AI Governance in Practice: Ethics and Responsibility 5 credits

As AI plays a greater role in business, it is more important than ever to have clear, ethical, and responsible ways to manage the governance routines in organizations. AI Governance in Practice gives you the knowledge you need to handle this fast changing business landscape, covering topics like ethical frameworks, regulatory rules, data management, and new risks in AI. Whether you are leading AI projects, handling compliance, or advising on responsible AI use, this course provides the introductory tools to help you make informed decisions.

The course covers the foundations of AI governance concepts and principles, including transparency, accountability, and fairness in AI systems. You will have the opportunity to explore ethical frameworks and standards for responsible AI adoption, enabling them to identify and evaluate ethical dilemmas in AI-driven decision-making. It also examines regulatory and compliance landscapes at international, national, and sector-specific levels, with particular attention to the EU AI Act and its implications for organisations. The course further covers data governance principles by addressing how organisations can ensure responsible data use in AI applications. The course also addresses emerging risks in AI, including automated decision-making and the societal and environmental impacts of AI systems. <br> **Connection to Research**<br> The course draws on current research in AI governance, technology ethics, and responsible AI adoption. You engage critically with peer-reviewed literature on algorithmic fairness, accountability mechanisms, and regulatory frameworks. The course also connects to research conducted at JIBS on renewal and ownership, particularly on how emerging technologies reshape organisational governance and strategic decision-making. <br> **Connection to Practice**<br> The course is designed around practice-oriented governance, ethics, and responsible AI. Drawing on practical knowledge of AI governance and regulation, the course integrates case studies and hands-on experience to explore the challenges of understanding and adopting AI governance frameworks. It also aims to bring together industry professionals and participants to discuss challenges and opportunities in AI governance. <br> **Connection to Ethics, Responsibility, Sustainability (ERS)**<br> ERS Perspectives are embedded throughout the course content and assessments. Ethical considerations are central to AI governance, and you critically examine issues of algorithmic bias, transparency, accountability, and fairness as core course themes rather than supplementary topics. The individual assignment is designed to test your ability to conduct an ethical analysis of an AI governance challenge, while the group assignment encourages discussion of the responsible use of AI, including data privacy, AI and environmental impacts, sustainability, and automated decision-making for the broader population.