Human Evaluation

Human evaluation asks people to score, rank, compare, or annotate AI outputs. It is essential for qualities such as usefulness, tone, creativity, cultural appropriateness, factual support, and safety when no automatic metric fully represents the goal. A reliable study defines clear criteria, randomizes presentation, includes representative tasks, trains evaluators, and measures agreement. Reviewers can still be inconsistent, fatigued, biased, or influenced by style, brand, and answer length. Preference results also depend on who participates and what context they receive. Human evaluation should protect worker well-being, especially for harmful content, and be combined with automated tests that provide scale and reproducibility.