ai.txt: A Domain-Specific Language for Guiding AI Interactions with the Internet
Yuekang Li, Wei Song, Bangshuo Zhu, Dong Gong, Yi Liu, Gelei Deng, Chunyang Chen, Lei Ma, Jun Sun, Toby Walsh, Jingling Xue

TL;DR
ai.txt is a new domain-specific language that enables precise regulation of AI interactions with web content, addressing limitations of existing standards and promoting responsible AI use online.
Contribution
The paper introduces ai.txt, a DSL that extends URL controls with element-level regulations and natural language instructions for AI systems.
Findings
Effective regulation through XML-based enforcement
Successful integration of natural language prompts
Preliminary experiments demonstrate practical viability
Abstract
We introduce ai.txt, a novel domain-specific language (DSL) designed to explicitly regulate interactions between AI models, agents, and web content, addressing critical limitations of the widely adopted robots.txt standard. As AI increasingly engages with online materials for tasks such as training, summarization, and content modification, existing regulatory methods lack the necessary granularity and semantic expressiveness to ensure ethical and legal compliance. ai.txt extends traditional URL-based access controls by enabling precise element-level regulations and incorporating natural language instructions interpretable by AI systems. To facilitate practical deployment, we provide an integrated development environment with code autocompletion and automatic XML generation. Furthermore, we propose two compliance mechanisms: XML-based programmatic enforcement and natural language prompt…
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