AI text watermarking and quality loss
Researchers investigating methods to embed invisible watermarks in AI‑generated text report that the technique can degrade readability and coherence. Experiments show that while watermarking helps identify machine‑produced content, it often introduces subtle errors and reduces fluency. The study suggests balancing detection capabilities with preserving output quality, and calls for further refinement before widespread deployment in real-world applications.