Search Engines, AI, And The Long Fight Over Fair Use
Search Engines, AI, And The Long Fight Over Fair Use
https://www.eff.org/deeplinks/2026/01/search-engines-ai-and-long-fight-over-fair-use
Publish Date: 2026-01-23 20:09:00
Source Domain: www.eff.org
Key Points:
- Focus on Fair Use vs. Copyright Control: The article discusses the ongoing debate between copyright holders and technologists about whether new tools like generative AI should be allowed to analyze and build upon existing works without extensive permission.
- Historical Precedent of Fair Use: Courts have historically recognized copying for purposes like analysis and indexing as fair use, emphasizing its importance for a free and open internet.
- Transformative Use of AI Training: Training AI models, through the analysis of many works to extract patterns, qualifies under fair use as it creates new outputs rather than replicates original works.
- Impact of Copyright Expansion: Expanding copyright to require permissions for learning and analysis could hinder research and innovation in science, medicine, and technology by making large-scale data analysis impractical.
- Supporting Case Law: In Bartz v. Anthropic, the court upheld the view that AI training is transformative, signaling a proper approach to handling these issues.
- Misaligned Response to Automation: The article argues that using copyright law to address the impact of AI and automation on jobs is misdirected; the focus should be on government-led economic transition management rather than copyright restrictions.
- Preserving Fair Use for Expression: Maintaining fair use is critical for ensuring that learning from prior works doesn’t hinder innovation and free expression, echoing historical rulings and practices.
- Consequences of Broad Licensing: Expanding copyright in this area would benefit mainly large, established companies, excluding smaller firms, nonprofits, and open-source contributors.
