Policy presence
Université de Lorraine has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Nancy, France
Université de Lorraine
Université de Lorraine has 3 source-backed AI policy claims from 3 official source attributions. Review state: agent reviewed; 3 reviewed claims. Last checked May 19, 2026.
Université de Lorraine AI policy short answer
v1 public contract
Université de Lorraine has 3 source-backed AI policy claims from 3 official source attributions, including 3 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 19, 2026. Discovery context: Université de Lorraine is listed as QS 2026 rank 751-760.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Université de Lorraine as an agent-reviewed AI policy record last checked on May 19, 2026 and last changed on May 19, 2026. The record contains 3 source-backed claims, including 3 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/universite-de-lorraine.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 Teaching claims.
- No specific AI service name is highlighted by the current public claim text.
- Teaching, assessment, coursework, or syllabus-related 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
Université de Lorraine has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.
Coursework
Université de Lorraine has 2 source-backed public claims for coursework; deterministic analysis status: required.
Exams
Université de Lorraine has 3 source-backed public claims for exams; deterministic analysis status: required.
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.
Academic integrity
Université de Lorraine has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
Approved tools
Université de Lorraine has 1 source-backed public claim for approved tools; deterministic analysis status: required.
Named AI services
Université de Lorraine has 1 source-backed public claim for named ai services; deterministic analysis status: required.
Teaching guidance
Université de Lorraine has 1 source-backed public claim 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
3 reviewed evidence-backed public claim
Academic Integrity
Universite de Lorraine's 2025 exam charter states that use of tools, including generative artificial intelligence, is fraud when it is not explicitly authorized.
Review: Agent reviewed
Normalized value: unauthorized_generative_ai_tools_constitute_exam_fraud
Original evidence
Evidence 1L'utilisation d'outils, notamment d'intelligence artificielle generative, non explicitement autorisee constitue une fraude.
Localized display only
Use of tools, including generative AI, that is not explicitly authorized constitutes fraud.
Ai Tool Treatment
For the Master Urbanisme et Amenagement, parcours Intelligence Territoriale, the SHS Metz AI-use charter requires students to clearly indicate any AI use in submitted work and provide an AI-use declaration in an appendix.
Review: Agent reviewed
Normalized value: program_ai_use_must_be_disclosed_with_appendix_declaration
Original evidence
Evidence 1Tout usage d'IA dans un travail doit etre clairement indique dans le document rendu, selon les modalites suivantes : Dans le corps du texte : Mentionner explicitement les passages ou elements generes ou modifies par l'IA. En annexe : Fournir une declaration d'usage de l'IA.
Localized display only
Any AI use in submitted work must be clearly indicated, including explicit marking in the text and an AI-use declaration in an appendix.
Teaching
Universite de Lorraine DACIP teaching guidance recommends favoring sovereign and secure generative AI, training on ethical issues, and transparency with students in pedagogical and assessment processes.
Review: Agent reviewed
Normalized value: teaching_guidance_recommends_secure_sovereign_iag_training_and_transparency
Original evidence
Evidence 1Recommandations des expert-es : Favoriser une IAG souveraine et securisee plutot qu'un outil externe qui peut aller a l'encontre des obligations professionnelles de l'enseignant-e entre autres en termes de respect du RGPD ; Se former aux enjeux deontologiques specifiques aux usages des technologies, dont les systemes d'IAG ; Etre transparent-e vis-a-vis des etudiant-es dans les processus pedagogiques et d'evaluation afin de soutenir leurs apprentissages.
Localized display only
Expert recommendations favor sovereign and secure generative AI, training on ethical issues, and transparency with students in pedagogical and assessment processes.
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
3 source attribution
Charte des bons usages de l'intelligence artificielle
shs-metz.univ-lorraine.fr
Charte des examens (hors concours)
mim.univ-lorraine.fr
Ouvroir de Pedagogie Potentielle (OuPePo) - Recit n 4
sup.univ-lorraine.fr
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.