This is an interesting failure-mode to me, and I've been interested in how accurate it is since the inception of these models.

My answer is still yes - I've got this personal concept that AI is sorta the "opposite" of lossy compression... As the model iterates on a larger corpus of context, things are missed, misinterpreted, slightly changed. This all eventually contributes to the writing feeling disconnected. LLMs make decisions on what the most important facet of a prompt is, obviously we can 'guide' it...

Over time, I feel that as we let more AI generated content (no human edited / modified / improved the output) sit around on the internet, the training data will pick up more of this 'poisoned' data and impact future output.