The increasing subtlety of cases requires careful consideration, as enhanced mitigation efforts can obscure underlying risks. The complexity associated with long-tail failure cases in models, especially when they act as judges, highlights that outputs which may seem benign or obvious to humans can be problematic. Human oversight is essential due to the model's susceptibility to misunderstandings, particularly at the nuanced boundaries of cases. In real-world applications, confusion can arise easily from seemingly innocent subtleties, making them potentially more harmful than straightforward extremes. Therefore, human intervention, often through prompt engineering, becomes crucial to tackle these nuanced challenges.

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