Fairness & Bias

Catalog description

This course investigates the pursuit of building equitable technology by addressing fairness and bias in algorithmic systems. Students will review the latest advancements in creating more equitable algorithms, exploring definitions and types of (un)fairness. The course covers the challenges of explaining machine learning processes, ensuring accountability in algorithmic decisions, and addressing systemic biases. Through a combination of theoretical insights and practical approaches, students will gain a comprehensive understanding of how to design and implement fair and accountable AI systems.