- RSL offers machine-readable licensing for AI training data.
- Major web publishers back RSL to collect royalties efficiently.
- Adoption by AI labs is crucial to prevent copyright chaos
The AI industry is grappling with a mounting copyright problem as lawsuits over unlicensed training data multiply. Following Anthropic’s $1.5 billion settlement, dozens of cases, including one against Midjourney for creating Superman images, are raising alarms about the legal future of AI training practices. The need for a scalable licensing system has never been more urgent.
Real Simple Licensing: A Scalable Solution
In response, technologists and web publishers have launched Real Simple Licensing (RSL), a system designed to streamline licensing for AI training data. Supported by major platforms like Reddit, Quora, and Yahoo, RSL combines technical and legal infrastructure to facilitate data licensing at internet scale. Co-founder Eckart Walther, also a creator of the RSS standard, emphasizes that “we need machine-readable licensing agreements for the internet,” highlighting RSL’s unique approach to AI copyright compliance.
How RSL Works
RSL’s technical backbone allows websites to specify licensing terms via their “robots.txt” files. Publishers can require AI companies to obtain custom licenses or adopt Creative Commons provisions, making it straightforward to identify which data can be used and under what conditions. On the legal side, the RSL Collective acts as a centralized licensing body, negotiating terms and collecting royalties for publishers—similar to ASCAP for music or MPLC for films. This setup gives even smaller websites access to licensing deals they couldn’t negotiate individually.
Adoption Challenges and Industry Outlook
Despite the system’s promise, AI labs face practical hurdles. Tracking when and how specific data is ingested by large language models remains technically complex. While some AI products, like Google’s AI Search Abstracts, maintain real-time attribution, most training pipelines do not log usage precisely enough to calculate royalties per data point. Nonetheless, RSL’s founders are confident that the system can function effectively enough to ensure publishers are fairly compensated.
The real question is adoption. Historically, web data has been treated as free or low-cost, and some AI labs may resist paying royalties. However, high-profile calls for licensing protocols from leaders like Sundar Pichai suggest momentum is building. RSL’s success could set a precedent, helping the AI industry navigate copyright law while maintaining access to high-quality training data.
Also Read: China’s $8B AI Strategy: How Lean, Practical Investments Are Challenging U.S. Tech
RSL represents a critical step toward legal clarity in AI training. By uniting publishers under a scalable licensing system, it may finally address the industry’s data dilemma—if AI companies embrace it.
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