Policy presence
University of Maryland, Baltimore has 2 source-backed public claims for policy presence; deterministic analysis status: unclear.
Baltimore, United States
University of Maryland, Baltimore
University of Maryland, Baltimore has 6 source-backed AI policy claims from 4 official source attributions. Review state: agent reviewed; 6 reviewed claims. Last checked May 20, 2026.
University of Maryland, Baltimore AI policy short answer
v1 public contract
University of Maryland, Baltimore has 6 source-backed AI policy claims from 4 official source attributions, including 6 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 20, 2026. Discovery context: University of Maryland, Baltimore is listed as QS 2026 rank 801-850.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of Maryland, Baltimore as an agent-reviewed AI policy record last checked on May 20, 2026 and last changed on May 20, 2026. The record contains 6 source-backed claims, including 6 reviewed claims, from 4 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-maryland-baltimore.json. The entity-level confidence is 96%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Other policy claims.
- Evidence includes Privacy claims.
- Evidence includes Procurement claims.
- Evidence includes Security review claims.
- Evidence includes Academic integrity claims.
- Evidence includes AI tool treatment claims.
- No specific AI service name is highlighted by the current public claim text.
- Privacy, sensitive-data, or security language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page 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.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
No source-backed public claim about AI disclosure or acknowledgement is present in this profile.
The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.
Coursework
University of Maryland, Baltimore has 3 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
University of Maryland, Baltimore has 2 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
University of Maryland, Baltimore has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
University of Maryland, Baltimore has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
Approved tools
University of Maryland, Baltimore has 4 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
University of Maryland, Baltimore has 3 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
University of Maryland, Baltimore has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Maryland, Baltimore has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
Security and procurement
University of Maryland, Baltimore has 3 source-backed public claims for security and procurement; deterministic analysis status: restricted.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
6 reviewed evidence-backed public claim
Other
UMB's AI Governance Policy applies to UMB faculty, staff, students, and affiliates who develop, use, or are impacted by AI technologies in research, teaching, operations, and service.
Review: Agent reviewed
Normalized value: university-wide AI governance scope
Original evidence
Evidence 1This policy applies to all UMB faculty, staff, students, and affiliates who develop, utilize, or are impacted by AI technologies in research, teaching, operations, and service.
Localized display only
This policy applies to all UMB faculty, staff, students, and affiliates who develop, use, or are impacted by AI technologies in research, teaching, operations, and service.
Privacy
UMB says Sensitive/Restricted Data, including PII and PHI, should not be uploaded into public AI systems, and confidential or sensitive UMB data should only be uploaded into approved secure UMB-sponsored AI systems.
Review: Agent reviewed
Normalized value: no sensitive or restricted data in public AI systems
Original evidence
Evidence 1Important: Never upload Sensitive/Restricted Data, which includes Personally Identifiable Information (PII) and Protected Health Information (PHI), into public AI systems. UMB confidential and sensitive data should only be uploaded into approved secure UMB sponsored AI systems.
Localized display only
UMB says never to upload Sensitive/Restricted Data, including PII and PHI, into public AI systems.
Procurement
UMB requires Strategic Sourcing and Acquisition Services and CITS approval for acquisition of new AI technology tools, including free tools.
Review: Agent reviewed
Normalized value: AI tool acquisition requires SSAS and CITS approval
Original evidence
Evidence 1Acquisition of new AI technology requires Strategic Sourcing and Acquisition Services (SSAS) and Center for Information Technology Services (CITS) approval, for both procurement and free tools.
Localized display only
Acquisition of new AI technology requires SSAS and CITS approval, including both procurement and free tools.
Security Review
UMB states that AI tools must be reviewed and approved before use on university devices, networks, or with university data.
Review: Agent reviewed
Normalized value: AI tools require review before UMB device, network, or data use
Original evidence
Evidence 1AI tools must be reviewed and approved before use on university devices, networks, or with university data.
Localized display only
AI tools must be reviewed and approved before UMB device, network, or university-data use.
Academic Integrity
UMB guidance says GenAI tools should not be used to fabricate, falsify, misrepresent information, impersonate individuals, or generate deceptive content, except in controlled ethical pedagogical or research uses.
Review: Agent reviewed
Normalized value: GenAI misuse conflicts with academic integrity
Original evidence
Evidence 1GenAI tools should not be used to fabricate, falsify, or misrepresent information, impersonate individuals, or generate deceptive content except when intentionally employed by instructors or researchers for pedagogical or research purposes in a controlled and ethical manner.
Localized display only
GenAI tools should not be used to fabricate, falsify, misrepresent, impersonate, or generate deceptive content outside controlled ethical uses.
Ai Tool Treatment
UMB's AI Toolkit organizes AI tools by data classification level and identifies Level 2 enterprise AI tools as approved for highly sensitive and confidential data.
Review: Agent reviewed
Normalized value: AI tools organized by data classification
Original evidence
Evidence 1Tools are organized by data classification level to help you choose the appropriate tool for your needs. Level 2 - Confidential Enterprise-grade AI tools approved for highly sensitive and confidential data.
Localized display only
The toolkit organizes tools by data classification level and identifies Level 2 enterprise AI tools for highly sensitive and confidential data.
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
4 source attribution
AI Governance Policy
umaryland.edu
AI Toolkit - AI at UMB
umaryland.edu
Safe and Responsible Use - AI at UMB
umaryland.edu
University of Maryland, Baltimore Artificial Intelligence (AI) Guidelines
umaryland.edu
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.