University AI Policy Tracker

Open, evidence-backed AI policy records for public reuse.

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Change log

Université de Montpellier

Source-check timeline, source snapshot hashes, claim review state, and a diff-style preview of current source-backed claim evidence.

Review: Agent reviewedLast checkedMay 16, 2026Last changedMay 16, 2026Claims6Sources3
University pagePublic JSON

Change summary

Current public record freshness and review state.

Université de Montpellier currently has 6 source-backed claim records and 3 official source attributions. Latest tracked changed date: May 16, 2026.

This tracker 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.

Claim/evidence diff preview

Diff-style preview built from current public claim/evidence records. Full old/new source diffs require paired historical snapshots.

Université de Montpellier current policy evidence

Inserted lines represent current public claim and evidence records in the source-backed dataset.

+12-0
11 # Université de Montpellier AI policy record
2+privacy: UM's AI-in-training principles say confidentiality, privacy, personal data, and intellectual property protections should be guaranteed, and no nominative, confidential, or sensitive data should be used in a public AI tool.
3+Evidence (fr, 268d1366e75f): Le respect de la confidentialite et de la vie privee, ainsi que la protection des donnees personnelles et de la propriete intellectuelle, doivent toujours etre garantis. Aucune donnee nominative, confidentielle ou sensible ne doit etre utilisee dans un outil d'IA public.
4+academic_integrity: UM's AI-in-training principles say student AI use should respect university regulations, rules for each teaching activity, and assessment-specific instructions; expectations should be clarified in course and assessment materials.
5+Evidence (fr, 268d1366e75f): L'utilisation de l'IA par les etudiantes et etudiants doit respecter les reglements en vigueur a l'Universite de Montpellier, les regles propres a chaque enseignement et les consignes specifiques a chaque evaluation. Les attentes concernant l'utilisation de l'IA sont explicitees dans les programmes de cours et expliquees aux etudiantes et etudiants.
6+teaching: UM's AI-in-training principles say decisions to use or address AI in training activities rest with teaching staff and should align with learning objectives.
7+Evidence (fr, 268d1366e75f): La decision d'utiliser ou d'aborder l'IA dans les activites de formation releve des personnels enseignants, et s'appuie sur une exploration des possibilites que l'IA offre dans leur domaine disciplinaire, en coherence avec les objectifs d'apprentissage.
8+source_status: Universite de Montpellier has official AI-in-training principles, but this staged crawl found no separate central binding AI policy page.
9+Evidence (fr, 268d1366e75f): Face aux enjeux lies a l'essor de l'IA, l'Universite de Montpellier a defini 7 principes pour l'usage de l'intelligence artificielle dans la formation. Ils ont ete votes par la Commission Formation et Vie Universitaire du 28 janvier 2025 et presentes au Conseil d'Administration du 3 fevrier 2025.
10+ai_tool_treatment: UM's digital-services guidance says the university provides institutional Microsoft Copilot access through A1 and A3 licences for staff and students, with data-protection advantages.
11+Evidence (fr, cfd6ea215023): L'Universite de Montpellier a un acces institutionnel a Copilot avec les licences A1 et A3 mises a disposition des personnels et etudiants. Cela signifie que vous beneficiez d'avantages, comme celui de la protection de vos donnees.
12+teaching: UM's official AI hub says it offers multiple pathways to help teachers, researchers, staff, and students discover and appropriate AI uses, including AI tools/platforms, resources, self-training, and student acculturation.
13+Evidence (fr, 81283164d517): Cet espace propose plusieurs parcours pour accompagner enseignants, chercheurs, personnels et etudiants dans la decouverte et l'appropriation des usages de l'IA. Contenu disponible : Outils & plateformes IA; Ressources & replays; Formations en autoformation; Acculturation des etudiants.

Claim changes

6 claim records

teaching

UM's official AI hub says it offers multiple pathways to help teachers, researchers, staff, and students discover and appropriate AI uses, including AI tools/platforms, resources, self-training, and student acculturation.

Review: Agent reviewedConfidence84%Evidence1Languagesfr

ai_tool_treatment

UM's digital-services guidance says the university provides institutional Microsoft Copilot access through A1 and A3 licences for staff and students, with data-protection advantages.

Review: Agent reviewedConfidence88%Evidence1Languagesfr

academic_integrity

UM's AI-in-training principles say student AI use should respect university regulations, rules for each teaching activity, and assessment-specific instructions; expectations should be clarified in course and assessment materials.

Review: Agent reviewedConfidence93%Evidence1Languagesfr

privacy

UM's AI-in-training principles say confidentiality, privacy, personal data, and intellectual property protections should be guaranteed, and no nominative, confidential, or sensitive data should be used in a public AI tool.

Review: Agent reviewedConfidence95%Evidence1Languagesfr

teaching

UM's AI-in-training principles say decisions to use or address AI in training activities rest with teaching staff and should align with learning objectives.

Review: Agent reviewedConfidence92%Evidence1Languagesfr

source_status

Universite de Montpellier has official AI-in-training principles, but this staged crawl found no separate central binding AI policy page.

Review: Agent reviewedConfidence90%Evidence1Languagesfr

Source snapshots

3 source attributions