Why can I not trace which retrieved document is responsible for what my AI just said?
机会
Enterprise RAG systems retrieve documents from internal corpora, licensed datasets, and external sources and generate responses that blend retrieved content. No standardized mechanism traces which retrieved chunk influenced which output sentence. This makes copyright compliance guesswork, PII leakage from retrieved documents undetectable after the fact, and fulfilling GDPR Art. 15 subject access requests for AI-generated outputs impossible to do accurately. Training-time attribution research is advancing, but inference-time chunk attribution at production scale remains an open and unsolved problem with no agreed standard.
为什么重要
Without inference-time attribution, any enterprise running RAG on regulated data is accumulating compliance liability it cannot measure or contain.
我如何评估机会
机会评分是我的个人判断，而非量化指标：痛苦程度、发生频率，以及当前解决方案的匮乏程度。分数越高，意味着我认为越值得去构建。
出现时造成的痛苦程度。
人们实际遇到它的频率。
当前针对它的优质工具有多匮乏。