Fair Use and AI Training Data Quiz

Answers and explanations appear as you take the quiz.

1. Which fair use factor asks about harm to the market for the original work?
   • Factor one
   • Factor two
   • Factor three
   • Factor four
2. Why did the court reject fair use in Thomson Reuters v. Ross Intelligence?
   • Ross copied Westlaw headnotes to build a competing, non-generative tool
   • Ross used pirated novels
   • Ross published the headnotes as a book
   • Ross failed to register its software
3. In Bartz v. Anthropic, what did Judge Alsup find was NOT covered by fair use?
   • Training on purchased books
   • Building a central library from pirated copies
   • Scanning purchased print books
   • Using the trained model to answer questions
4. What settlement did Anthropic reach in Bartz, as reported?
   • $15 million total
   • No money, only an apology
   • About $1.5 billion, roughly $3,000 per covered work
   • A license to use all future books free
5. Why did Meta win in Kadrey v. Meta?
   • The authors did not develop evidence of market harm
   • The judge ruled all AI training is always legal
   • The books were in the public domain
   • Meta had licenses for every book
6. What is 'market dilution' as discussed in Kadrey?
   • A drop in stock price after a lawsuit
   • Lower printing costs for publishers
   • Mixing training data from different sources
   • Floods of AI-generated works competing with originals
7. What did Warhol v. Goldsmith emphasize for factor one?
   • Any commercial use is unfair
   • Only nonprofit uses can be fair
   • Whether the use serves a different purpose, not just adds new meaning
   • The length of the copied work
8. Why does the guide say output filtering cannot cure every fair use problem?
   • Filters are illegal
   • Liability can arise from how the data was acquired, before any output
   • Filters always slow models down
   • Courts never consider outputs