Policy presence
University of Münster has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Munster, Germany
University of Münster
University of Münster is listed as QS 2026 rank =350. University of Münster has 7 source-backed AI policy claim records from 6 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
University of Münster is listed as QS 2026 rank =350. University of Münster has 7 source-backed AI policy claim records from 6 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of Münster as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 7 source-backed claims, including 7 reviewed claims, from 6 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-munster.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 Privacy claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Academic integrity claims.
- Evidence includes Research claims.
- No specific AI service name is highlighted by the current public claim text.
- Disclosure, acknowledgment, citation, or attribution language appears in the 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
University of Münster has 3 source-backed public claims for ai disclosure; deterministic analysis status: recommended.
Coursework
University of Münster has 1 source-backed public claim for coursework; deterministic analysis status: allowed.
Exams
University of Münster has 4 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
University of Münster has 2 source-backed public claims for privacy and data entry; deterministic analysis status: blocked.
Academic integrity
University of Münster has 3 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
University of Münster has 1 source-backed public claim for approved tools; deterministic analysis status: allowed.
Named AI services
University of Münster has 3 source-backed public claims for named ai services; deterministic analysis status: blocked.
Teaching guidance
University of Münster has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Münster has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
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
7 reviewed evidence-backed public claim
Privacy
UniGPT terms distinguish local and external models: local models may process confidential V3 information but not strictly confidential V4 information, while external models may receive only public V1 information.
Review: Agent reviewed
Normalized value: local_models_v3_allowed_v4_forbidden_external_models_v1_only
Original evidence
Evidence 1Bei der Nutzung von lokalen Modellen verbleiben die Daten innerhalb der Universität Münster. Hierbei dürfen Informationen der Vertraulichkeitsklasse "vertraulich" (V3) von den Nutzer*innen übermittelt werden ... Informationen, die als streng vertraulich (V4) klassifiziert worden sind, dürfen nicht durch Nutzer*innen verarbeitet werden. ... Bei Nutzung extern gebundener Modelle erfolgt eine Datenverarbeitung durch externe Anbieter. Dabei dürfen nur Informationen der Vertraulichkeitsklasse "öffentlich" (V1) übermittelt werden
Localized display only
Local UniGPT models keep data within the university and may receive V3 information but not V4; external models may receive only public V1 information.
Privacy
The UniGPT privacy page states that user-generated chat data is not used to train models; logs and metrics are automatically deleted after 14 days, and other data is automatically deleted after six months without login.
Review: Agent reviewed
Normalized value: chats_not_used_for_training_logs_14_days_other_data_6_months_without_login
Original evidence
Evidence 1Nutzer*innengenerierte Daten (Chats) werden nicht für das Training von Modellen verwendet. ... Logs und Metriken werden nach 14 Tagen automatisch gelöscht. Alle anderen Daten werden nach 6 Monaten ohne Login automatisch gelöscht. ... Bei der Nutzung externer Modelle werden nutzergenerierte Daten (Prompts) zu externen Anbietern übermittelt.
Localized display only
User-generated chats are not used for model training; logs and metrics are deleted after 14 days, and other data after six months without login.
Ai Tool Treatment
University of Munster provides UniGPT as a chatbot service for research, teaching, and administration, offering on-premise models in the Uni Cloud and external models; the service page says on-premise model data remains within the university.
Review: Agent reviewed
Normalized value: unigpt_available_on_premise_and_external_models
Original evidence
Evidence 1UniGPT ist ein Chatbot-Service der Universität Münster, der mittels fortschrittlicher Sprachmodelltechnologie verschiedene Large Language Models (LLM) für Forschung, Lehre und Verwaltung bereitstellt. Der Dienst integriert sowohl eigene on-premise Modelle, aktuell LLaMA 3.1-70B und Mixtral 8x7B, als auch externe Modelle wie GPT-3.5 und (für Beschäftigte) GPT-4 von OpenAI. Das on-premise Model wird in der Uni Cloud auf Servern der Universität Münster betrieben und eignet sich besonders für sensible Daten und Projekte, bei denen Datenschutz im Vordergrund steht.
Localized display only
UniGPT is a University of Munster chatbot service for research, teaching, and administration, with on-premise and external models.
Academic Integrity
University of Munster central guidance states that whether generative AI systems may be used for examination work depends on the assessed competency and is set by examination regulations and examiners; for work where expression, translation, or code creation is itself assessed, use is generally not permissible.
