Policy presence
Université de Lorraine has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Nancy, France
Université de Lorraine
Record status
Review: Agent reviewed
Policy profile
Review: Machine candidate
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.
AI tools
No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.
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
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