Policy presence
University of Texas at Austin has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
Austin, United States
University of Texas at Austin
Record status
Review: Agent reviewed
Policy profile
Review: Machine candidate
AI disclosure
University of Texas at Austin has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
University of Texas at Austin has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
University of Texas at Austin has 4 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
University of Texas at Austin has 4 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
University of Texas at Austin has 4 source-backed public claims for academic integrity; deterministic analysis status: restricted.
Approved tools
University of Texas at Austin has 3 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
University of Texas at Austin has 4 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
University of Texas at Austin has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Texas at Austin has 4 source-backed public claims for research guidance; deterministic analysis status: restricted.
Security and procurement
University of Texas at Austin has 2 source-backed public claims for security and procurement; deterministic analysis status: restricted.
AI tools
No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.
Evidence-backed claims
11 reviewed evidence-backed public claim
Privacy
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.
Review: Agent reviewed
Normalized value: Published data allowed; controlled/confidential data limited to contracted university-managed AI tools with protections and disabled web search.
Original evidence
Evidence 1Public or Published Data: Data that is publicly available or classified as Published university information ... may be used freely with AI tools. Controlled or Confidential Data ... can be used with AI tools that are managed by the university and covered by contracts explicitly protecting university data ... and web search functionality must be disabled.
Privacy
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.
Review: Agent reviewed
Normalized value: Unauthorized AI tools not approved for controlled/confidential university information.
Original evidence
Evidence 1AI tools that lack a university contract and appropriate data-sharing controls are not approved for use with Controlled or Confidential university information. This includes free or non-UT-managed versions of AI tools like ChatGPT and Copilot.
Procurement
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.
Review: Agent reviewed
Normalized value: AI detection software for student-work evaluation requires university contract or purchase order.
Original evidence
Evidence 1The University prohibits the use of all third-party software, including AI Detection Software ... to evaluate student work or assignments unless a University contract or purchase order is in place.
Security Review
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.
Review: Agent reviewed
Normalized value: CISO review required for consequential-decision AI uses.
Original evidence
Evidence 1UT Austin’s CISO must review AI tools to be used for any of these purposes prior to their procurement, development, deployment, or use.
Teaching
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.
Review: Agent reviewed
Normalized value: Responsible AI in teaching and learning is tied to learning outcomes and human development.
Original evidence
Evidence 1At UT Austin, we define responsible use of AI in teaching and learning as the adoption of AI that facilitates the achievement of learning outcomes and fosters human development for all members of the campus community.
Privacy
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.
Review: Agent reviewed
Normalized value: AI detection uploads without university contract may implicate student IP/copyright/FERPA rights.
Original evidence
Evidence 1Submitting student work (even if it is anonymized) into any AI Detection Software (or any other third-party software) without a University contract or purchase order in place may be a violation of that student’s copyright and intellectual property rights.
Academic Integrity
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.
Review: Agent reviewed
Normalized value: Academic integrity is an explicit responsible-adoption principle.
Original evidence
Evidence 1Academic Integrity: Use AI in alignment with our honor code and fundamental scholarly values such honesty, respect and authenticity, taking ownership and claiming authorship of the output of tools when appropriate.
Research
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.
Review: Agent reviewed
Normalized value: Graduate AI recommendations restrict non-public research data to vetted university-contracted platforms.
Original evidence
Evidence 1Graduate students and their mentors must only use vetted, University-contracted generative AI platforms for work involving non-public research data.
Academic Integrity
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.
Review: Agent reviewed
Normalized value: Unacceptable instructor-disallowed AI-generated assignment responses may be academic dishonesty.
Original evidence
Evidence 1The use of generative AI tools to create responses to course assignments in a way that is unacceptable to the course instructor may be considered a case of academic dishonesty by the university.
Teaching
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.
Review: Agent reviewed
Normalized value: Classroom-required AI use guidance addresses acceptable use, syllabus notice, and course-material reporting.
Original evidence
Evidence 1Ensure that your syllabus clearly identifies Syllabus Policy statements regarding the use of generative AI in your class. If you plan to encourage or require the use of generative AI in your class, ensure that requirement is clearly listed in the Required Course Materials section of your syllabus.
Research
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.
Review: Agent reviewed
Normalized value: Graduate milestone recommendations keep student authorship/accountability central and reject AI authorship.
Original evidence
Evidence 1Students should remain accountable as the sole intellectual author of milestone work and should never cite AI as an author.
Candidate claims
0 machine or needs-review claim
Official sources
6 source attribution
Acceptable Use of Generative AI Tools | UT Austin Information Security Office
security.utexas.edu
AI Detection Software Guidance - Office of the Executive Vice President and Provost
provost.utexas.edu
AI Use in Graduate Education - Office of the Executive Vice President and Provost
provost.utexas.edu
Generative AI in Teaching and Learning: Policies | Faculty Instructional Support and Development
ctl.utexas.edu
Requiring Generative AI in the Classroom - Office of the Executive Vice President and Provost
provost.utexas.edu
Responsible Adoption of AI Tools for Teaching and Learning - Office of the Executive Vice President and Provost
provost.utexas.edu