Vienna, Austria

Technische Universität Wien

Technische Universität Wien is listed as QS 2026 rank =197. Technische Universität Wien has 4 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

Technische Universität Wien is listed as QS 2026 rank =197. Technische Universität Wien has 4 source-backed AI policy claim records from 4 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 Technische Universität Wien as an agent-reviewed AI policy record last checked on May 15, 2026 and last changed on May 15, 2026. The record contains 4 source-backed claims, including 4 reviewed claims, from 4 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/technische-universitat-wien.json. The entity-level confidence is 93%. 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.

Claim coverage4 reviewedSource languagedePublic JSON/api/public/v1/universities/technische-universitat-wien.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes Privacy claims.
  • Evidence includes Teaching claims.
  • Named AI services detected in public claims: ChatGPT.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims4Reviewed4Candidate0Official sources4

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.

Coverage score90/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence78%

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

Technische Universität Wien has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.

RequiredMachine candidateConfidence79%Evidence1Sources1

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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

Academic Integrity

TU Wien's student guidance says ChatGPT and other large language models must be documented as aids in written work, AI-used passages must be marked, and undisclosed generative-AI use in student work is treated as equivalent to plagiarism.

Review: Agent reviewedConfidence93%

Normalized value: disclose_and_mark_genai_use_in_written_work

Original evidence

Evidence 1
ChatGPT und andere Large Language Models müssen als Hilfsmittel dokumentiert und die Stellen, bei denen KI’s eingesetzt wurden, entsprechend markiert werden. ... Es ist wichtig zu verstehen, dass die nicht offengelegte Verwendung von generativer KI in einer studentischer Arbeit einem Plagiat gleichkommt.

Localized display only

ChatGPT and other large language models must be documented as aids and AI-used passages marked; undisclosed generative-AI use in a student work is treated as equivalent to plagiarism.

Privacy

TU Wien's teacher handout tells instructors to raise awareness that data entered into AI models requires caution and compliance with data-protection rules, and warns not to enter personal or identifying data in prompts.

Review: Agent reviewedConfidence92%

Normalized value: avoid_personal_or_identifying_data_in_ai_prompts

Original evidence

Evidence 1
Schaffen Sie in Ihrer Lehrveranstaltung Bewusstsein dafür, dass man bei der Eingabe von Daten in das Modell vorsichtig sein und die gesetzlichen Regeln zum Datenschutz einhalten muss. Achtung: Geben Sie niemals personenbezogene Daten von sich und insbesondere von anderen Personen ... ein oder Daten, die Personen identifizierbar machen.

Localized display only

Instructors should raise awareness that data entered into the model requires caution and compliance with data-protection rules; never enter personal or identifying data.

Academic Integrity

TU Wien's teacher handout says reliable technical identification of AI-tool use is hardly possible and recommends adapting exam formats so they cannot be solved exclusively by AI outputs.

Review: Agent reviewedConfidence91%

Normalized value: assessment_design_should_account_for_ai_detection_limits

Original evidence

Evidence 1
Eine zuverlässige technische Identifikation des Einsatzes von KI-Tools ist kaum möglich. ... Prüfungsformate werden so umgestaltet, dass Sie nicht ausschließlich durch KI-Outputs gelöst werden können.

Localized display only

Reliable technical identification of AI-tool use is hardly possible; exam formats should be redesigned so they cannot be solved exclusively by AI outputs.

Teaching

TU Wien's generative-AI teaching guidance says instructors decide whether to use AI systems in courses; if they do, the rules must be clearly defined and the handling of those technologies must be made central.

Review: Agent reviewedConfidence90%

Normalized value: instructor_discretion_with_clear_course_rules

Original evidence

Evidence 1
Die Entscheidung, ob Lehrkräfte KI-Systeme verwenden obliegt ihnen selbst. Sollten diese verwendet werden, dann müssen die Vorgaben klar definiert sein und der Umgang mit diesen entsprechend in den Fokus gestellt werden.

Localized display only

The decision whether instructors use AI systems is up to them; if used, the rules must be clearly defined and handling of the technologies must be made central.

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

4 source attribution

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.

Last checkedMay 15, 2026Last changedMay 15, 2026Open change log

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.

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