This course introduces participants to some of the central ethical issues arising from existing and emerging artificial intelligence technologies. Participants will gain a non-technical understanding of machine learning models, enabling them to appreciate what makes these models so powerful and potentially useful but also why such models raise important ethical questions and concerns.

In addition to presenting general ethical challenges posed by AI, the course will focus on generative AI models specifically, addressing some of the distinctive ethical issues arising from large language models (LLMs) such as Chat GPT: truth and reliability, data harvesting and intellectual property, transparency and deception, outsourcing of human thinking and judgment, among other issues.

Through a discussion of timely case studies, participants will address how these ethical concerns regarding AI might affect professional engineers in the context of their work, with an eye towards establishing principles that can guide responsible use of AI in their professional lives.

Course Details

Date: April 24, 2024 or June 19, 2024
Time: 9–11 a.m. (online)
PDHs: 4.0 | CEUs: 0.4
Price: $185

Who Should Attend

 Professional engineers at any stage of their careers including:

• Entry Level Professionals
• Leaders
• Decision makers at the highest levels
• Individuals interested in learning about the topic

Benefits

• Gain a solid understanding of machine learning technologies, with a focus on generative AI models.
• Learn about ethical questions raised by machine learning and generative AI models and their deployment.
• Develop concrete guiding principles for addressing ethical challenges raised by AI in the context of work and professional life.

Outcomes

• Describe the basic components of modern AI technologies and how those components create unique applications and risks.
• Identify key ethical inquiries surrounding machine learning technologies, emphasizing the unique considerations of generative AI models.
• Assess the ethical complexities and potential pitfalls of AI technologies within the context of engineering or business environments.
• Articulate and apply ethical principles to proactively address ethical concerns and challenges in professional practice related to AI implementation.

About the Instructor

Andrew McAninch, Ph.D., is an Associate Professor of Philosophy in MSOE’s Department of Humanities, Social Science, and Communications. Before arriving at MSOE, he was an Andrew W. Mellon Postdoctoral Teaching Fellow at the University of Pennsylvania, where is also spent a year as Program Director with the Center for Ethics and the Rule of Law (CERL) at the Penn Law School. He works in moral philosophy, broadly construed, and regularly teaches courses in engineering ethics, biomedical ethics, ethics of artificial intelligence, social and political philosophy, philosophy of mind and AI, and epistemology. He serves on the MSOE AI Impact task force.