Ten-school policy record and evidence correction

UChicago tool classifications corrected: directory approval is not institutional recommendation; Chrome AI extensions require specific-use review. Existing evidence, access conditions and assessment rules are preserved. This is a Tracker correction, not a new University policy.

Historical correction: counts and claims reflect this version, not the latest selected record.

2026-10-15T02:32:16.611Z · v6-chicago-tools-20261014

• ETH Zurich (Swiss Federal Institute of Technology Zurich) · 15 reviewed current records · View policy page
  • Added records: 0; Corrected records: 0; Historical / held: 0

Previous V6 release history

Record revision, scope and original evidence

Original evidence and audience, course and unit scopes are preserved. Tracker correction time is not a policy effective date.

0318627152f6c22e70b727831eb2a046ac48f2e7c310c84878edfa5a97f2a8f8

{
  "addedClaimIds": [],
  "updatedClaimIds": [],
  "heldClaimIds": []
}

• cl-eth-zurich-gemini-45 — Google Gemini is officially licensed and provided to ETH Zurich employees and students free of charge through the ETH Google Workspace Cloud Subscription with enterprise data protection (no model training). CISO cloud assessment remains OPEN; Google tools are not approved for confidential or protected personal data. An optional fee-based Google AI Pro license is available for employees.
• cl-eth-zurich-microsoft-copilot-46 — Microsoft Copilot is officially licensed for ETH Zurich. M365 Copilot Chat is available free to all members and approved for internal data. M365 Copilot Work mode without web search is approved for confidential data for licensed employees. Uploading strictly confidential data is prohibited.
• cl-eth-zurich-notebooklm-47 — Google NotebookLM is officially available free of charge to ETH Zurich members through the Google Workspace Cloud Subscription with enterprise data protection. CISO cloud assessment remains OPEN; tools lacking assessment have not been released for confidential or personal ETH data.
• cc-eth-zurich-a3ed60700a9a8d80 — ETH Zurich advocates a proactive approach to the use of generative AI in educational contexts, emphasising responsible use among students and lecturers.
• cc-eth-zurich-b2226b51825107d5 — Students are responsible for the content of work they submit. Performance assessments must be conducted independently and personally; GenAI may serve a supplementary role but not replace student efforts.
• cc-eth-zurich-0baba14322b53072 — Lecturers determine whether and how GenAI may be used in their courses and for respective assessments. Teaching materials created with GenAI must be subjected to quality control by the lecturer.
• cc-eth-zurich-47f48fedc92290ac — Violations of GenAI guidelines such as use of unauthorised aids or non-disclosure of their use are subject to disciplinary action under existing performance assessment rules and the declaration of originality.
• cc-eth-zurich-3ecccc0b6798ed66 — ETH Zurich recommends Microsoft Copilot, Google Gemini, and NotebookLM for teaching purposes, as they offer data-protected access via ETH accounts where personal data is not used for training models.
• cc-eth-zurich-04547e201e6c33a4 — Students must refrain from disclosing copyrighted, private, or confidential information to commercial GenAI clients unless expressly permitted, and must respect privacy and copyright of content they work with.
• cc-eth-zurich-46ad6a07df059f93 — ETH Zurich's teaching guidelines instruct students to be transparent about their use of generative AI and to identify which tools contributed to which parts of their work, in accordance with applicable lecturer instructions and citation conventions. For scientific writing and theses, students should agree in advance with their supervisors on authorised AI use and disclosure requirements. ETH Library guidance recognises an exception where a supervisor has expressly agreed that particular AI use need not be separately declared. In the absence of such an agreement, undeclared use may constitute a breach of academic integrity.
• cc-eth-zurich-9184c974106f677e — ETH Zurich states that technical recognition of AI-generated output is currently unreliable and will probably remain so; trust in such methods is not appropriate.
• clm-eth-zurich-originality-declaration-ai-2026 — ETH Zurich's declaration of originality provides two options: confirming that no generative AI was used, or confirming that authorised generative AI was used and its disclosure agreed with the supervisor. Bachelor's and Master's theses require a signed declaration of originality, while requirements for other written assessments depend on the applicable academic instructions. Doctoral candidates declare independent authorship through the doctoral examination registration process. The permitted use, disclosure format and any exceptions must follow the relevant supervisor and unit requirements.
• clm-eth-zurich-ai-data-classification-2026 — ETH Zurich prohibits the processing of strictly confidential information in external cloud AI services. Confidential information may be processed only in services and configurations explicitly approved for that classification. ETH IT guidance distinguishes Microsoft 365 Copilot Work mode without web search, which is approved for confidential data, from Copilot Chat and web mode, which are approved for internal data. Unassessed AI services must not be used for confidential ETH data or protected personal data.
• clm-eth-zurich-research-genai-authorship-disclosure — ETH Library guidance requires researchers to remain responsible for their scientific work and to verify AI-generated information, references and quotations. Generative AI tools cannot be listed as scientific authors or relied upon as authoritative scientific sources. Researchers should agree on permitted AI use with collaborators and follow applicable departmental, funder, publisher and journal requirements. Disclosure of an AI tool's contribution is distinct from citing that tool as evidence for a scientific claim.
• clm-eth-zurich-turnitin-similarity-and-ai-detection — ETH Library provides Turnitin Originality to eligible professors and lecturers for text-similarity checking, subject to data classification and responsible selective-use guidance. Only public or internal documents may be uploaded. Similarity screening is distinct from AI-authorship detection; ETH Zurich warns that technical detection of AI-generated output is unreliable and should not be treated as conclusive evidence.

Public student snapshot endpoint returns HTTP 404 (Not Found). Local 6-dimension candidate draft prepared in outputs/student-topics.json but not a published strong student snapshot.

Google AI tools (Gemini Chat, NotebookLM, Google AI Pro) have not completed CISO cloud assessment (status OPEN). Unassessed tools are not released for ETH confidential, strictly confidential, or protected personal data.

Turnitin Originality access is restricted to professors and lecturers, but fee structure (free/central vs departmental) is not stated on official page.

Disciplinary appeal stages, legal deadlines, and administrative court review procedures are governed by general Swiss administrative law and ETH regulations, but full statute texts were not crawled.

Explicit disability adjustment or assistive technology exceptions for generative AI are not detailed in current teaching guidelines.