Evidence-Driven Policy Making

Catalog description

This course explores the role of artificial intelligence (AI) and machine learning (ML) in shaping evidence-driven policy decisions across various sectors. Using case studies from various AI/ML sectors, students will critically examine how AI/ML tools influence policy outcomes. Rather than delving into the technical intricacies of ML, this course emphasizes a "black box" approach, where data inputs lead to predictions. Students will learn to distinguish between prediction and intervention, recognize the limitations of AI/ML, and develop a transparent, precise language for discussing these technologies. By fostering healthy skepticism, this course equips students to make informed decisions about AI's role in evidence-based policy making.