UMES Artificial Intelligence Policy

I. Purpose

The University of Maryland Eastern Shore (UMES) is committed to fostering innovation and responsible use of technology, including Generative Artificial Intelligence (AI). This policy establishes a mandatory framework to guide the ethical, secure, and effective use of AI tools among administration, faculty, staff, and students. As AI evolves, this policy will be reviewed annually to ensure alignment with best practices, State of Maryland legal standards, and the needs of the UMES community.

II. Scope

This policy applies to all members of the UMES community—students, faculty, staff, and researchers—who use AI tools in their academic, administrative, and professional activities.

III. General Principles and Foundational Guidelines

1. Data Security, Privacy, and Confidentiality

Prohibition on Sensitive Data: Absolutely do not input confidential, personally identifiable, or sensitive university-related data (including student records protected by FERPA, proprietary research data, or non-public administrative information) into public, unapproved AI systems.
Approved Tools: Only use AI tools that have been officially reviewed and approved by UMES Information Technology (IT) for handling university business or Level 2 and above confidential data. Faculty, staff, and researchers must refer to current IT policy before deploying AI tools connected to the Learning Management System (LMS) or handling sensitive institutional data.
Legal Compliance: All use of AI must comply with federal regulations (including FERPA and HIPAA) and all applicable State of Maryland laws and regulations, particularly regarding automated decision-making and consumer data protection.

2. Academic and Research Integrity

Human Responsibility: The user of the AI tool—whether student, faculty, or researcher—is ultimately and personally responsible for the accuracy, validity, originality, and ethical implications of any output generated or assisted by AI.
Mandatory Disclosure: All AI use in academic or research work must be disclosed and appropriately cited. Failure to properly disclose the use of AI tools is a violation of academic integrity and will be treated as plagiarism.

3. Ethical and Bias Awareness

Bias Mitigation: Users must be aware that AI systems can reflect and perpetuate biases present in their training data. Users must critically evaluate AI outputs for fairness, equity, and accuracy before use or dissemination.
Fair Use and Copyright: Users are responsible for ensuring that the use of AI tools and their outputs comply with intellectual property and copyright laws.

IV. Application Guidelines for Students and Faculty

Course Syllabi AI Policy (Traffic Light Model)

Faculty are required to adopt a clear, three-tiered “Traffic Light” model for AI use in their courses and must articulate this policy explicitly in their syllabus.

Tier	Policy Name	Permitted Use & Rationale	Mandatory Requirement
🟢 Green Light	Full Use Allowed	AI tools may be used freely as per assignment instructions. Rationale: The goal is to learn how to effectively use AI tools as a professional skill.	Mandatory Disclosure and Citation Required.
🟡 Yellow Light	Limited, Specified Use	AI tools may be used only for specific tasks (e.g., brainstorming, checking grammar, generating code snippets). Use for core assessment tasks is prohibited. Rationale: The goal is to develop specific skills while allowing AI support.	Mandatory Disclosure and Citation Required detailing how the AI was used.
🔴 Red Light	No Use Allowed	AI tools are prohibited entirely for coursework and assessments. Rationale: The goal is to develop foundational skills, original critical thought, or manual expertise.	Any use is a violation of Academic Integrity.

Academic Integrity Violations: Any violation of an instructor’s specific AI policy will be referred to the UMES Academic Integrity Committee for appropriate action, per the existing Student Code of Conduct.

V. Strategic AI Literacy and Workforce Development

UMES recognizes its role in preparing the Maryland workforce for an AI-infused world, as highlighted by State legislative goals.

AI Literacy Mandate: UMES will prioritize providing structured training for all community members (Faculty, Staff, and Students) on:
- The capabilities and limitations of Generative AI.
- Ethical prompt engineering and critical evaluation of AI output.
- Best practices for data privacy and security (FERPA compliance).
Curriculum Integration: Faculty are strongly encouraged to integrate AI literacy, critical evaluation, and responsible AI usage into their departmental curricula, moving toward authentic assessments that prioritize human reasoning over simple content generation.

VI. Review and Contact

Policy Review: This policy will be reviewed and updated annually by the UMES AI Guidance/Policy Committee.

Contact Information: For questions about this policy or to report potential compliance issues, please contact the UMES AI Committee or the Office of Information Technology (IT).