Review: Agent reviewed
Normalized value: permission_contextual_by_exam_regulations_and_examiners
Original evidence
Evidence 1Ob generative KI-Systeme zur Erbringung von Prüfungsleistungen statthaft sind, hängt von der jeweils geprüften Kompetenz ab und wird in den Prüfungsordnungen und von den Prüfenden festgelegt. Handelt es sich z.B. um Leistungen, bei denen die Ausdrucksform, Sprachübertragung oder das Erstellen von Computercode Gegenstand der Prüfung ist, ist die Verwendung dieser Systeme in der Regel nicht statthaft.
Localized display only
Whether generative AI systems may be used for examination work depends on the assessed competency and is set by examination regulations and examiners.
Research
University of Munster central guidance says it orients itself to the DFG statement on generative models for text and image creation in research, including disclosure of whether, which, why, and how extensively generative models were used when results are made publicly accessible.
Review: Agent reviewed
Normalized value: research_orients_to_dfg_generative_ai_statement
Original evidence
Evidence 1Für den Bereich Forschung hat das Präsidium der DFG am 21.09.2023 in einer Stellungnahme Leitlinien zum Umfang mit generativen Modellen zur Text- und Bilderstellung herausgegeben, an denen sich die Universität Münster orientiert: ... Wissenschaftlerinnen und Wissenschaftler sollten bei der öffentlichen Zugänglichmachung ihrer Ergebnisse im Sinne wissenschaftlicher Integrität offenlegen, ob und welche generativen Modelle sie zu welchem Zweck und in welchem Umfang eingesetzt haben.
Localized display only
For research, the page says the University of Munster orients itself to DFG guidance, including disclosure of generative-model use when results are made publicly accessible.
Academic Integrity
For Faculty 06, the dean's office recommends that generative AI content in examination work be clearly cited, that an explanation of tool use be added, and that full prompts and AI responses be appended; instructors may adapt or reduce these documentation and citation duties for individual exams or courses.
Review: Agent reviewed
Normalized value: faculty_06_recommends_citation_declaration_prompt_appendix_instructors_may_adapt
Original evidence
Evidence 1Das Dekanat gibt folgende Leitlinie als Empfehlung heraus: Inhalte und Textstellen, die mit generativer KI erstellt wurden, müssen durch Zitationsangaben eindeutig gekennzeichnet werden. ... Wenn Systeme und Programme der künstlichen Intelligenz als Hilfsmittel eingesetzt werden, muss der betreffenden Arbeit eine Erklärung hinzugefügt werden ... Lehrende sind berechtigt, die oben beschriebenen Dokumentations- und Zitationspflichten im Rahmen einzelner Prüfungen und Lehrveranstaltung anzupassen oder zu reduzieren.
Localized display only
Faculty 06 recommends citation of AI-generated content, an explanation of AI-tool use, and permits instructors to adapt documentation and citation duties.
Academic Integrity
The University and State Library Munster advises users to ask instructors or their university before using generative AI for academic work and warns that AI use in examination documents can be evaluated as attempted deception.
Review: Agent reviewed
Normalized value: library_guidance_ask_before_use_exam_deception_risk
Original evidence
Evidence 1Erkundigen Sie sich unbedingt vor der Verwendung von generativer KI bei Ihren Dozent*innen/Ihrer Hochschule inwiefern Sie für Ihre wissenschaftliche Arbeit generative KIs verwenden dürfen. Was müssen Sie dabei beachten? Muss die Verwendung von generativer KI (inklusive Prompt) in Ihrer Arbeit angegeben werden? ... Gerade wenn es sich bei Ihren Arbeiten um Prüfungsunterlagen handelt, ist das eine heikle Frage und kann als Täuschungsversuch gewertet werden.
Localized display only
The library guide tells users to ask instructors or the university before using generative AI in academic work and warns that use in examination documents may be treated as attempted deception.
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
6 source attribution
Chancen und Risiken des Einsatzes von Kunstlicher Intelligenz (KI)
uni-muenster.de
CIT - UniGPT
uni-muenster.de
CIT - UniGPT Datenschutzerklarung
uni-muenster.de
CIT - UniGPT Nutzungsbedingungen
uni-muenster.de
ULB-LOTSE: ChatGPT & Co
ulb.uni-muenster.de
Umgang mit KI
uni-muenster.de
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.