This research quantifies the Data Compliance Gap (DCG) - the performance cost when LLMs respect web crawling opt-outs during training.

• Models trained on opt-out compliant data showed 5-17% performance degradation
• Specialized domains (like biomedical research) suffer disproportionately when major publishers opt out
• Respecting opt-outs leads to more limited factual knowledge but minimal reasoning ability loss
• Presents a fundamental tension between model performance and data ethics

This research matters for security professionals as it provides concrete metrics for balancing AI capabilities against ethical data compliance requirements, helping organizations make informed decisions about responsible AI development.

Original Paper: "Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs"