New Standard for Website Interaction with AI: ForkLog Lab Sets Rules for Machine Reading of Content
The internet has ceased to be a space exclusively for humans. AI models, crawlers, and autonomous agents daily index, summarize, and transform public data. In response to this reality, the ForkLog Lab team has developed and implemented a machine-readable page that sets clear boundaries for interaction between web resources and artificial intelligence.
The first integration of the standard, named ForkLog AI Access version 0.1, was implemented with the ForkLog magazine. The page acts as a single access point, understandable to both humans and automated systems—from search bots to LLM crawlers.
What is Allowed and What is Prohibited
The document outlines four scenarios for public use: indexing of open pages (taking robots.txt into account), short quotations with attribution, links to originals, and non-commercial research summaries. However, without a separate license, mass scraping of full texts, training commercial models on archives, distributing full-text datasets, and removing attribution are strictly prohibited.
This is an important step toward formalizing the rights of content creators in an era when data has become raw material for AI. The market has long needed transparent mechanisms that separate legal citation from uncontrolled exploitation.
Licensed Access and Ecosystem
In addition to the basic level, the standard provides four tiers of access: Discovery Access (search engines and non-commercial research), Research Access (academic use), Commercial Dataset Access (for AI products and financial tools), and Strategic Access (deep integrations and partnerships).
The page also describes related projects: N0X—an experimental human-AI knowledge system, and doNONdo—a network performance offering 10 minutes of inactivity daily. These initiatives underscore ForkLog's philosophical approach to human-machine interaction.
From my perspective, such standards are not merely a technical formality but a necessary foundation for the sustainable development of the AI industry. Without clear rules of the game, we risk turning the internet into a legal vacuum zone, where quality content is devalued by machine copying.