Change log
Release-to-release tracker diff with separate policy-text, newly-extracted claim, evidence, and source snapshot categories.
Current public record freshness and review state.
University of Texas at Austin currently has 11 source-backed claim records and 6 official source attributions. Latest tracked changed date: May 13, 2026. No tracker diff rows are recorded in the latest public release.
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.
Semantic classification for this release diff.
Unified tracker diff generated from the previous and current public release snapshots.
No tracker claim/evidence/source changes are recorded for this university in the latest public release.
11 claim records
UT Austin acceptable-use guidance says published university information may be used freely with AI tools, while controlled or confidential university information can be used only with university-managed AI tools covered by contracts that protect university data and disable web search functionality.
UT Austin acceptable-use guidance says unauthorized AI tools are not approved for controlled or confidential university information, including student records subject to FERPA, health information, proprietary information, and other controlled or confidential data.
UT Austin AI detection guidance prohibits third-party AI detection software from being used to evaluate student work or assignments unless a university contract or purchase order is in place.
UT Austin acceptable-use guidance says the CISO must review AI tools before procurement, development, deployment, or use when the tools are intended to autonomously make, or be a controlling factor in making, consequential decisions.
UT Austin responsible-adoption guidance defines responsible AI use in teaching and learning as adopting AI in ways that facilitate learning outcomes and foster human development for campus community members.
UT Austin AI detection guidance says submitting student work into AI detection or other third-party software without a university contract or purchase order may violate student copyright, intellectual property, or FERPA privacy rights.
UT Austin responsible-adoption guidance includes academic integrity as a principle for AI use, linking responsible use to the honor code, scholarly values, ownership, and appropriate authorship of tool outputs.
UT Austin graduate-education recommendations state that graduate students and mentors must use only vetted, university-contracted generative AI platforms for work involving non-public research data.
UT Austin CTL teaching-policy guidance says using generative AI tools to create course-assignment responses in a way the instructor does not accept may be considered academic dishonesty by the university.
UT Austin classroom guidance recommends that instructors requiring generative AI understand and abide by UT acceptable-use guidance, identify syllabus policies clearly, and submit specific software requirements through the University Co-Op.
UT Austin graduate-education recommendations say students should remain accountable as the sole intellectual author of milestone work and should never cite AI as an author.
6 source attributions
official_guidance Tracker checked at May 13, 2026, 1:54 AM
official_guidance Tracker checked at May 13, 2026, 1:54 AM
official_guidance Tracker checked at May 13, 2026, 1:54 AM
official_guidance Tracker checked at May 13, 2026, 1:54 AM
official_guidance Tracker checked at May 13, 2026, 1:54 AM
official_guidance Tracker checked at May 13, 2026, 1:54 AM