Policy presence
Université de Lille has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Lille, France
Université de Lille
Université de Lille has 5 source-backed AI policy claims from 2 official source attributions. Review state: agent reviewed; 5 reviewed claims. Last checked May 18, 2026.
Université de Lille AI policy short answer
v1 public contract
Université de Lille has 5 source-backed AI policy claims from 2 official source attributions, including 5 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 18, 2026. Discovery context: Université de Lille is listed as QS 2026 rank =654.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Université de Lille as an agent-reviewed AI policy record last checked on May 18, 2026 and last changed on May 18, 2026. The record contains 5 source-backed claims, including 5 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/universite-de-lille.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 Privacy claims.
- Evidence includes Teaching claims.
- Evidence includes Source status 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.
- Privacy, sensitive-data, or security 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 Lille has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
Université de Lille has 3 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Université de Lille has 3 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
Université de Lille has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Université de Lille has 1 source-backed public claim for academic integrity; deterministic analysis status: blocked.
Approved tools
Université de Lille has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.
Named AI services
Université de Lille has 2 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Université de Lille 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
5 reviewed evidence-backed public claim
Academic Integrity
Universite de Lille's SIAG charter says presenting content generated by generative AI systems as one's own production is prohibited and that using AI to paraphrase others' content is considered a form of plagiarism.
Review: Agent reviewed
Normalized value: presenting_siag_content_as_own_work_is_prohibited_and_ai_paraphrase_can_be_plagiarism
Original evidence
Evidence 1Fraude et Plagiat : Présenter des contenus générés par SIAG comme sa propre production est interdit. L’utilisation de l’IA pour paraphraser des contenus d’autrui est considéré comme une forme de plagiat, dans la mesure où elle rend complexe l’identification de toute production originale et représente une forme de dissimulation.
Localized display only
The charter prohibits presenting SIAG-generated content as one's own and treats AI paraphrasing of others' content as a form of plagiarism.
Ai Tool Treatment
Universite de Lille's SIAG charter says any use of generative AI systems in academic work should be clearly indicated, including how, to what extent, and for what objectives AI was used.
Review: Agent reviewed
Normalized value: siag_use_in_academic_work_should_be_clearly_indicated
Original evidence
Evidence 1Toute utilisation de SIAG dans la production de travaux académiques doit être clairement indiquée. Les utilisateurs doivent spécifier comment et dans quelle mesure l'IAG a été employée et pour quels objectifs.
Localized display only
Any SIAG use in academic work should be clearly indicated, including how, to what extent, and for what objectives AI was used.
Privacy
Universite de Lille's SIAG charter advises users not to transmit sensitive documents or personal data to externally hosted generative AI systems and to check confidentiality policies and GDPR compliance.
Review: Agent reviewed
Normalized value: do_not_transmit_sensitive_documents_or_personal_data_to_external_siag
Original evidence
Evidence 1Protection des données : Ne pas transmettre de documents sensibles ou des données personnelles à des SIAG hébergés en externe. S’assurer des politiques de confidentialité des outils utilisés avant de les intégrer dans un projet universitaire. S’assurer du respect du Règlement Général de Protection des Données (RGPD).
Localized display only
The charter advises users not to send sensitive documents or personal data to externally hosted SIAG tools and to check confidentiality policies and GDPR compliance.
Teaching
Universite de Lille's SIAG charter says teachers should specify SIAG-use instructions in their courses, inform students how SIAG use is or is not integrated into learning situations and assessments, and cannot require students to use SIAG tools that need personal data or payment.
Review: Agent reviewed
Normalized value: teachers_specify_siag_course_rules_and_cannot_require_personal_data_or_paid_siag
Original evidence
Evidence 1Le personnel enseignant ne peut pas obliger les étudiants à utiliser des SIAG nécessitant des données personnelles pour se connecter ou s'inscrire, ou entraînant des coûts dans le cadre de leur formation. Les enseignants doivent spécifier les consignes d’utilisation des SIAG dans leurs cours.
Localized display only
Teachers cannot require SIAG tools needing personal data or payment, and should specify SIAG-use instructions in their courses.
Source Status
Universite de Lille has an official 2025 charter of good practices for generative AI systems in pedagogical work; an official university page says the charter was finalized in March 2025 and aims to frame SIAG uses responsibly and transparently.
Review: Agent reviewed
Normalized value: official_2025_siag_good_practices_charter_for_pedagogical_work
Original evidence
Evidence 1Cette charte vise à encadrer les usages des SIAG dans un esprit de responsabilité, de transparence et de respects des valeurs universitaires, tout en encourageant un apprentissage enrichi et innovant. Face à l’essor rapide des outils d’intelligence artificielle générative, l’université de Lille a choisi d’accompagner les usages plutôt que de les restreindre.
Localized display only
The official page says the charter frames SIAG uses responsibly and transparently, and that Universite de Lille chose to support uses rather than restrict them.
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
2 source attribution
Charte des bonnes pratiques d'utilisation des IAG dans les travaux pédagogiques
edsmre.univ-lille.fr
Charte des bonnes pratiques d'utilisation des intelligences artificielles génératives dans les travaux pédagogiques
psysef.univ-lille.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.