Scaling Laws AI Copyright Lawsuits with Pam Samuelson
Sep 16, 2025
Pam Samuelson, the Richard M. Sherman Distinguished Professor of Law at UC Berkeley, specializes in copyright law and AI's legal implications. She discusses recent court rulings like Bartz v. Anthropic, probing whether training AI on copyrighted material constitutes fair use. The conversation highlights the balance between protecting creators' rights and promoting innovation, while also exploring the transformative nature of AI outputs. Key cases like Warhol vs. Goldsmith are examined for their impact on copyright law, making this a must-listen for anyone interested in the future of intellectual property.
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Why Training Data Triggers Copyright Issues
- Copyright grants exclusive reproduction rights, so training models by copying works raises prima facie infringement concerns.
- Fair use can defeat infringement, making training on copyrighted works legally contested.
Fair Use Hinges On Transformation And Market Effects
- The fair use analysis centers on transformativeness and market effect, with courts treating them as the most significant factors.
- Greater transformativeness usually reduces the likelihood of market substitution and favors fair use.
Copyright's Broader Public Purpose
- Copyright's constitutional purpose is to promote public progress, not only to benefit authors financially.
- Courts weigh whether allowing a defendant's use advances public benefit versus harming markets for creators.