AI Firms Face New Robots.txt Rules for Pay-Per-Output Models
▼ Summary
– Major internet companies and publishers have announced the “Really Simply Licensing” (RSL) standard to address AI crawlers scraping content without permission or compensation.
– RSL evolves robots.txt by adding an automated licensing layer that blocks bots not fairly compensating creators for content usage.
– The open, decentralized protocol is free for publishers and clearly communicates licensing, usage, and compensation terms to AI crawlers and agents.
– RSL supports various models including free, attribution, subscription, pay-per-crawl, and pay-per-inference to protect digital content like webpages, books, and videos.
– The standard was created by the RSL Collective, founded by industry veterans Doug Leeds and Eckart Walther, inspired by the RSS standard and concerns over AI’s impact on publishers.
A new standard is emerging to address the growing tension between AI companies and content creators over the unauthorized use of web data. Called “Really Simply Licensing” (RSL), this protocol aims to modernize the traditional robots.txt file by integrating automated licensing terms, giving publishers a clearer way to demand compensation when their content is used for AI training or output generation.
Announced by the RSL Collective, the initiative has already garnered support from major platforms and publishers such as Reddit, Yahoo, Quora, Medium, and The Daily Beast. The system is designed to be open and decentralized, allowing any publisher to specify licensing requirements, including free use, attribution, subscription, pay-per-crawl, or pay-per-inference models.
The brains behind the effort are Doug Leeds, former CEO of Ask.com, and Eckart Walther, an ex-Yahoo VP who co-created the original RSS standard. Their collaboration began after a speaking engagement at UC Berkeley late last year, where they discussed how AI is reshaping search and content consumption. Both veterans of the search industry, they recognized that falling web traffic and the rise of AI-generated answers have put publishers at a significant disadvantage.
Built on the foundation of the widely adopted RSS framework, RSL can be applied to protect various forms of digital content, from web pages and books to videos and datasets. This allows content owners to define and enforce terms around how their material is accessed and used, especially as AI crawlers increasingly harvest information without transparent compensation structures.
The timing is critical. As generative AI models grow more sophisticated, their reliance on vast amounts of web data has sparked legal and ethical debates. Publishers argue that their content fuels these systems but often without fair payment or acknowledgment. RSL offers a technical and legal pathway to rebalance that relationship, providing a machine-readable method to communicate licensing expectations directly to AI agents.
What sets RSL apart is its flexibility. Publishers can choose from multiple compensation models, including one-time crawl fees or usage-based royalties each time an AI model generates output based on their content. This granularity aims to reflect the real value that original content contributes to AI systems, whether in training or live inference.
Adoption is free and voluntary, but backers hope widespread implementation will create a new norm in AI-data interactions. If successful, RSL could establish a more equitable ecosystem where creators are compensated fairly and AI firms operate with clearer legal and ethical guidelines.
(Source: Ars Technica)
