Human judgment in artificial intelligence includes defining the real problem, selecting evidence, recognizing context, weighing tradeoffs, and deciding whether an automated result is suitable for action. It matters most when objectives are ambiguous, evidence is incomplete, values conflict, or errors could cause meaningful harm.
Models can support judgment by organizing information and offering alternatives, but fluent output is not independent verification. People remain responsible for checking sources, understanding uncertainty, challenging assumptions, and preserving the ability to reject or revise an automated recommendation.
