Generative Artificial Intelligence Guidance

In the rapidly evolving landscape of Generative AI (GenAI) within higher education, Michigan State University emphasizes the importance of ethical foundations. MSU AI is the university’s hub for AI guidelines and resources to support the responsible and ethical use of generative AI in teaching, learning, research, administrative work, and more.

Values

• Collaboration: We prioritize reciprocity and ethics partnerships, aiming to drive interdisciplinary innovation that benefits both our community and society at large.
• Equity: We are committed to maximizing accessibility and equity, actively dismantling biases and barriers related to socioeconomic status, disabilities, and institutional boundaries to empower all members of our community.
• Excellence: We will ethically employ AI for institutional enhancement and societal betterment, supporting professional development and continuous policy refinement to elevate our standards in all facets of our work.
• Integrity: We commit to responsible AI use, adhering to all laws, acknowledging its limitations, ensuring privacy, security, and unbiased data handling, while rigorously reviewing outputs to maintain our standard of honesty and trustworthiness.
• Respect: We pledge to utilize AI in ways that honor human dignity and foster a culture of safety and understanding, valuing human insight above all while acknowledging and mitigating AI biases to ensure a respectful, secure community.

Themes

• Human agency and oversight: An AI system should be a source of a fair society by supporting human agency and fundamental rights, rather than reducing, limiting or undermining human independence.
• Diversity, non-discrimination and fairness: AI systems should consider all degrees of people's talents, skills, and needs, as well as guarantee user accessibility.
• Technical robustness and safety: Trustworthy AI requires algorithms that are sufficiently secure, reliable, and robust to deal with errors or inconsistencies in all phases of the AI system's work.
• Privacy and data governance: Citizens should have full control over their personal data. This data must not be used to harm or disadvantage them.
• Transparency: Emphasizes the AI system's traceability, explainability, and communication.
• Societal and environmental wellbeing: AI systems should be utilized to reinforce positive social change and increase sustainability and environmental responsibility.
• Accountability: Mechanisms should be put in place to ensure responsibility and accountability for AI systems and the results of their processes, including the opportunity to review and report negative consequences.