Policy presence
New York University (NYU) has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
New York City, United States
New York University (NYU)
New York University (NYU) is listed as QS 2026 rank 55. New York University (NYU) has 4 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
New York University (NYU) is listed as QS 2026 rank 55. New York University (NYU) has 4 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.
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
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.
Coursework
New York University (NYU) has 3 source-backed public claims for coursework; deterministic analysis status: conditionally_allowed.
Exams
New York University (NYU) has 3 source-backed public claims for exams; deterministic analysis status: conditionally_allowed.
Privacy and data entry
New York University (NYU) has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
New York University (NYU) has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
Approved tools
New York University (NYU) has 3 source-backed public claims for approved tools; deterministic analysis status: allowed.
Named AI services
New York University (NYU) has 3 source-backed public claims for named ai services; deterministic analysis status: unclear.
Teaching guidance
New York University (NYU) has 2 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
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.
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
Teaching
NYU offers access and support for Google's Gemini and NotebookLM to faculty, staff, and students through institutional accounts.
Review: Agent reviewed
Normalized value: NYU offers access and support for Google's Gemini and NotebookLM to faculty, staff, and students thr
Original evidence
Evidence 1NYU now offers access and support for both Google's Gemini and NotebookLM to faculty, staff, and students.
Academic Integrity
NYU's policy requires instructor approval for student AI use, student compliance with instructor limitations, and adherence to the Academic Integrity Policy.
Review: Agent reviewed
Normalized value: NYU's policy requires instructor approval for student AI use, student compliance with instructor lim
Original evidence
Evidence 11. The instructor approves. 2. The student abides by any requirements or limitations the instructor may have. 3. The use does not violate NYU's Academic Integrity Policy
Ai Tool Treatment
NYU does not license or endorse AI detection tools due to accuracy and reliability concerns.
Review: Agent reviewed
Normalized value: NYU does not license or endorse AI detection tools due to accuracy and reliability concerns.
Original evidence
Evidence 1The Office of the Provost and IT's Academic Technology group do not believe any current AI detectors work well enough to recommend their use or license them on behalf of the university.
Privacy
NYU institutional accounts for Gemini and NotebookLM do not train AI models on user data and do not log queries or answers.
Review: Agent reviewed
Normalized value: NYU institutional accounts for Gemini and NotebookLM do not train AI models on user data and do not
Original evidence
Evidence 1When used with an NYU account instead of your personal Gmail, Gemini and NotebookLM never train their AI models on your data. They do not log your queries or model answers
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
Academic Integrity and Syllabus Support
steinhardt.nyu.edu
Frequently Asked Questions About Teaching and AI - NYU
nyu.edu
Generative AI Tools for Academic Research: An Introduction
guides.nyu.edu
NYU Generative AI Guidance
New York University
Student Learning with Generative AI - NYU
nyu.edu
Teaching with Generative AI - NYU
nyu.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.