Human-like metacognitive skills will reduce LLM slop and aid alignment and capabilities

A new analysis argues that Large Language Models (LLMs) lack metacognitive skills—the ability to monitor and correct their own thinking. The paper hypothesizes that developing these skills in AI could dramatically reduce errors and 'slop,' curb sycophancy, and potentially aid alignment research by helping models catch their own mistakes. The author notes this work is already underway and could lead to significant capability gains alongside alignment benefits.