AI has knowledge, humans have context

The author examines the issue of information transmission through a chain of two AIs: one assisting the author in writing and another summarizing content for the reader. Drawing an analogy to measurement channels in automation, the author notes that errors accumulate in such a scheme. While knowledge is transmitted effectively, context is often lost. The article highlights the danger of a 'common model error' that is broadcast to all readers, creating an illusion of understanding. It explores what specific context is lost during automated text processing and how authors and readers can verify the reliability of information passing through such filters. The author illustrates these findings with personal experience, emphasizing the importance of preserving human context in an era of widespread AI usage.