AI & Governance

Catalog description

Artificial intelligence is becoming central to business strategy, productivity, and competitive advantage across sectors. But unlike prior software innovations, AI systems raise substantial social, environmental, and economic challenges which make trade-offs unavoidable and necessitate appropriate governance models. This course examines AI governance as the set of mechanisms through which companies, regulators, and civil society actors attempt to balance the drive for AI innovation and integration with risk mitigation. Students will analyze why governance challenges arise in the first place, how different governance models have emerged in response, and where those models succeed or fail in practice. The course covers a range of approaches, including corporate self-regulation, government regulation, the application of international standards, and multi-stakeholder initiatives. Rather than treating governance as a compliance exercise, the course frames it as a core strategic question for businesses, and one that is continuously evolving. By the end of the course, students will be equipped with practical frameworks to evaluate AI governance decisions they are likely to confront as executives, investors, or policymakers.