AI Ethics and Responsible AI

About this guide

A concise exam companion for AI ethics and responsible AI. It works through moral foundations, where bias comes from, fairness definitions and the impossibility results, privacy and differential privacy, transparency and explainability, accountability and auditing, and safety. Worked examples are marked the way an examiner marks them, so you can see why an answer earns the grade, and every claim is dated so you can see how current it is.

Inside the guide

• Moral foundations
• Where bias comes from
• Fairness definitions and the impossibility results
• Privacy and differential privacy
• Transparency and explainability
• Accountability and auditing
• Safety

Questions students ask