| 1.0030R |
Disruptive Behavior |
- Misinformation: AI can create misinformation causing , disruption to university processes.
- Interference with Teaching: AI can generate fake scholarly content or tools that potentially undermine academics.
- Unauthorized Use of Property: AI can access or manipulate University systems without permission.
- Disruption of Functions: AI can automate actions that programmatically disrupt University functions,.
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| 1.0020P |
Ethical Conduct |
- Integrity of University Business: AI systems in grading or admissions shouldbe transparent and unbiased.
- Ethical Standards: AI use should align with university ethical standards, avoiding plagiarism and acknowledging AI contributions to maintain academic integrity.
- Non-Discrimination: AI systems should be free from bias and prevent discrimination based on race, sex, or disability.
- Confidentiality and Security: Maintain confidentiality and security of university information. By using university approved tools
- Proper Use of Resources:. AI systems must be financially transparent and prevent misuse.
- Public's Business and Transparency: AI use in decision-making or data analysis should be transparent and auditable to comply with public record laws.
- Reporting Misconduct: provide mechanisms for reporting and addressing AI-related ethical violations.
- Climate of Care and Civility: AI applications should support a climate of care and civility, avoiding biased or hostile environments.
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| 5.0010R |
Student Code of Conduct |
- Misuse of Technology AI should not be used to generate work for academic credit that is not the student's own.
- Unauthorized Collaboration: unauthorized assistance can include work generated by AI
- Plagiarism: Includes AI-generated content used without proper attribution.
- Misuse of Materials: includes AI-generated content as course materials or sharing instructor-created materials without permission.
- Student Rights: Address a student’s right to allow the presentation of evidence in AI misconduct cases, including their history with technology and AI tools.
- Sanctions: Apply existing sanctions, including forfeiture of academic credit, to cases of AI misconduct.
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| 2.0340P |
Appealing Academic Grades |
- Instructor's Authority: Specify the weight of AI-generated grades compared to an instructor’s judgment and clarify how instructors can contest or override AI decisions.
- Appeals Committee Process: Ensure the committee has expertise in evaluating AI grading methodologies
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| 2.0670P |
Undergraduate Certificate Programs |
- Curriculum Development: Update the curriculum to include AI-related courses or integrate AI concepts into existing courses, involving new course development and approval processes.
- Student Learning Outcomes: Define new learning outcomes related to AI competencies and evolve assessment methods to measure understanding and application of AI concepts.
- Eligibility and Prerequisites: Adjust eligibility criteria and prerequisites for AI courses to ensure students have the necessary background knowledge.
- Coursework and Residency Requirements: Consider distance learning opportunities for AI courses while maintaining the requirement for completing at least 50% of coursework in residence.
- "Good Standing": Apply the same academic requirements to students taking AI courses, ensuring their performance in AI-related courses does not jeopardize their standing.
- Certificate Conferral: Highlight AI-related certificate programs on transcripts, ensuring the Registrar accounts for this in printing and conferring completion documents.
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| 2.0720P |
Graduate Certificate Programs |
- Curriculum Design: Update the curriculum to include new AI courses and integrate AI concepts into existing courses.
- Course Prerequisites: Define new prerequisites for AI courses, ensuring students have the necessary background in programming, mathematics, or relevant fields.
- Transfer of Credits: Review policies for transferring credits, especially for AI courses from other institutions, and determine their applicability towards certificate requirements.
- Program Requirements: Revisit the requirement for completing at least 50% of coursework in residence, considering if online AI coursework should be included.
- New Certificate Programs: Develop new certificate programs in AI-related areas like Artificial Intelligence, Machine Learning, or Data Science.
- Academic Standards: Apply the same academic standards to students in AI-related coursework as those for degree-seeking students.
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| 2.0020P |
Patents, Copyrights and Other Intellectual Property |
- Clarity: Explicitly include AI-related terms in definitions of "Invention" and "Work" for greater clarity, with examples like AI algorithms, models, and data sets.
- Specific Challenges: Address unique AI intellectual property challenges, such as:
- Ownership of data sets used to train AI models.
- Ownership of AI-generated content.
- Role of open-source AI tools and libraries in determining ownership.
- Ethical implications of AI development and deployment.
- Faculty Concerns: Consider changes related to AI in the context of existing collective bargaining agreements with faculty.
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