Introduction

This course examines the ethical dimensions of AI, including fairness, transparency, and responsibility in AI systems. Topics cover algorithmic fairness, bias detection, and explainable AI (XAI). Learners will critique AI safety frameworks, implement fairness measures, and apply explanation techniques using practical tools, ensuring that AI solutions are justifiable and aligned with ethical principles for responsible AI deployment.

Learning Outcomes

• Understand ethical implications in AI.
• Critique AI safety and alignment debates.
• Detect and measure algorithmic bias.
• Apply fairness measures and perform empirical analysis.
• Evaluate and implement explanation techniques in AI.