Ann Arbor, United States

University of Michigan-Ann Arbor

University of Michigan-Ann Arbor is listed as QS 2026 rank 45. University of Michigan-Ann Arbor has 8 source-backed AI policy claim records from 8 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Last checkedMay 10, 2026Last changedMay 10, 2026Review: Agent reviewedConfidence98%

Public JSON Citation rules Dataset access

Reviewed claims8Candidate claims0Official sources8

Candidate claims are source-backed records pending review. They are not final policy conclusions and are not legal or academic integrity advice.

Reviewed claims

8 reviewed public claim

Normalized value: university_provides_custom_ai_tools

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

ITS 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.
Source: ITS AI Services

Source language: English (en)
Snapshot hash: 893178af5c9197012d66bce9c04db17b5899909a4f7697c8dfc2f09f443682d2
Retrieved: May 10, 2026
Evidence locator: Main content

Normalized value: ai_detection_not_recommended

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

U-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.
Source: U-M Guidance for Faculty/Instructors

Source language: English (en)
Snapshot hash: b8f0b533c74eb26ea17164cffc32d96be3d9be527d1474437c7870a9fcc1ff2c
Retrieved: May 10, 2026
Evidence locator: Academic/Teaching Implications section

Normalized value: data_classification_ai_rules

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

When 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.
Source: Appropriate Use of AI Services & U-M Policy

Source language: English (en)
Snapshot hash: 86f1343685c0921363964358bf5657ea67102a6f77d3bce42e169b10e02602ae
Retrieved: May 10, 2026
Evidence locator: When Handling University Data section

Normalized value: ai_generated_code_must_be_human_reviewed

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

Ensure 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.
Source: Appropriate Use of AI Services & U-M Policy

Source language: English (en)
Snapshot hash: 86f1343685c0921363964358bf5657ea67102a6f77d3bce42e169b10e02602ae
Retrieved: May 10, 2026
Evidence locator: To Generate Computer Code section

Normalized value: ai_services_include_hipaa_safeguards

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

ITS AI Services include the safeguards required by HIPAA. Accordingly, you may use these services with Protected Health Information (PHI).
Source: ITS AI Services

Source language: English (en)
Snapshot hash: 893178af5c9197012d66bce9c04db17b5899909a4f7697c8dfc2f09f443682d2
Retrieved: May 10, 2026
Evidence locator: Sensitive Data with U-M AI Service Offerings section

Normalized value: ai_use_must_align_with_scholarship_integrity

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

When 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.
Source: Appropriate Use of AI Services & U-M Policy

Source language: English (en)
Snapshot hash: 86f1343685c0921363964358bf5657ea67102a6f77d3bce42e169b10e02602ae
Retrieved: May 10, 2026
Evidence locator: For Teaching, Learning, and Knowledge Production section

Normalized value: instructor_discretion_on_ai_use

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

Instructors 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.
Source: Course Policies & Syllabi Statements

Source language: English (en)
Snapshot hash: a34dec58d56d995ca91c9ed899847169d777362e3aa0bf7d30372d539d318ea0
Retrieved: May 10, 2026
Evidence locator: Syllabus Language section

Normalized value: students_warned_about_ai_privacy_risks

Last checked: May 10, 2026
Last changed: May 10, 2026

Original evidence

Evidence 1

Understand 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.
Source: U-M Guidance for Students

Source language: English (en)
Snapshot hash: 3a9af93df94bab28629148d05410b149c5347fa6c66a74770dfadf61e7a0a598
Retrieved: May 10, 2026
Evidence locator: Choosing a GenAI tool to use - Privacy risks

Candidate claims

0 machine or needs-review claim

Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.

Official sources

8 source attribution

Academic Integrity, GenAI - CRLT

crlt.umich.edu

Source URL: https://crlt.umich.edu/academic-integrity-genai
Snapshot hash: 711b5d19a260fb95589720bf32238469e9b61074593ace8413addd5aee476a0e

Appropriate Use of AI Services & U-M Policy

genai.umich.edu

Source URL: https://genai.umich.edu/resources/appropriate-use
Snapshot hash: 86f1343685c0921363964358bf5657ea67102a6f77d3bce42e169b10e02602ae

Course and Assignment (Re-)Design

genai.umich.edu

Source URL: https://genai.umich.edu/resources/faculty/redesigning-assessments
Snapshot hash: 3310af878dd2ad2a792459f8cc0db82cac6c704201cdbdfd3f7a1ab8028caee1

Course Policies & Syllabi Statements

genai.umich.edu

Source URL: https://genai.umich.edu/resources/faculty/course-policies
Snapshot hash: a34dec58d56d995ca91c9ed899847169d777362e3aa0bf7d30372d539d318ea0

Generative AI Academic Integrity Resources

academictechnology.umich.edu

Source URL: https://academictechnology.umich.edu/instructional-resources/generative-ai/academic-integrity-resources
Snapshot hash: 204c235ee73270a75e64f261e93527f3e11164837289e3dfd6d100929f8a1f37

ITS AI Services

its.umich.edu

Source URL: https://its.umich.edu/computing/ai
Snapshot hash: 893178af5c9197012d66bce9c04db17b5899909a4f7697c8dfc2f09f443682d2

U-M Guidance for Faculty/Instructors

genai.umich.edu

Source URL: https://genai.umich.edu/resources/faculty
Snapshot hash: b8f0b533c74eb26ea17164cffc32d96be3d9be527d1474437c7870a9fcc1ff2c

U-M Guidance for Students

genai.umich.edu

Source URL: https://genai.umich.edu/resources/students
Snapshot hash: 3a9af93df94bab28629148d05410b149c5347fa6c66a74770dfadf61e7a0a598

Back to universities

University AI Policy Tracker. "University of Michigan-Ann Arbor AI Policy Tracker record." Last checked May 10, 2026. https://eduaipolicy.org/universities/university-of-michigan-ann-arbor

Versioned university record with claims, evidence, source attribution, review state, confidence, and citation fields.

8 source attribution record.

Tracker metadata is open licensed. Official source documents, page text, PDFs, and other source materials retain their original rights and terms.

Tracker metadata: CC-BY-4.0

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.

Human reviewed
Agent reviewed
Machine candidate
Needs review
Rejected

Review state describes workflow status. Confidence is a separate machine-assessed support score.

University of Michigan-Ann Arbor

Citation-ready overview

Reviewed claims

U-M ITS offers 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, with service offerings described as equitable and accessible.

U-M does not recommend the use of AI-detection technology given their high error rate. False positives and negatives are possible, and even likely.

U-M requires using approved ITS AI Services for university data. Only data classified as Low may be used with AI services lacking a U-M contract or data agreement.

U-M requires that AI-generated computer code is always reviewed by a human, with professionally trained peer code reviews for applications handling Restricted or High data.

U-M ITS AI Services include HIPAA safeguards and may be used with Protected Health Information (PHI).

U-M requires AI use in teaching and learning to align with principles of honesty, candor, openness, and integrity in scholarship and research, including appropriate disclosure and citation.

U-M leaves GenAI policy to individual instructors, who may allow, restrict, or forbid AI use in their courses. Course policies should be clearly articulated in syllabi.

U-M advises students that data shared with external AI tools is not private and may be accessible by external parties. Students should not share private or sensitive information.

Candidate claims

Official sources

Academic Integrity, GenAI - CRLT

Appropriate Use of AI Services & U-M Policy

Course and Assignment (Re-)Design

Course Policies & Syllabi Statements

Generative AI Academic Integrity Resources

ITS AI Services

U-M Guidance for Faculty/Instructors

U-M Guidance for Students