Hallucinations and Bias in Generative AI (Faculty and Staff)

11 m

This course provides faculty and staff with essential knowledge to identify and mitigate two critical risks in generative AI systems: hallucinations and bias. As AI tools become standard in academic and administrative workflows, users must understand how these systems can produce incorrect information and perpetuate unfair patterns that undermine institutional credibility and student trust. Participants will learn to recognize AI hallucinations—confident-sounding but factually incorrect outputs—and bias that reinforces problematic assumptions about individuals and groups. The course covers practical warning signs, from fabricated citations to stereotypical recommendations, and provides concrete strategies for safe, responsible AI use in educational settings.

Hallucinations and Bias in Generative AI (Faculty and Staff)

Author Details

Author | Aaron Burgess

Dr. Aaron Burgess is an Assistant Professor of Management, CAPS Business and Technology Program Director at Mount Vernon University. He has previously served as a professor at Thomas Moore University, Mount St. Joseph University, and Cincinnati Christian University. In addition to his academic career, he serves as a Performance Management, Learning and Information Technology Consultant for organizations like Mayo Clinic, Salesforce, University of Pittsburg, Katz Business School, Cincinnati Children's Hospital, Drees Homes, Fischer Homes, and many others.

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