Human Feedback

Input from human raters or users used to guide AI training, typically in the form of preferences between outputs, quality ratings, or corrections. Human feedback is the foundation of reinforcement learning from human feedback and allows AI developers to incorporate nuanced human values and judgments into model behavior at scale. It also introduces the biases and inconsistencies of the humans providing it, which is a recognized limitation.
See also: reinforcement learning from human feedback, human evaluation, AI alignment.