Guiding Principles
UNC Charlotte is committed to the ethical and responsible use of artificial intelligence (AI) to enhance academic, research and administrative endeavors. These guiding principles provide a flexible framework to guide individual, unit and university decision-making on the use and adoption of AI.
While these Guiding Principles apply University-wide, academic instructors, researchers and operational units retain the individual responsibility to establish localized policies and rules, such as prohibiting or mandating AI for specific learning objectives, research protocols or operational needs.
Accountability & Human Responsibility
Maintain clear lines of human accountability for the adoption, deployment and outputs of AI. Members of the University community should decide if, when and how AI tools are integrated into their work. Humans remain fully accountable for verifying AI outputs for accuracy, completeness and bias, and hold ultimate ownership over final products.
Continuous Learning
Provide continuous learning opportunities for students, faculty and staff about AI technologies, ethical considerations, and best practices.
Environmental Responsibility
Encourage the efficient, intentional, and sustainable use of AI, recognizing its high resource demands.
Inclusivity & Accessibility
Ensure AI is accessible to all members of the university community, regardless of background or ability. Identify and mitigate biases in AI systems to promote impartiality and fairness.
Intellectual Property & Content Ownership
Safeguard institutional data, research and creative works. AI tools must not be populated with proprietary, unpublished or protected institutional data unless vendor contracts guarantee data privacy and explicitly prevent public model training.
Privacy & Data Protection
Safeguard personal data and adhere to data protection regulations. Use University- approved AI tools that provide data protection. Adhere to the University data-handling guidelines.
Procurement
Third-party software containing AI components must undergo appropriate vetting prior to deployment to ensure compliance with University data security, privacy, accessibility and algorithmic bias standards.Performance
Research & Innovation
Foster a culture of AI research and innovation, including the range of societal impacts and ethical use. Embrace opportunities for operational efficiency.
Transparency
Ensure AI processes and decisions are transparent and understandable to all stakeholders.