Policy presence
Aix-Marseille University has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Open, evidence-backed AI policy records for public reuse.
Marseille, France
Aix-Marseille University is listed as QS 2026 rank =428. Aix-Marseille University has 4 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
v1 public contract
Aix-Marseille University is listed as QS 2026 rank =428. Aix-Marseille University has 4 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
As of this public record, University AI Policy Tracker lists Aix-Marseille University as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 2 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/aix-marseille-university.json. The entity-level confidence is 86%. 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.
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.
Deterministic source-backed dimensions derived from this record's public claims.
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.
Aix-Marseille University has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Aix-Marseille University has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Aix-Marseille University has 3 source-backed public claims for coursework; deterministic analysis status: required.
Aix-Marseille University has 3 source-backed public claims for exams; deterministic analysis status: required.
Aix-Marseille University has 2 source-backed public claims for privacy and data entry; deterministic analysis status: required.
Aix-Marseille University has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
Aix-Marseille University has 1 source-backed public claim for approved tools; deterministic analysis status: required.
Aix-Marseille University has 3 source-backed public claims for named ai services; deterministic analysis status: required.
Aix-Marseille University has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.
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.
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.
4 reviewed evidence-backed public claim
Academic Integrity
Normalized value: AI use in evaluated work is treated as fraud unless expressly authorized, per reported AMU 2024/2025 M3C note.
Original evidence
Evidence 1Suite à une réflexion et validation en CFVU, AMU a intégré une mention dans ses documents de cadrage des Modalités de contrôle des connaissances et des compétences (M3C) pour l’année universitaire 2024/2025 : « L’utilisation par les étudiants d’outils d’intelligence artificielle (comme ChatGPT ou autre) lors de la production de travaux personnels ou de groupe de toute nature, susceptible de faire l’objet d’une évaluation, est considérée comme une fraude passible de poursuites disciplinaires, à moins qu’elle ne soit expressément autorisée.
Localized display only
After CFVU validation, AMU integrated a 2024/2025 M3C note treating student AI use in evaluated work as fraud unless expressly authorized.
Ai Tool Treatment
Normalized value: Authorized AI use in evaluated work should be explicitly mentioned.
Original evidence
Evidence 1Dans ce cas, elle devra être explicitement mentionnée, comme n’importe quel emprunt ou citation d’une source externe.
Localized display only
When AI use is authorized, the note says it should be explicitly mentioned like any borrowing or citation from an external source.
Teaching
Normalized value: AMU ObsiaFormation supports AI use in teaching and learning.
Original evidence
Evidence 1L’Observatoire des usages et laboratoire de pratiques de l’IA en formation a pour vocation d’accompagner dans l’appropriation des usages de l’Intelligence Artificielle en enseignement et apprentissage.
Localized display only
ObsiaFormation states that its role is to support appropriation of AI uses in teaching and learning.
Privacy
Normalized value: ObsiaFormation guide advises reliability checks and ethics/data-protection attention for educational AI use.
Original evidence
Evidence 1Parmi les bonnes pratiques : Ne pas surcharger les étudiants avec trop d’automatisation, privilégier une approche équilibrée. Vérifier la pertinence et la fiabilité des outils et de leurs contributions avant de les intégrer. Respecter les principes d’éthique, notamment en matière de protection des données.
Localized display only
The guide lists good practices including balanced use, checking tool reliability and outputs, and respecting ethics including data protection.
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.
2 source attribution
observatoire-ia-formation.univ-amu.fr
observatoire-ia-formation.univ-amu.fr
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