Change log

University of Maryland, College Park

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.

Change summary

Current public record freshness and review state.

University of Maryland, College Park currently has 11 source-backed claim records and 5 official source attributions. Latest tracked changed date: May 15, 2026. No tracker diff rows are recorded in the latest public release.

This page combines all public release diffs for University of Maryland, College Park. 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.

Diff categories

Semantic classification for this release diff.

Policy text0Newly extracted0Evidence0Source snapshots0Source text0Source added0Source removed0

Combined release diff

Unified tracker diff generated from all public release snapshots for this university.

University of Maryland, College Park combined release diff

Initial tracked release. Lines represent public claim/evidence records entering the release snapshot.

+20-0
11 # University of Maryland, College Park AI policy record
2+ai_tool_treatment: UMD publishes GenAI guidelines that apply to faculty, staff, students, and affiliates using GenAI tools in academic, research, or administrative activities.
3+Evidence (en, b32fc71f9563): These guidelines apply to all UMD faculty, staff, students, and affiliates using GenAI tools and technologies in academic, research, or administrative activities.
4+academic_integrity: For coursework, UMD tells students to assume GenAI use for assignments and assessments is not allowed unless the syllabus or assignment instructions specify otherwise.
5+Evidence (en, b32fc71f9563): Students should assume that the use of GenAI tools to complete course assignments and assessments is not allowed unless otherwise specified in the course syllabus or assignment/assessment instructions.
6+research: UMD guidance tells researchers not to input federal, state, or UMD data into externally sourced GenAI tools and not to upload unpublished research data or other confidential information into tools that have not undergone proper review.
7+Evidence (en, b32fc71f9563): Researchers should not input federal, state, or UMD data into externally sourced GenAI tools due to the high risk of exposing sensitive information to public or open-source domains.
8+privacy: For administrative work, UMD guidance says administrative staff should not input non-public institutional data into externally sourced GenAI platforms and faculty or staff should not put moderate-risk Level 2 or higher data into public external GenAI platforms.
9+Evidence (en, b32fc71f9563): Administrative staff should not input any institutional data that is not publicly available into externally sourced platforms (free or paid) using GenAI tools.
10+teaching: UMD strongly encourages instructors to establish course-specific policies defining appropriate and inappropriate GenAI use.
11+Evidence (en, b32fc71f9563): Instructors are strongly encouraged to establish a course-specific policy that defines the appropriate and inappropriate use of GenAI tools.
12+academic_integrity: UMD's Division of Academic Affairs advises against incorporating GenAI detection tools into course policies and says detection results should be treated only as potential indicators, not definitive proof or the sole basis for grading decisions.
13+Evidence (en, b32fc71f9563): The Division of Academic Affairs advises against incorporating GenAI detection tools into course policies. Results from GenAI detection tools should be treated only as potential indicators of misconduct, not definitive proof.
14+procurement: UMD guidance says individuals intending to use UMD credentials to access or purchase products with GenAI functionality should contact the Division of IT before signing up, including for free or open-source products.
15+Evidence (en, b32fc71f9563): Individuals intending to use UMD credentials to access or purchase products or tools with GenAI functionality should contact the Division of IT at itsupport@umd.edu before signing up.
16+security_review: UMD's AI services page lists DIT AI services and states that listed DIT tools have gone through SRM review and are approved for university community members to use.
17+Evidence (en, b0ccb1028a77): All software that will be used with university data or for educational activities must go through the university's Software Risk Management (SRM) review process.
18+security_review: UMD's AI software page identifies a list of software with AI capabilities approved by DIT Security and Compliance.
19+Evidence (en, 535d56159ee0): The following is a list of software with AI capabilities approved by DIT Security and Compliance. For a complete list of software approved for use, visit the Software Catalog.
20+teaching: UMD's TLTC guidance encourages instructors to communicate expectations for AI-based tools and to assess privacy/security risks, including using UMD-approved tools when possible.
21+Evidence (en, 2518aa5abda8): Speak openly and frequently with your students about your expectations for technology use - specifically, for AI-based tools.

Release history

0 public release diffs

Claim changes

11 claim records

ai_tool_treatment

UMD publishes GenAI guidelines that apply to faculty, staff, students, and affiliates using GenAI tools in academic, research, or administrative activities.

Review: Agent reviewedConfidence94%Evidence1Languagesen

academic_integrity

For coursework, UMD tells students to assume GenAI use for assignments and assessments is not allowed unless the syllabus or assignment instructions specify otherwise.

Review: Agent reviewedConfidence93%Evidence1Languagesen

research

UMD guidance tells researchers not to input federal, state, or UMD data into externally sourced GenAI tools and not to upload unpublished research data or other confidential information into tools that have not undergone proper review.

Review: Agent reviewedConfidence93%Evidence1Languagesen

privacy

For administrative work, UMD guidance says administrative staff should not input non-public institutional data into externally sourced GenAI platforms and faculty or staff should not put moderate-risk Level 2 or higher data into public external GenAI platforms.

Review: Agent reviewedConfidence93%Evidence1Languagesen

teaching

UMD strongly encourages instructors to establish course-specific policies defining appropriate and inappropriate GenAI use.

Review: Agent reviewedConfidence92%Evidence1Languagesen

academic_integrity

UMD's Division of Academic Affairs advises against incorporating GenAI detection tools into course policies and says detection results should be treated only as potential indicators, not definitive proof or the sole basis for grading decisions.

Review: Agent reviewedConfidence92%Evidence1Languagesen

procurement

UMD guidance says individuals intending to use UMD credentials to access or purchase products with GenAI functionality should contact the Division of IT before signing up, including for free or open-source products.

Review: Agent reviewedConfidence91%Evidence1Languagesen

security_review

UMD's AI services page lists DIT AI services and states that listed DIT tools have gone through SRM review and are approved for university community members to use.

Review: Agent reviewedConfidence90%Evidence1Languagesen

security_review

UMD's AI software page identifies a list of software with AI capabilities approved by DIT Security and Compliance.

Review: Agent reviewedConfidence90%Evidence1Languagesen

teaching

UMD's TLTC guidance encourages instructors to communicate expectations for AI-based tools and to assess privacy/security risks, including using UMD-approved tools when possible.

Review: Agent reviewedConfidence88%Evidence1Languagesen

teaching

UMD's TLTC sample syllabus page gives instructors non-binding example AI course-policy language spanning prohibited, limited, and broad AI use, with citation or attribution expectations where applicable.

Review: Agent reviewedConfidence88%Evidence1Languagesen

Source snapshots

5 source attributions

Available Services

official_guidance Tracker checked at May 15, 2026, 1:08 PM

Snapshot hash
b0ccb1028a770d6b0653382cc40af9f90216bc58fdd914b9fa4c1585877995c7

Software

official_guidance Tracker checked at May 15, 2026, 1:08 PM

Snapshot hash
535d56159ee0de4186808478de964be4bd1987207a94a210f770302978b6f9b7