Hallucinations Undermine Trust; Metacognition Is a Way Forward
13 hours ago
- #Metacognition in AI
- #Uncertainty in LLMs
- #AI Hallucinations
- Hallucinations, or confident errors, remain a major issue for generative AI and LLMs, even in simple factoid QA.
- Most factual improvements have come from expanding knowledge boundaries, not from improving awareness of those boundaries.
- Perfectly distinguishing known from unknown may be inherently difficult, leading to a trade-off between eliminating hallucinations and preserving utility.
- Reframing hallucinations as confident errors allows for a third approach: expressing uncertainty, termed 'faithful uncertainty'.
- Faithful uncertainty aligns linguistic expressions with intrinsic uncertainty, a key aspect of metacognition.
- Metacognition involves awareness of one's own uncertainty and acting on it, such as honest communication in interactions or as a control layer in agents.
- Developing metacognition is crucial for making LLMs both trustworthy and capable, with open problems remaining for progress.