Policy presence
University of California, Riverside has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Riverside, United States
University of California, Riverside
University of California, Riverside is listed as QS 2026 rank =440. University of California, Riverside has 7 source-backed AI policy claim records from 5 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 California, Riverside is listed as QS 2026 rank =440. University of California, Riverside has 7 source-backed AI policy claim records from 5 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 California, Riverside as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 7 source-backed claims, including 7 reviewed claims, from 5 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-california-riverside.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 Security review claims.
- Evidence includes Teaching claims.
- Evidence includes Procurement claims.
- Evidence includes Academic integrity claims.
- Evidence includes Source status claims.
- Named AI services detected in public claims: ChatGPT, Microsoft Copilot, Gemini.
- 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.
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 California, Riverside has 2 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
University of California, Riverside has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
University of California, Riverside has 4 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
No source-backed public claim about privacy or data-entry restrictions is present in this profile.
The current public tracker record does not contain claim evidence about personal, confidential, sensitive, regulated, or student data entry into AI tools.
Academic integrity
University of California, Riverside has 2 source-backed public claims for academic integrity; deterministic analysis status: restricted.
Approved tools
University of California, Riverside has 2 source-backed public claims for approved tools; deterministic analysis status: allowed.
Named AI services
University of California, Riverside has 2 source-backed public claims for named ai services; deterministic analysis status: allowed.
Teaching guidance
University of California, Riverside has 5 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
No source-backed public claim about research AI use is present in this profile.
The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.
Security and procurement
University of California, Riverside has 3 source-backed public claims for security and procurement; deterministic analysis status: required.
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
7 reviewed evidence-backed public claim
Security Review
UCR's Provost guidelines state that generative AI tools that have not passed a campus security review may be used with public data only; for other data classifications, UCR points to secure tools including Google Gemini and Microsoft Copilot.
Review: Agent reviewed
Normalized value: non-reviewed AI tools limited to public data
Original evidence
Evidence 1Generative AI tools which have not passed a campus security review may be used with public data only. For all other data classifications, UCR provides access to secure tools including Google Gemini and Microsoft Copilot.
Original evidence
Evidence 2The standard ChatGPT tool (even paid versions) does not meet UCR privacy requirements. As a result, only P1 (Public) data can be used with a non-enterprise version of ChatGPT.
Teaching
UCR's Provost generative-AI guidelines say instructional uses of generative AI by instructors or students should aim to improve student learning and align with UCR's instructional mission.
Review: Agent reviewed
Normalized value: beneficial and mission-aligned instructional AI use
Original evidence
Evidence 1Any use of generative AI in an instructional setting, by instructors or students, should aim to improve the learning experience for students and better position students for academic and post-graduation success.
Original evidence
Evidence 2The use of generative AI in instructional settings should aim to advance the university's instructional mission. This includes a strong emphasis on equitable access, opportunity, and achievement.
Procurement
UCR ITS lists UCR-supported AI tools by role and allowed data level, including Gemini, NotebookLM, Google AI Studio, Microsoft 365 Copilot, Vertex AI, Zoom AI Companion, The Grove, and a ChatGPT EDU offering that the page says is not currently available.
Review: Agent reviewed
Normalized value: ITS lists supported AI tools and allowed data levels
Original evidence
Evidence 1The AI tools comparison chart lists Tool/Platform, Description, Roles Allowed, Getting Access, Training Resources, Cost, and Allowed Data for tools including The Grove, Gemini, NotebookLM, Google AI Pro, Google AI Studio, Microsoft 365 Copilot, ChatGPT EDU, Vertex AI, and Zoom AI Companion.
Original evidence
Evidence 2ChatGPT EDU | Generates text, images, and other content in response to user prompts, facilitating natural and interactive communication. | Faculty, Staff, Students | Not available currently, still in negotiations with OpenAI.
Academic Integrity
UCR's student-facing AI announcement says students should discuss generative-AI expectations with professors, use AI to assist or enhance rather than replace original work, avoid generating entire deliverables, and cite AI-generated content or data when used.
Review: Agent reviewed
Normalized value: students should follow instructor expectations, keep original work, and cite AI use
Original evidence
Evidence 1We encourage you to discuss with your professors for specific policies or expectations before engaging in the use of Generative AI resources on academic assignments, papers, tests, etc.
Original evidence
Evidence 2AI can assist with data analysis, generate ideas, or help structure your thoughts. However, you should not use it to generate essays, assignments, or other deliverables in their entirety.
Original evidence
Evidence 3If you use AI-generated content or data as part of your research or assignments, ensure that you cite it properly.
Teaching
UCR XCITE advises instructors to discuss when AI may be used in coursework and how it should be cited, and its sample syllabus language treats uncited AI use as a potential academic-integrity issue.
Review: Agent reviewed
Normalized value: instructors should set syllabus/class AI-use and citation expectations
Original evidence
Evidence 1Key points to discuss in your syllabus/ in class: If and when AI may be used to write a portion of homework or any other assignment; How to properly cite the use of any AI.
Original evidence
Evidence 2Although generative AI may be used like any other source of information that supports your work, it must be properly quoted and cited each time it is used. Failure to properly cite the use of AI in your work will be viewed as a potential academic integrity violation.
Source Status
UCR's public generative-AI guidance for instructional settings places course-level use decisions with the Instructor of Record rather than setting one universal student-use rule in the evidence reviewed here.
Review: Agent reviewed
Normalized value: official instructional guidance found; course-level local authority emphasized
Original evidence
Evidence 1In instructional settings, this means the Instructor of Record has broad latitude to determine whether and how generative AI may be used, provided this use is consistent with applicable policies and rules governing data security and instruction at UCR.
Original evidence
Evidence 2We encourage you to discuss with your professors for specific policies or expectations before engaging in the use of Generative AI resources on academic assignments, papers, tests, etc.
Academic Integrity
UCR's general academic-integrity page defines academic misconduct to include using prohibited or inappropriate materials, plagiarism without appropriate credit, and unauthorized collaboration without instructor permission.
Review: Agent reviewed
Normalized value: general academic misconduct definitions
Original evidence
Evidence 1Cheating: Fraud, deceit, or dishonesty in an academic assignment, or using or attempting to use materials, or assisting others in using materials that are prohibited or inappropriate in the context of the academic assignment or capstone in question.
Original evidence
Evidence 2Plagiarism is the appropriation of another person's ideas, processes, results, or words without giving appropriate credit.
Original evidence
Evidence 3Unauthorized Collaboration: Working with others without the specific permission of the instructor on assignments that will be submitted for a grade.
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
5 source attribution
Academic Integrity Polices & Procedures
conduct.ucr.edu
AI in the Classroom
teaching.ucr.edu
Generative AI at UCR
its.ucr.edu
Guidelines for Using Generative Artificial Intelligence in Instructional Settings at UCR
provost.ucr.edu
Update on artificial intelligence use for students
insideucr.ucr.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.