No matter how detailed the rules are, agents do not apply them deterministically. They generate predictions, and errors are inevitable. Humans intervene not to declare the truth but to manage uncertainty.
Humans identify risky outputs, evaluate contextual alignment and reduce uncertainty.
Context, formatting, repeated values and agent explanations form the basis of human evaluation.
Agents cannot detect their own mistakes. When conflicting or unclear results appear, responsibility shifts to human review.
Agents produce results with confidence levels and uncertainty signals. Humans approve, reject or escalate the result.
A claim file may contain different policy start dates: 01.04.2023, 03.04.2023 and 1/4/23. The agent may place these dates in incorrect context. The human examines the document and selects the most reliable date.
Rules improve agents but cannot eliminate errors. Human and agent collaboration creates a more reliable system.