Politics

Industry-backed RSL 1.0 standard aims to reshape AI content licensing and compensation

Wednesday, 10 December 2025 4:22PM UTC

Leading tech firms and publishers have launched RSL 1.0, a new machine-readable web standard designed to clarify rights, attribution, and payment mechanisms for AI training data, potentially transforming how online content is used and compensated.

Leading internet infrastructure firms, publishers and standards bodies on Wednesday announced the publication of Really Simple Licensing (RSL) 1.0, a machine‑readable web standard intended to let publishers define how their content may be used by artificial intelligence systems and to create new routes for compensation. According to the original report, the RSL Technical Steering Committee , backed by organisations including Cloudflare, Akamai, Creative Commons and the IAB Tech Lab , said RSL 1.0 formalises licensing signals that can sit alongside robots.txt and RSS to express rights, attribution and payment requirements for AI training and search applications. ^[1]^[2]

The specification adds finer-grained usage categories such as "ai-all", "ai-input" and "ai-index" so publishers can permit inclusion in search results while opting out of AI search applications, the committee said. The standard also introduces a "contribution" payment option developed with Creative Commons intended to protect the so‑called digital commons by allowing non‑commercial creators to require monetary or in‑kind contributions from AI systems that benefit from their work. Anna Tumadóttir, CEO of Creative Commons, is quoted in the announcement endorsing contribution and attribution options as vital to sustaining access to knowledge. ^[1]^[2]^[4]

RSL 1.0 is the outcome of a collaborative process led by the RSL Collective and informed by a broad community of publishers and open standards organisations. The initiative traces back to an earlier launch of the RSL protocol in September 2025, when founders and early supporters , among them Eckart Walther, co‑creator of RSS, and Doug Leeds , outlined a vision for scaling a training‑data licensing system across the web and for establishing a collective licensing body analogous to performing‑rights organisations. Industry coverage at that time noted participating sites would publish RSL terms in prearranged formats such as robots.txt to make licensing straightforward for crawlers to detect. ^[3]^[5]^[7]

The release has attracted endorsements from more than 1,500 media organisations, brands and technology companies, the RSL committee said, and lists new publisher supporters including The Associated Press, Vox Media, USA Today, Boston Globe Media, BuzzFeed, Stack Overflow, Arena Group, Mansueto Group, The Guardian and Slate. The announcement framed this scale of backing as covering billions of web pages and representing much of the high‑quality content that currently feeds foundation models. Industry spokespeople quoted in the announcement described RSL as a mechanism to restore clarity and economic alignment between creators and AI platforms. ^[1]^[2]^[6]

Infrastructure vendors emphasised practical implementation paths. Cloudflare said machine‑readable licensing will be important for the web's future and noted its customers already handle large volumes of HTTP 402 payment responses; Akamai highlighted the need for enforceable signals as AI automation grows. Saas vendors such as Supertab signalled they will offer managed RSL server implementations to simplify adoption for publishers. The press release presented these statements as part of a concerted effort to make the standard operational at scale. ^[1]

The RSL Collective , described in the announcement as a nonprofit collective rights organisation , will operate alongside the standard, offering a mechanism to negotiate terms and collect payments where publishers choose to do so. Earlier reporting on the initiative compared the proposed collective to organisations that collect royalties in other creative industries and noted that publisher partnerships are non‑exclusive. The collective is led by Doug Leeds and Eckart Walther, both highlighted in the organisation's materials. ^[1]^[3]^[5]

Advocates say RSL attempts to balance continued open access with sustainable funding models: the contribution‑based licence is pitched as a way to sustain non‑commercial and public‑interest content without forcing sites to close access. Creative Commons framed the contribution option as the first application of its CC signals work to recognise reciprocity in the commons. Critics and neutral observers not quoted in the release have previously warned that any system requiring payments or enforcement could fragment the web or introduce complexity for downstream AI developers; the announcement acknowledges implementation challenges by emphasising standards‑based, machine‑readable integration with existing web infrastructures such as RSS and Schema.org. ^[1]^[4]^[5]

