Policy presence
Philipps-Universität Marburg has 2 source-backed public claims for policy presence; deterministic analysis status: unclear.
Marburg, Germany
Philipps-Universität Marburg
Philipps-Universität Marburg has 4 source-backed AI policy claims from 3 official source attributions. Review state: agent reviewed; 4 reviewed claims. Last checked May 20, 2026.
Philipps-Universität Marburg AI policy short answer
v1 public contract
Philipps-Universität Marburg has 4 source-backed AI policy claims from 3 official source attributions, including 4 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 20, 2026. Discovery context: Philipps-Universität Marburg is listed as QS 2026 rank 771-780.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Philipps-Universität Marburg as an agent-reviewed AI policy record last checked on May 20, 2026 and last changed on May 20, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/philipps-universitat-marburg.json. The entity-level confidence is 92%. 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 Teaching claims.
- Evidence includes Academic integrity 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.
- 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
Philipps-Universität Marburg has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
Philipps-Universität Marburg has 3 source-backed public claims for coursework; deterministic analysis status: blocked.
Exams
Philipps-Universität Marburg has 3 source-backed public claims for exams; deterministic analysis status: blocked.
Privacy and data entry
Philipps-Universität Marburg has 2 source-backed public claims for privacy and data entry; deterministic analysis status: blocked.
Academic integrity
Philipps-Universität Marburg has 2 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
No source-backed public claim identifying approved or licensed AI tools is present in this profile.
The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.
Named AI services
Philipps-Universität Marburg has 1 source-backed public claim for named ai services; deterministic analysis status: restricted.
Teaching guidance
Philipps-Universität Marburg has 2 source-backed public claims 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
4 reviewed evidence-backed public claim
Privacy
The HRZ AI services page says the university offers generative AI services via GWDG KI-Cloud and lists usage rules including no prompt/file input of personal, confidential, or security-relevant data and transparent disclosure when the service is used.
Review: Agent reviewed
Normalized value: gwdg_ki_cloud_rules_no_sensitive_data_transparency
Original evidence
Evidence 1Geben Sie niemals personenbezogene, vertrauliche oder sicherheitsrelevante Daten über den Prompt ein bzw. stellen sie diese niemals dem genKI-Modell über Dateien zur Verfügung. ... Sollte der Dienst genutzt werden, muss dies transparent angegeben werden.
Localized display only
Do not enter personal, confidential, or security-relevant data through prompts or files; if the service is used, this must be transparently stated.
Teaching
Philipps-Universität Marburg's central teaching-and-AI orientation says the university does not prohibit generative AI and frames the guidance around exploring productive use in teaching and teaching organization.
Review: Agent reviewed
Normalized value: central_guidance_not_general_ban
Original evidence
Evidence 1Die UMR verbietet nicht den Einsatz generativer KI. Dazu gehören sprachbasierte KI-Anwendungen (z.B. ChatGPT) ebenso wie bildgenerierende KI-Anwendungen (z.B. DALL-E, Midjourney).
Localized display only
UMR does not prohibit the use of generative AI, including language-based applications such as ChatGPT and image-generating applications.
Academic Integrity
The central teaching-and-AI orientation recommends that, for written work, AI-generated text parts be marked as such as a matter of good scientific practice.
Review: Agent reviewed
Normalized value: ai_generated_text_parts_should_be_marked
Original evidence
Evidence 1Gute wissenschaftliche Praxis erfordert, dass KI-generierte Textteile als solche gekennzeichnet werden.
Localized display only
Good scientific practice requires that AI-generated text parts be identified as such.
Academic Integrity
A Fachbereich 03 Empirische Kulturwissenschaft page states that information taken directly or indirectly from AI tools must be marked, otherwise it is a deception attempt; this claim is limited to that page's department-scoped guidance.
Review: Agent reviewed
Normalized value: fb03_ai_derived_information_must_be_marked
Original evidence
Evidence 1In jedem Fall müssen Informationen, die direkt oder sinngemäß aus einem solchen Tool stammen, gekennzeichnet werden, andernfalls handelt es sich hierbei um einen Täuschungsversuch.
Localized display only
Information taken directly or indirectly from such a tool must be marked; otherwise this is a deception attempt.
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
3 source attribution
KI-gestützte Dienste (GWDG KI-Cloud)
uni-marburg.de
Positionspapier Lehre und KI
uni-marburg.de
Umgang mit künstlicher Intelligenz im Rahmen von wissenschaftlichen Arbeiten
uni-marburg.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.