Stony Brook, United States

Stony Brook University, State University of New York

Stony Brook University, State University of New York is listed as QS 2026 rank =452. Stony Brook University, State University of New York 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

Stony Brook University, State University of New York is listed as QS 2026 rank =452. Stony Brook University, State University of New York 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 Stony Brook University, State University of New York 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/stony-brook-university-state-university-of-new-york.json. The entity-level confidence is 96%. 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 Academic integrity claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Privacy claims.
  • Evidence includes Source status claims.
  • Evidence includes Teaching claims.
  • Named AI services detected in public claims: Microsoft Copilot, Gemini.
  • 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.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims7Reviewed7Candidate0Official sources5

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 confidence78%

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

Stony Brook University, State University of New York has 1 source-backed public claim for academic integrity; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence82%Evidence1Sources1

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

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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

Academic Integrity

Stony Brook's Academic Integrity Policy lists representing work generated by artificial intelligence as one's own work as an example of academic dishonesty.

Review: Agent reviewedConfidence96%

Normalized value: ai_generated_work_as_own_work_academic_dishonesty

Original evidence

Evidence 1
The following represents examples of academic dishonesty and does not constitute an exhaustive list: ... Representing work generated by artificial intelligence as one's own work.

Localized display only

The Academic Integrity Policy expressly lists representing AI-generated work as one's own as an example of academic dishonesty.

Ai Tool Treatment

Stony Brook guidance says generative AI use in coursework can be prohibited, allowed, or required depending on the course or assignment, and students should consult course policies or instructors when unsure.

Review: Agent reviewedConfidence93%

Normalized value: course_or_assignment_specific_ai_use

Original evidence

Evidence 1
Using generative AI in academic work is prohibited in some cases, allowable in others, and required in some instances. Read policies on academic integrity ... consult course policies, and when in doubt ask your instructor.

Localized display only

The FAQ frames coursework AI use as course- and assignment-dependent and advises students to consult policies or instructors.

Privacy

Stony Brook guidance warns users not to enter sensitive, personal, or proprietary information into generative AI tools without understanding the protections provided by the tool.

Review: Agent reviewedConfidence92%

Normalized value: sensitive_personal_proprietary_information_requires_tool_protection_review

Original evidence

Evidence 1
You should not enter sensitive, personal, or proprietary information into a generative AI tool without understanding the specific protections provided by that tool.

Localized display only

The FAQ warns against entering sensitive, personal, or proprietary information into AI tools without understanding the protections.

Source Status

Stony Brook's central generative AI FAQ states that the University does not currently have an AI policy and is reviewing existing policies for generative AI implications.

Review: Agent reviewedConfidence91%

Normalized value: no_central_ai_policy_under_review

Original evidence

Evidence 1
Does Stony Brook have an AI policy? No. The University is reviewing existing policies to ensure they appropriately address the power and implications of generative AI.

Localized display only

The central FAQ says there is no AI policy yet and that policy owners are reviewing existing policies for generative AI implications.

Ai Tool Treatment

Stony Brook DoIT maintains an AI Tools directory that identifies available tools such as Copilot, Gemini, NotebookLM, Turnitin, and Zoom AI Companion, while noting that listed tools may not be used with HIPAA data.

Review: Agent reviewedConfidence90%

Normalized value: doit_ai_tools_directory_with_hipaa_limitation

Original evidence

Evidence 1
A current directory of AI tools offered by DoIT ... HIPPA Data Considerations. The following tools may not be used with HIPAA data. Copilot ... Gemini ... NotebookLM ... Turnitin ... Zoom.

Localized display only

DoIT's AI Tools directory lists several tools and flags that the listed tools may not be used with HIPAA data.

Teaching

Stony Brook CELT guidance advises instructors to discuss AI usage policies clearly, include AI statements in syllabi, and outline which assignments allow or do not allow AI tools.

Review: Agent reviewedConfidence88%

Normalized value: instructor_ai_syllabus_guidance

Original evidence

Evidence 1
It is important to discuss your policies on AI usage in a clear and unambiguous manner. Including an AI statement in your course syllabus ... outline which assignments allow for the use of AI tools and which assignments do not permit the usage of AI tools.

Localized display only

CELT recommends clear syllabus and assignment-level AI expectations.

Teaching

Stony Brook CELT guidance says users should review AI-generated content for accuracy because AI tools can produce biased, illogical, false, or nonexistent-source outputs.

Review: Agent reviewedConfidence86%

Normalized value: review_ai_generated_content_for_accuracy

Original evidence

Evidence 1
In many cases, AI tools can develop biased, illogical, or false information and even can generate sources that do not exist. It is important that anyone who makes use of AI tools to generate content reviews its output for accuracy.

Localized display only

CELT warns that AI can generate false or biased outputs and says users should review AI output for accuracy.

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

AI Tools | Division of Information Technology

it.stonybrook.edu

Snapshot hash
d019ff3a7394581c990eba22085246c7fa1d61411080d4e7bac6fa09ce730681

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 16, 2026Last changedMay 16, 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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