This research examines how Reinforcement Learning from Human Feedback (RLHF) impacts both the quality and detectability of AI-generated content.

• RLHF significantly improves text quality by making AI outputs more human-like
• However, this improvement makes AI text harder to detect using current detection methods
• Creates a security challenge where more aligned models produce content that's more difficult to identify as non-human
• Highlights the tension between creating helpful AI systems and maintaining the ability to identify AI-generated content

These findings are crucial for security professionals developing detection tools and policies for managing AI-generated content in sensitive contexts.

Understanding the Effects of RLHF on the Quality and Detectability of LLM-Generated Texts