The RSL Technical Steering Committee and the RSL Collective urged publishers, platforms and developers to adopt the specification and participate in further development. According to the original report, the standard will be stewarded with ongoing input from the community and aims to dovetail with complementary work such as the IAB Tech Lab's standards efforts. The announcement pointed readers to rslstandard.org for more information and to view the list of supporters. ^[1]^[4]

Whether RSL 1.0 will rapidly change the economics of AI training or simply become one of several signalling mechanisms remains to be seen; industry data from the founding period shows strong early publisher interest, but practical adoption will depend on tooling, enforcement, and how AI companies respond to machine‑readable licensing at scale. The RSL initiative's proponents argue the standard provides a clear, interoperable starting point for publishers and platforms navigating a fast‑evolving AI landscape. ^[3]^[5]^[6]

📌 Reference Map:

##Reference Map:

^[1] (GlobeNewswire press release) - Paragraph 1, Paragraph 2, Paragraph 4, Paragraph 5, Paragraph 6, Paragraph 8, Paragraph 9
^[2] (GlobeNewswire summary) - Paragraph 1, Paragraph 2, Paragraph 4
^[3] (RSL press page) - Paragraph 3, Paragraph 9
^[4] (RSL standard site) - Paragraph 2, Paragraph 7
^[5] (TechCrunch) - Paragraph 3, Paragraph 7, Paragraph 9
^[6] (Digiday) - Paragraph 4, Paragraph 9
^[7] (Wikipedia) - Paragraph 3

Source: Noah Wire Services

More on this

https://www.globenewswire.com/news-release/2025/12/10/3203217/0/en/RSL-AI-Licensing-1-0-Now-an-Official-Industry-Standard-with-New-Capabilities-as-Momentum-Accelerates.html - Please view link - unable to able to access data
https://www.globenewswire.com/news-release/2025/12/10/3203217/0/en/RSL-AI-Licensing-1-0-Now-an-Official-Industry-Standard-with-New-Capabilities-as-Momentum-Accelerates.html - The RSL Technical Steering Committee, comprising leading internet, media, and technology companies, announced the publication of the official standards specification for Really Simple Licensing (RSL) 1.0, the first licensing standard to protect content in the AI era. Developed collaboratively with the RSL Collective and a broad community of publishers, platforms, and open standards organizations, including Yahoo, Ziff Davis, and O’Reilly Media, RSL 1.0 is an open web standard for publishers and creators to define transparent, machine-readable usage and licensing terms for content used in AI systems. RSL 1.0 introduces new capabilities, such as enhanced control over content use in AI search applications and contribution-based licensing to protect the Digital Commons. The standard has received support from over 1,500 media organizations, brands, and technology companies worldwide, including Cloudflare, Akamai, Creative Commons, and the IAB Tech Lab. Publishers like The Associated Press, Vox Media, USA Today, Boston Globe Media, BuzzFeed, Stack Overflow, Arena Group, Mansueto Group, The Guardian, and Slate have also endorsed RSL 1.0, joining hundreds of other high-quality publishers and media brands. This widespread support spans billions of web pages, representing most high-quality internet content used in AI foundation model training.
https://rslstandard.org/press/rsl-standard - On September 10, 2025, leading internet publishers and technology companies, including Reddit, Yahoo, People Inc., Internet Brands, Ziff Davis, Fastly, Quora, O’Reilly Media, and Medium, announced their support for the launch of the RSL Standard licensing protocol and the nonprofit RSL Collective rights organization. The RSL Standard aims to provide fair, standardized compensation for publishers and creators and simple, automated licensing for AI and technology companies. This initiative seeks to protect content rights in the AI era by enabling publishers to define transparent, machine-readable usage and licensing terms for their content used in AI systems.
https://rslstandard.org/ - The Really Simple Licensing (RSL) standard is an open, collaborative initiative dedicated to defining standardized, machine-readable building blocks for expressing content licensing and compensation rules for how content is accessed and processed for Artificial Intelligence (AI) model development, deployment, and use. The RSL standard allows publishers to define machine-readable licensing terms for their content, including attribution, pay per crawl, and pay per inference compensation. It integrates with RSS and Schema.org to enable publishers to create standards-based, machine-readable catalogs of their licensable content and datasets. The RSL Collective is a nonprofit collective rights organization and technology platform, supported by leading internet companies, with a mission to protect the value of human creativity online by leveraging the RSL Standard to ensure that the millions of online creators and publishers are fairly compensated when AI companies use their work.
https://techcrunch.com/2025/09/10/rss-co-creator-launches-new-protocol-for-ai-data-licensing/ - On September 10, 2025, RSS co-creator Eckart Walther launched the Really Simple Licensing (RSL) protocol, aiming to create a training-data licensing system that could scale across the internet. The RSL Protocol lays out specific licensing terms a publisher can set for their content, whether that means AI companies need a custom license or to adopt Creative Commons provisions. Participating websites will include the terms as part of their 'robots.txt' file in a prearranged format, making it straightforward to identify which data falls under which terms. The RSL team has established a collective licensing organization, the RSL Collective, that can negotiate terms and collect royalties, similar to ASCAP for musicians or MPLC for films. A host of web publishers have already joined the collective, including Yahoo, Reddit, Medium, O’Reilly Media, Ziff Davis, Internet Brands, People Inc., and The Daily Beast. Others, like Fastly, Quora, and Adweek, are supporting the standard without joining the collective.
https://digiday.com/media/arena-group-buzzfeed-usa-today-co-vox-media-join-rsls-ai-content-licensing-efforts/ - In November 2025, more publishers joined the Really Simple Licensing (RSL) Collective AI licensing framework, designed to standardize how publishers tell AI systems what content they can use and how they must pay. Arena Group, BuzzFeed, USA Today Co., and Vox Media have joined the growing list of publishers supporting the framework. The RSL Collective now has over 50 partners, including People Inc., Ziff Davis, Yahoo, Reddit, Medium, and Quora. The partnerships are non-exclusive. RSL’s mission is to stop AI crawlers from scraping publishers’ sites without compensation or permission. The IAB Tech Lab and RSL are collaborating on how each standard can dovetail and complement the other.
https://en.wikipedia.org/wiki/Really_Simple_Licensing - Really Simple Licensing (RSL) is an open content licensing standard that allows web publishers to set terms for web crawlers gathering training data for generative AI use. It was launched on September 10, 2025, and is managed by the nonprofit RSL Collective, co-founded by RSS co-creator Eckart Walther and former Ask.com CEO Doug Leeds. Participating companies at launch include Reddit, Yahoo, and Medium. Publishers can implement the RSL standard by adding licensing terms to their robots.txt files.

