Riverside, United States

University of California, Riverside

Record status

Policy statusReviewed evidence-backed recordReview: Agent reviewedClaim coverage7 reviewedEvidence-backed claims7Reviewed7Candidate0Official sources5Source languageenPublic JSON/api/public/v1/universities/university-of-california-riverside.json

Policy profile

Coverage score85/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence75%

Policy presence

University of California, Riverside has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.

UnclearMachine candidateConfidence73%Evidence1Sources1

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

AI tools

Derived tool records0

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

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 reviewedConfidence92%

Normalized value: non-reviewed AI tools limited to public data

Original evidence

Evidence 1
Generative 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 2
The 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 reviewedConfidence90%

Normalized value: beneficial and mission-aligned instructional AI use

Original evidence

Evidence 1
Any 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 2
The 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 reviewedConfidence90%

Normalized value: ITS lists supported AI tools and allowed data levels

Original evidence

Evidence 1
The 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 2
ChatGPT 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 reviewedConfidence90%

Normalized value: students should follow instructor expectations, keep original work, and cite AI use

Original evidence

Evidence 1
We 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 2
AI 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 3
If 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 reviewedConfidence88%

Normalized value: instructors should set syllabus/class AI-use and citation expectations

Original evidence

Evidence 1
Key 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 2
Although 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 reviewedConfidence86%

Normalized value: official instructional guidance found; course-level local authority emphasized

Original evidence

Evidence 1
In 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 2
We 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 reviewedConfidence82%

Normalized value: general academic misconduct definitions

Original evidence

Evidence 1
Cheating: 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 2
Plagiarism is the appropriation of another person's ideas, processes, results, or words without giving appropriate credit.

Original evidence

Evidence 3
Unauthorized 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

Official sources

5 source attribution

Generative AI at UCR

its.ucr.edu

Snapshot hash
fe06ed36a4eea2fbc2e61a5d3dffe97528c28ada7d97136a8b7c1c5797041495

Change log

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

Corrections

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