AI Accountability: Build Responsible and Transparent Systems [Released: 8/20/2025]

AI offers businesses the potential for a dramatic increase in functionality and profitability, but it can also spark an array of complex ethical, legal, and social challenges. In this nontechnical, conceptually oriented course, Barton Poulson digs into the hazards of generative AI, offering potential solutions to some of its key concerns.

Barton explores the ethical issues posed by AI, including competing concepts of fairness and moral reasoning. He also goes over social concerns and safety challenges for AI, such as potential life-and-death scenarios drawn from medicine and military warfare. Barton concludes with recommendations tailored to developers, executives, PR professionals, regulators, and consumers to help them reap the potential benefits of generative AI in a way that's trustworthy and profitable for everyone involved.

Learning objectives

• Review the challenges of AI.
• Apply narrow AI to a decision.
• Define two major approaches used when dealing with AI.
• Examine supervised and unsupervised learning.
• Explain harassment by AI.
• Identify three concepts that distributive justice is based on.