency, including only considering low-risk data generally suitable for GenAI and using appropriate internal review for medium- or high-risk data.
Review: Agent reviewed
Normalized value: research_genai_data_protection_verification_transparency
Original evidence
Evidence 1As a general guide, only data classified as low risk by the University Data Security Classification Policy should be considered suitable for entry to GenAI.
Original evidence
Evidence 2Three key duties of data protection, verification, and transparency frame appropriate use of GenAI in research.
Academic Integrity
The SAS/Hajim Academic Honesty Policy lists use of AI-generated material not allowed by the instructor as an example of plagiarism under that school-scoped policy.
Review: Agent reviewed
Normalized value: sas_hajim_instructor_disallowed_ai_material_plagiarism_example
Original evidence
Evidence 1Usage of material generated by AI tools (Grammarly, ChatGPT, DALL-E, translation software, or similar) that is not allowed by the instructor.
Candidate claims
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
Official sources
4 source attribution
Academic Honesty Policy
rochester.edu
Generative AI Use in Education - Office of the Provost
rochester.edu
Responsible Use of AI Tools and Institutional Data Security
rochester.edu
Responsible Use of Generative Artificial Intelligence in Research
rochester.edu
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.