ai_tool_treatment
UMD publishes GenAI guidelines that apply to faculty, staff, students, and affiliates using GenAI tools in academic, research, or administrative activities.
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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.
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11 claim records
UMD publishes GenAI guidelines that apply to faculty, staff, students, and affiliates using GenAI tools in academic, research, or administrative activities.
For coursework, UMD tells students to assume GenAI use for assignments and assessments is not allowed unless the syllabus or assignment instructions specify otherwise.
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tells researchers not to input federal, state, or UMD data into externally sourced GenAI tools and not to upload unpublished research data or other confidential information into tools that have not undergone proper review.
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.
UMD strongly encourages instructors to establish course-specific policies defining appropriate and inappropriate GenAI use.
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.
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.
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.
UMD's AI software page identifies a list of software with AI capabilities approved by DIT Security and Compliance.
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.
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.
5 source attributions
official_guidance Tracker checked at May 15, 2026, 1:08 PM
official_guidance Tracker checked at May 15, 2026, 1:08 PM
official_policy_page Tracker checked at May 15, 2026, 1:05 PM
official_guidance Tracker checked at May 15, 2026, 1:08 PM
official_guidance Tracker checked at May 15, 2026, 1:08 PM