Course 3 · Module 3
Information, Fairness, and Creative Rights
This module covers three disputes about what AI does to shared goods: reliable information, fair treatment, and creative work. You'll be able to assess claims about AI-generated misinformation against the evidence, explain why fairness has competing definitions that can't all be met, and compare creators' and developers' positions on training data using what courts have ruled. Each topic has more evidence behind it than the headlines suggest, and less agreement.
Module objectives
- Assess the evidence on how AI-generated content affects misinformation and public trust.
- Explain how bias enters AI systems and compare the standards of fairness used to judge them.
- Compare the positions of creators and AI developers on training data, using the state of the law.
Lessons
- Lesson 1 Information and Rights: Synthetic media, misinformation, and trust You'll compare the predicted flood of AI-generated misinformation with what researchers have measured, and look at harms that are well documented, such as fraud. You'll be able to… 61111h 3m
- Lesson 2 Information and Rights: Bias, fairness, and automated decisions You'll see how bias gets into AI systems through data and design, and why "fair" has several definitions that conflict. You'll be able to explain a well-known dispute over a… 61111h 3m
- Lesson 3 Information and Rights: Copyright, training data, and creative work You'll examine the dispute over whether AI developers may train models on copyrighted work without permission. You'll be able to state each side's position and say what US and UK… 611111h 33m