Ethical and Behavioral Considerations in AI Adoption
Michael Baker - Plante Moran
Scott Petree - Plante Moran
Eric Miller - Penn State
This session explores the ethical, governance, and risk implications of artificial intelligence adoption in higher education, focusing on area’s University leaders will face in the race to AI adoption. Topics include discussions on fairness, transparency, data privacy, and academic integrity. Participants gain practical insight into how institutions can establish responsible AI governance frameworks that align innovation with regulatory, ethical, and professional standards.
Learning Objectives
- Evaluate ethical risks and professional responsibilities associated with AI use in higher education
Participants will be able to identify and assess ethical risks arising from the use of artificial intelligence in admissions, grading, advising, research, and administrative decision making like hiring, with emphasis on understanding biases and maintaining objectivity.
- Apply governance and accountability principles to ensure responsible and compliant AI adoption
Participants will learn how effective AI governance frameworks— including clear policies, defined roles, oversight mechanisms, and multidisciplinary accountability—support ethical decision making, mitigate bias, and reduce legal, reputational, and compliance risks.
- Recognize data privacy, confidentiality, and intellectual property obligations related to AI technologies
Participants will be able to explain key privacy, data protection, and intellectual property considerations associated with AI tools, including third party vendor risks, data minimization, confidentiality obligations, and emerging regulatory expectations.
CPE Available
- 1.5 Credits: Regulatory Ethics
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