Noah Fact Check Pro

The draft above was created using the information available at the time the story first emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed below. The results are intended to help you assess the credibility of the piece and highlight any areas that may warrant further investigation.

Freshness check

Score: 10

Notes: The narrative is fresh, with the earliest known publication date being December 10, 2025. There are no indications of recycled content or discrepancies in figures, dates, or quotes. The narrative is based on a press release, which typically warrants a high freshness score.

Quotes check

Score: 10

Notes: The quotes from Anna Tumadóttir, CEO of Creative Commons, and other industry spokespeople are unique to this release, with no earlier matches found. This suggests potentially original or exclusive content.

Source reliability

Score: 9

Notes: The narrative originates from GlobeNewswire, a reputable press release distribution service. The RSL Collective, a nonprofit rights organization, is also a credible source. However, the reliance on a single outlet for the initial dissemination of information introduces a slight uncertainty.

Plausability check

Score: 10

Notes: The claims about the RSL 1.0 standard and its capabilities are consistent with information from other reputable sources, such as TechCrunch and The Register. The narrative includes specific details about the standard's features and endorsements, which are corroborated by multiple outlets. The language and tone are appropriate for the topic and region, with no inconsistencies or off-topic details.

Overall assessment

Verdict (FAIL, OPEN, PASS): PASS

Confidence (LOW, MEDIUM, HIGH): HIGH

Summary: The narrative is fresh, with no signs of recycled content or discrepancies. The quotes appear original, and the sources are reliable, though the single-source dissemination introduces slight uncertainty. The claims are plausible and corroborated by other reputable outlets, with appropriate language and tone. Therefore, the overall assessment is a PASS with high confidence.

AI licensing
web standards
content monetisation