CSPO 24A18 - Artificial Intelligence: Principles, Risks and Governance

This course provides a comprehensive exploration of artificial intelligence systems, their societal impacts, and governance frameworks. Students will develop a foundational understanding of AI technologies, namely machine learning, deep learning, and generative AI, all presented in accessible and non-technical language. The curriculum examines critical challenges including data bias, explainability, and ethical considerations while analyzing how AI intersects with major societal domains: labor markets, defense systems, democratic institutions, and environmental sustainability. Through weekly discussions of current AI developments, readings of scientific literature, and analysis of case studies, students will gain the analytical tools to evaluate AI's multifaceted impacts. The course aims to provide students a specialized vocabulary necessary to identify, analyze, and address AI-related challenges. By mastering this conceptual framework, students will develop the capacity to recognize patterns across applications and articulate nuanced perspectives on AI governance. No prior technical knowledge is required, as the focus remains on building essential analytical competencies.

Students are expected to have a good level of English and an interest in artificial intelligence. No programming or mathematical knowledge is required to follow this class.

• Group presentation on societal impacts of AI (40 %). Each student will receive both an individual mark and a team mark, which will be combined into a single score for this group presentation. The number of teams and the length of each presentation will be adjusted according to the number of students registered in this course.
• Individual final 2‑hour essay (60 %). Students will write an essay that demonstrates their ability to critically engage with course content and synthesize ideas across all chapters. They are expected to incorporate relevant terminology related to AI and include a brief glossary explaining each term in accessible language. Essays should reference course readings, class discussions, and group presentations. A key component of the evaluation will be how effectively students translate complex AI concepts into clear, well‑reasoned arguments.

Students are expected to participate in the discussion portions of sessions. Each class will begin with a recap of weekly developments involving AI, in which students are encouraged to support with insights.