Fair Use Of Generative AI: Why Its Plausibility Is Questionable

The article discusses the challenges of applying the fair use doctrine to generative AI, which creates content like text, art, and music by learning from vast datasets that often include copyrighted materials. Traditional fair use factors—such as transformative use, scale of usage, market impact, and lack of consent—are difficult to satisfy with generative AI. AI outputs typically lack the intentional transformation seen in human creativity, and the large-scale use of copyrighted content without consent disrupts creative markets and weakens fair use claims.

Legal cases like Authors Guild v. Google and Anderson v. Stability AI highlight the tension between generative AI and copyright protections. The article suggests that current legal and ethical frameworks are inadequate for addressing these issues. Proposed solutions include opt-in models for creators, licensing systems, transparency requirements, and regulatory guidelines to balance innovation with creator rights. The article argues that new frameworks are needed to ensure generative AI benefits society without undermining the rights of creators.

Key takeaways:

Generative AI challenges traditional fair use principles due to its large-scale, automated processes involving copyrighted material.
AI's lack of intentionality and transformative purpose makes it difficult to meet fair use requirements.
The use of copyrighted material without consent and potential market impact further weakens fair use claims for generative AI.
New legal and ethical frameworks are needed to balance innovation with creator rights, including opt-in models and licensing systems.

Fair Use Of Generative AI: Why Its Plausibility Is Questionable

Key takeaways:

Comments (0)

Newsletter