Policy presence
University of Michigan-Ann Arbor has 2 source-backed public claims for policy presence; deterministic analysis status: unclear.
Ann Arbor, United States
University of Michigan-Ann Arbor has 2 source-backed public claims for policy presence; deterministic analysis status: unclear.
University of Michigan-Ann Arbor has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.
University of Michigan-Ann Arbor has 4 source-backed public claims for coursework; deterministic analysis status: restricted.
University of Michigan-Ann Arbor has 4 source-backed public claims for exams; deterministic analysis status: restricted.
University of Michigan-Ann Arbor has 3 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
University of Michigan-Ann Arbor has 2 source-backed public claims for academic integrity; deterministic analysis status: required.
University of Michigan-Ann Arbor has 3 source-backed public claims for approved tools; deterministic analysis status: restricted.
University of Michigan-Ann Arbor has 4 source-backed public claims for named ai services; deterministic analysis status: restricted.
University of Michigan-Ann Arbor has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
University of Michigan-Ann Arbor has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.
University of Michigan-Ann Arbor has 1 source-backed public claim for security and procurement; deterministic analysis status: restricted.
No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.
8 reviewed evidence-backed public claim
Ai Tool Treatment
Normalized value: university_provides_custom_ai_tools
Original evidence
Evidence 1ITS is now offering a generative AI platform available to all active U-M faculty, staff, and students on the Ann Arbor, Flint, and Dearborn campuses and Michigan Medicine. These service offerings are equitable, accessible, and support everything from basic consumer usage to advanced research and experimentation.
Academic Integrity
Normalized value: ai_detection_not_recommended
Original evidence
Evidence 1U-M does not recommend the use of AI-detection technology at this time given their high error rate. False positives and negatives are possible, and even likely.
Privacy
Normalized value: data_classification_ai_rules
Original evidence
Evidence 1When working with university data in AI platforms: Use approved ITS AI Services. Only use university data classified as Low with AI services that do not have a contract or data agreement with U-M.
Security Review
Normalized value: ai_generated_code_must_be_human_reviewed
Original evidence
Evidence 1Ensure AI-generated computer code is always reviewed by a human. Conduct code reviews with professionally trained peers for all new or significantly changed applications, particularly those that maintain, process, transmit, or store data classified as Restricted or High.
Privacy
Normalized value: ai_services_include_hipaa_safeguards
Original evidence
Evidence 1ITS AI Services include the safeguards required by HIPAA. Accordingly, you may use these services with Protected Health Information (PHI).
Academic Integrity
Normalized value: ai_use_must_align_with_scholarship_integrity
Original evidence
Evidence 1When using AI services for teaching, learning and knowledge production, U-M community members must: Align with the university's principles for honesty, candor, openness, and integrity in scholarship and research, including appropriate disclosure and citation where AI has been used.
Teaching
Normalized value: instructor_discretion_on_ai_use
Original evidence
Evidence 1Instructors are disciplinary experts responsible for what is taught, appropriate pedagogies, and assessment methodologies. GenAI may influence all three, and as such, instructors need flexibility to allow or disallow the use of GenAI tools.
Privacy
Normalized value: students_warned_about_ai_privacy_risks
Original evidence
Evidence 1Understand that in most cases, the data you share is not private and will be accessible by external parties hosting the GenAI-based tools. Do not share information that is considered private, or sensitive, such as credit card information, personal details such as ID numbers or addresses, and so on.
0 machine or needs-review claim
8 source attribution
crlt.umich.edu
genai.umich.edu
genai.umich.edu
genai.umich.edu
academictechnology.umich.edu
its.umich.edu
genai.umich.edu
genai.umich.edu