Through Cloudflare’s detailed exposure and extensive media coverage reading, the controversy surrounding the cyber scratch practices around AI is deeper and more polarized than it appeared first. CloudFlare accuses of systematically ignoring website blocks and hiding their identities to scrape data from opt-out sites, raising serious issues about ethics, transparency and the future of Internet business models.
What Cloudflare observed
CloudFlare’s report and independent investigations show that AI startups are allegedly confused by crawling and scratching content from websites, which explicitly state (via Robots.txt and Direct Blocks) that AI tools are not welcome. Technical evidence includes changing user agents to mimic MACOS and rotary autonomous system numbers (ASNS) on browsers like Google Chrome – a complex strategy designed to evade detection and blocking. Cloudflare claims it detected tens of thousands of secret scratches that generated millions of domains a day and fingerprinted the crawler using machine learning and other network signals.
Why the allegations matter
For decades, websites have used robots.txt as a “gentleman agreement” to tell bots. Although illegal in few jurisdictions, norms between leaders such as Openai and Anthropic are respectful of these signals. The so-called method of confusion ruined the unwritten contract, demonstrating a willingness to bypass the desire of the site owner in pursuit of training data.
This issue broke out when CloudFlare launched the new “Pay Per Crawl” market that allowed publishers to charge for AI robot access and block most crawlers by default. Major media outlets of Atlantic Ocean, Buzzfeed, Time Inc. and O’Reilly have registered and now over 2.5 million websites are banning AI training altogether.
Respond to confusion
A spokesperson for Confusion dismissed Cloudflare’s blog post, which was nothing more than a “sales promotion”, claiming that the screenshot “showed no access to content” and denied ownership of the robots involved. Later, confused, most of Cloudflare SAW is user-driven acquisition (AI proxy, acting on direct user requests), rather than automatic crawling – a key difference in the ongoing debate about the true meaning of “scratch”. They also mentioned that similar incidents have occurred before, especially theft allegations from media such as Wired, and the company has been working hard to define its own standards for using content.
Response and broader meanings
- Cloudflare’s position: Protect the publisher’s business model, enforce block signals, and charge “AI access” fees for content.
- Confused defense: AI Web Proxy should not be distinguished from human browsing when acting for users.
- Community debate: Some argue on social platforms that if a user requests a public site through confusion, it is similar to opening it in Firefox. Others countered that this hurts website owners’ advertising-driven revenue and control over data.
The overall situation: The Internet’s business model is changing
- Content monetization It is moving quickly. Publishers are moving from advertising to access fees, and scratches are becoming a paid market.
- Transparency and compliance No longer optional. AI companies face reputation and legal risks if they are found to evade blocks or abuse content.
- Data Partnership Will define the future. AI major players are conducting license deals with publishers instead of relying on stealth scratches.
in conclusion
Whether it is unfair or a confusion about truly violating network specifications, this is a watershed. The era of “free data” for AI is about to end. Ethics, economics and new web services platforms such as Cloudflare are driving paid data, greater accountability and sustainable content partnerships. Unless AI companies adapt, they will face locked doors and fragmented internet, which will ultimately reshape the foundations of the digital world.
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Asif Razzaq is CEO of Marktechpost Media Inc. As a visionary entrepreneur and engineer, ASIF is committed to harnessing the potential of artificial intelligence to achieve social benefits. His recent effort is to launch Marktechpost, an artificial intelligence media platform that has an in-depth coverage of machine learning and deep learning news that can sound both technically, both through technical voices and be understood by a wide audience. The platform has over 2 million views per month, demonstrating its popularity among its audience.
