Policy presence
University of New Hampshire has 4 source-backed public claims for policy presence; deterministic analysis status: unclear.
Durham, United States
University of New Hampshire
University of New Hampshire has 6 source-backed AI policy claims from 6 official source attributions. Review state: agent reviewed; 6 reviewed claims. Last checked May 25, 2026.
University of New Hampshire AI policy short answer
v1 public contract
University of New Hampshire has 6 source-backed AI policy claims from 6 official source attributions, including 6 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 25, 2026. Discovery context: University of New Hampshire is listed as QS 2026 rank 1001-1200.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of New Hampshire as an agent-reviewed AI policy record last checked on May 25, 2026 and last changed on May 25, 2026. The record contains 6 source-backed claims, including 6 reviewed claims, from 6 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-new-hampshire.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 Security review claims.
- Evidence includes Privacy claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Teaching claims.
- Evidence includes Source status claims.
- Named AI services detected in public claims: ChatGPT, Microsoft Copilot.
- Disclosure, acknowledgment, citation, or attribution 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 New Hampshire has 3 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
University of New Hampshire has 5 source-backed public claims for coursework; deterministic analysis status: required.
Exams
University of New Hampshire has 3 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
University of New Hampshire has 3 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
University of New Hampshire has 1 source-backed public claim for academic integrity; deterministic analysis status: required.
Approved tools
University of New Hampshire has 2 source-backed public claims for approved tools; deterministic analysis status: blocked.
Named AI services
University of New Hampshire has 2 source-backed public claims for named ai services; deterministic analysis status: required.
Teaching guidance
University of New Hampshire has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of New Hampshire has 1 source-backed public claim for research guidance; deterministic analysis status: restricted.
Security and procurement
University of New Hampshire has 2 source-backed public claims for security and procurement; deterministic analysis status: blocked.
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
6 reviewed evidence-backed public claim
Academic Integrity
UNH's Academic Integrity policy treats unauthorized use or attempted use of AI tools as cheating, and treats computer-generated text or work submitted as one's own without proper citation or attribution as plagiarism.
Review: Agent reviewed
Normalized value: unauthorized_ai_tools_cheating_computer_generated_text_plagiarism
Original evidence
Evidence 1Cheating: Use or attempted use of any academic exercise materials, information, study aids, electronic data, AI tools, assignment/exam surrogate, or other forms of assistance without authorization. Plagiarism: Use or submission of intellectual property, ideas, evidence produced by another person, including computer generated text or work outsourced to third-parties, in whole or in part as one's own in any academic assessment without providing proper citation or attribution.
Security Review
The USNH Artificial Intelligence Standard, which applies to USNH component institutions, says users of AI tools must not share or enter non-public Tier 2 or higher data, including PII or non-public research data, and that any AI implementation is subject to USNH policies, standards, and security review.
Review: Agent reviewed
Normalized value: no_tier2_plus_data_security_review_required
Original evidence
Evidence 1This Standard applies to all administrative, academic, and business units at USNH and its component institutions. Users of AI tools or programs must not share or enter any data classified as non-public (Tier 2 data and above), including but not limited to Personally Identifiable information (PII) or non-public research data. Any implementation of artificial intelligence is subject to USNH policies and standards, including the security review process.
Privacy
UNH Provost syllabus guidance says generative-AI detection tools should not be used to make definitive academic-integrity judgments, and says uploading documents containing student names, emails, or ID numbers violates FERPA; faculty using AI-enabled tools to evaluate student work must disclose that use and keep student data protections in mind.
Review: Agent reviewed
Normalized value: ai_detection_not_definitive_ferpa_disclosure
Original evidence
Evidence 1Turnitin and other software include features that analyze student work for potential plagiarism and use of generative AI tools... They should not be used to make definitive judgments about academic integrity. Further, uploading documents that contain student names, emails, or ID numbers constitutes a violation of FERPA. ChatGPT, Grammarly, Co-Pilot, and other tools may by useful for evaluating the content of student work. You must disclose your use to students.
Ai Tool Treatment
USNH's AI chatbot KB identifies DeepThought and Microsoft Copilot as USNH-provided AI options, recommends signing into Copilot with a USNH account for enterprise data protection, says public chatbots such as ChatGPT and Bard are not secure, and says alternative AI solutions must complete the Security Assessment Review process before purchase or implementation.
Review: Agent reviewed
Normalized value: deepthought_copilot_public_chatbots_sar
Original evidence
Evidence 1The platform includes several free language models (LLMs), which keep data private on the USNH network. Copilot is Microsoft's branded chatbot... We recommend signing in with your USNH account to benefit from enterprise data protection. Public platforms like ChatGPT, Bard and others are not secure and pose risks related to data privacy, intellectual property and compliance with cybersecurity standards. Any alternative must successfully complete the Security Assessment Review (SAR) process before purchase or implementation.
Teaching
UNH Provost syllabus guidance recommends that instructors explicitly tell students whether automated writing tools and AI tools are allowed in a course, and if allowed, specify how and when they may be used.
Review: Agent reviewed
Normalized value: recommended_course_ai_policy_disclosure
Original evidence
Evidence 1The university recommends that instructors be very explicit with their students about whether any use of automated writing tools and tools that use artificial intelligence is allowed; and if allowed, be specific about just how and just when.
Source Status
UNH maintains official Teaching & Learning Resource Hub pages for generative AI and academic honesty that point faculty to AI programming, UNH AI-related policies, the Provost syllabus guidance, and an Academic Honesty and AI policy summary; these pages were used as source-status context rather than binding policy by themselves.
Review: Agent reviewed
Normalized value: official_teaching_resource_hub_ai_context
Original evidence
Evidence 1Getting Started with AI Workshop... will also cover UNH's AI-related policies and recommended practices... Workshop: Teaching Without AI... understand UNH's AI policies, and communicate clear expectations around AI use... Workshop: Partnering with AI... review key elements of UNH's AI policies.
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 Honesty
unh.edu
Academic Integrity
catalog.unh.edu
Artificial Intelligence Standard
usnh.edu
Generative Artificial Intelligence
unh.edu
Syllabus Guidance Fall 2025 for Durham and Manchester
unh.edu
USNH AI Chatbots: Overview
td.usnh.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.