Policy and Guidance

CMU’s use of AI is grounded in institutional policies and the recommendations of the cross-divisional workgroups of the Embracing AI at CMU Go Grant. Draft policy principles emphasize academic integrity, data privacy and security, compliance with applicable laws, role specific guidance, and university community education. 

Core principles

• Student-centered learning and career readiness: AI should enhance learning and prepare graduates for an AI-rich workplace. 
• Equity and accountability: Provide equitable access to AI education and tools, with clear expectations for use. 
• Privacy and data security: Institutional data stewardship and regulatory compliance are nonnegotiable. 
• Transparency and academic integrity: Be explicit about when and how AI is used; model proper attribution. 
• Sustainability and assessment: Support with governance, staffing, and evaluation to ensure continuous improvement. 

Campus expectations

• Use institutionally approved tools when working with university data; consumer tools are typically for public data only unless covered by an enterprise agreement.  
• Do not input regulated data (e.g., HIPAA, CUI, PCI) into generative AI tools unless the tool is explicitly approved for that classification.  
• Follow all applicable laws/policies (e.g., accessibility, copyright, research integrity, data security) and consult the appropriate office when in doubt. 
• Provide clear guidance on acceptable use including syllabus statements and assignment directions.  Visit the Office of Curriculum and Instructional Support website for more information.