Quiz dotyczący danych dotyczących dozwolonego użytku i szkoleń w zakresie sztucznej inteligencji

Odpowiedzi i wyjaśnienia pojawiają się w miarę rozwiązywania quizu.

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