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 has 2 source-backed public claims for policy presence; deterministic analysis status: unclear.
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.
University of Maryland, Baltimore has 3 source-backed public claims for coursework; deterministic analysis status: restricted.
University of Maryland, Baltimore has 2 source-backed public claims for exams; deterministic analysis status: restricted.
University of Maryland, Baltimore has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
University of Maryland, Baltimore has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
University of Maryland, Baltimore has 4 source-backed public claims for approved tools; deterministic analysis status: restricted.
University of Maryland, Baltimore has 3 source-backed public claims for named ai services; deterministic analysis status: restricted.
University of Maryland, Baltimore has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.
University of Maryland, Baltimore has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
University of Maryland, Baltimore has 3 source-backed public claims for security and procurement; deterministic analysis status: restricted.
6 reviewed evidence-backed public claim
Other
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
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
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
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
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
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.
0 machine or needs-review claim
4 source attribution
umaryland.edu
umaryland.edu
umaryland.edu
umaryland.edu