AI Didn't Break Copyright Law, It Just Exposed How Broken It Was
10 hours ago
- #intellectual-property
- #copyright-law
- #generative-ai
- AI has exposed the existing ambiguities and inconsistencies in copyright law, rather than breaking it.
- Copyright law traditionally operates under human-scale assumptions, tolerating non-commercial, private creations like fan art.
- Generative AI removes human-scale constraints, making gray areas in copyright law unmanageable and leading to legal battles.
- Banning AI training on copyrighted content is impractical due to the saturation of legally posted content about copyrighted characters online.
- Enforcing copyright at the training layer is unfeasible due to the scale and complexity of AI model training.
- Enforcement at the generation layer is problematic due to the difficulty in determining intent and the impracticality of statutory damages.
- Copyright law functions best at the distribution layer, where harm is most evident, but AI complicates this by blurring the lines between creation and distribution.
- Liability for AI-generated content is complex, with no clear solution that doesn't favor incumbents or require invasive surveillance.
- Global nature of AI development means strict U.S. regulations may be circumvented by foreign models, leading to a two-tier system.
- Existing copyright frameworks are ill-suited for the dynamic, personalized, and on-demand content that AI enables, raising fundamental questions about the future of IP.