Providence, United States

Brown University

Brown University is listed as QS 2026 rank 69. Brown University has 9 source-backed AI policy claim records from 6 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

Brown University is listed as QS 2026 rank 69. Brown University has 9 source-backed AI policy claim records from 6 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims9Reviewed9Candidate0Official sources6

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.

Coverage score85/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence79%

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

No source-backed public claim about AI disclosure or acknowledgement is present in this profile.

The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Academic integrity

Brown University has 2 source-backed public claims for academic integrity; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence79%Evidence2Sources2

Research guidance

Brown University has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence78%Evidence1Sources1

Security and procurement

Brown University has 2 source-backed public claims for security and procurement; deterministic analysis status: conditionally_allowed.

Conditionally AllowedMachine candidateConfidence79%Evidence2Sources1

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

9 reviewed evidence-backed public claim

Privacy

Brown OIT guidance says users should not enter Level 2 or 3 Brown data into publicly available or vendor-enabled AI tools unless Brown has a contract for a specific service that protects the data.

Review: Agent reviewedConfidence95%

Normalized value: no_level_2_or_3_data_without_protective_contract

Original evidence

Evidence 1
Unless Brown has a contract for a specific service which protects our data, do not enter Level 2 or 3 data into publicly available or vendor-enabled AI tools.

Ai Tool Treatment

Brown OIT guidance says Google Gemini Chat and NotebookLM are accessible at no cost to Brown and can be used with data classified as Risk Level 3, unlike consumer AI services named on the page with which Brown does not have agreements.

Review: Agent reviewedConfidence95%

Normalized value: gemini_notebooklm_accessible_risk_level_3

Original evidence

Evidence 1
The two Artificial Intelligence (AI) services Google Gemini Chat and NotebookLM are now accessible at no cost to Brown. These services can be used with data classified as Risk Level 3 (unlike consumer AI services such as ChatGPT, DeepSeek, and Claude with whom Brown does not have agreements).

Academic Integrity

Brown Provost guidance says any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Graduate Student Edition Academic Code.

Review: Agent reviewedConfidence94%

Normalized value: unapproved_ai_assignment_use_academic_code

Original evidence

Evidence 1
Any unapproved use of AI to complete assignments would be covered by Brown’s Academic Code and Academic Code, Graduate Student Edition.

Teaching

Brown University Provost guidance says the University is not prescribing specific AI policies, and that faculty should give clear, unambiguous information about what AI use is and is not allowed in their courses.

Review: Agent reviewedConfidence93%

Normalized value: instructor_discretion_clear_course_expectations

Original evidence

Evidence 1
While the University is not prescribing specific AI policies, faculty should offer clear, unambiguous information about what is, and is not, allowed in their courses.

Ai Tool Treatment

Brown OIT guidance says Gemini and NotebookLM are optional tools available to Brown students, Brown staff, Brown-paid faculty, and Brown clinical/medical faculty.

Review: Agent reviewedConfidence93%

Normalized value: gemini_notebooklm_optional_available_to_brown_community_roles

Original evidence

Evidence 1
Google Gemini and NotebookLM are available to: Brown students Brown staff Brown-paid faculty Brown clinical/medical faculty

Academic Integrity

Brown Sheridan Center guidance says instructors should be explicit with students about expectations for generative AI use, including how students should, might, or cannot engage with it.

Review: Agent reviewedConfidence92%

Normalized value: ai_use_expectations_require_explicit_course_guidelines

Original evidence

Evidence 1
Because of changing norms and the wide variety of instructional practice, it is essential for instructors to be explicit to students about their own expectations.

Research

Brown OIT research guidance says researchers should deeply review AI-generated code for quality and efficiency.

Review: Agent reviewedConfidence92%

Normalized value: research_ai_generated_code_requires_deep_review

Original evidence

Evidence 1
It’s critical to deeply review all code generated with these tools for quality and efficiency.

Security Review

Brown OIT guidance says AI tool use is subject to the same policies as other information technology resources, including acceptable use, copyright, conduct, and contract review policies.

Review: Agent reviewedConfidence91%

Normalized value: ai_tools_subject_to_existing_it_and_contract_policies

Original evidence

Evidence 1
Use of AI tools is subject to the same policies as other information technology resources. Familiarize yourself and follow these guidelines at Brown: The Code of Conduct and Student Code of Conduct ... The Acceptable Use of Information Technology Policy ... The Copyright Ownership and Use Policy ... The Contract Review Policies and Process

Privacy

Brown University Communications guidance for Brown communicators says not to input identifying personal information or proprietary information into AI tools.

Review: Agent reviewedConfidence90%

Normalized value: communicators_no_identifying_personal_or_proprietary_info_in_ai

Original evidence

Evidence 1
This includes a prohibition against inputting names, birthdates, addresses, grades, performance ratings, etc. into any AI tool in ways that identify individuals ... This includes a prohibition against inputting proprietary information into any AI tool

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

6 source attribution

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.

Last checkedMay 12, 2026Last changedMay 12, 2026Open change log

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.

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