Change log

École polytechnique fédérale de Lausanne

Source-backed change history with no release-to-release policy diff rows recorded yet; current claims, official sources, review state, and freshness remain visible across 0 public release records.

Review: Agent reviewedLast checkedMay 10, 2026Last changedMay 10, 2026Claims5Sources6Release records0

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École polytechnique fédérale de Lausanne currently has 5 source-backed claim records and 6 official source attributions. Latest tracked changed date: May 10, 2026. No tracker diff rows are recorded in the latest public release.

This page combines all public release diffs for École polytechnique fédérale de Lausanne. Individual release snapshots remain available from their release-specific URLs.

No release-to-release policy diff rows are recorded for this university yet. The page still tracks current source-backed claims, official source attributions, review state, source freshness, and public JSON for discovery and citation.

This tracker 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.

Newly extracted claims are tracker additions and are not necessarily newly published by the university. Source snapshot changes show hash changes for the same source URL and are not by themselves policy changes.

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11 # EPFL – École polytechnique fédérale de Lausanne AI policy record
2+privacy: EPFL advises students not to input confidential, private or personal information into generative AI tools. When using generative AI tools, students are sharing data with private companies and lose control over it.
3+Evidence (en, 5eeaf435b051): Never input confidential, private or personal information about yourself or others into these tools. Always reflect first on the nature of the information you are using, because once you enter it into one of these tools, it’s no longer confidential.
4+academic_integrity: EPFL requires students to disclose the use of AI tools in assessment work. EPFL rules (Lex 1.3.3, Article 4) require that all assessment material that is not the student's personal and original contribution must be recognizable as such.
5+Evidence (en, 87edcd847e7d): EPFL rules (Lex 1.3.3, Article 4) require that all assessment material that is not the student’s personal and original contribution must be recognizable as such. Therefore, the use of AI tools should be disclosed in a statement.
6+teaching: EPFL recommends that teachers make explicit to students what AI use is not legitimate in a course and what rules accompany AI tool use.
7+Evidence (en, fba7ab5ff6ba): Since there is no ‘one-size-fits-all’ rule regarding the use of AI in assessment, it is recommended that teachers make explicit to students what kind of use is not legitimate in their course, and what rules accompany the use of AI tools.
8+academic_integrity: EPFL considers the use of AI-generated content in assignments without proper attribution as AI plagiarism. Tools that detect AI-generated content are not admissible as stand-alone evidence of AI plagiarism due to high risk of false positives.
9+Evidence (en, 2760bf9bac8e): The use of AI-generated content in assignments without proper attribution is considered AI plagiarism. Tools that specifically aim to detect whether content was AI-generated (e.g., turnitin ) are not admissible as stand-alone evidence of AI plagiarism due to their high risk of false positives
10+privacy: EPFL guidance says enterprise licenses such as Microsoft 365 Copilot via EPFL account are currently not a secure solution for processing regulated data because EPFL has not signed a data processing agreement guaranteeing aligned data protection measures.
11+Evidence (en, 2760bf9bac8e): However, enterprise licenses such as Microsoft 365 Copilot via your EPFL account are currently not a secure solution for processing regulated data, because no data processing agreement has been signed by EPFL that would guarantee that data protection measures align with institutional needs or with Swiss legislation on personal data protection.

Release history

0 public release diffs

Claim changes

5 claim records

privacy

EPFL advises students not to input confidential, private or personal information into generative AI tools. When using generative AI tools, students are sharing data with private companies and lose control over it.

Review: Agent reviewedConfidence96%Evidence1Languagesen

academic_integrity

EPFL requires students to disclose the use of AI tools in assessment work. EPFL rules (Lex 1.3.3, Article 4) require that all assessment material that is not the student's personal and original contribution must be recognizable as such.

Review: Agent reviewedConfidence95%Evidence1Languagesen

teaching

EPFL recommends that teachers make explicit to students what AI use is not legitimate in a course and what rules accompany AI tool use.

Review: Agent reviewedConfidence94%Evidence1Languagesen

academic_integrity

EPFL considers the use of AI-generated content in assignments without proper attribution as AI plagiarism. Tools that detect AI-generated content are not admissible as stand-alone evidence of AI plagiarism due to high risk of false positives.

Review: Agent reviewedConfidence93%Evidence1Languagesen

privacy

EPFL guidance says enterprise licenses such as Microsoft 365 Copilot via EPFL account are currently not a secure solution for processing regulated data because EPFL has not signed a data processing agreement guaranteeing aligned data protection measures.

Review: Agent reviewedConfidence92%Evidence1Languagesen