HITL
Human in the Loop (HITL) integrates human judgment into the decision-making process of AI systems.
9 topics found for
“human judgment”
Representativeness
Representativeness is a heuristic in decision-making where individuals judge the probability of an event based on how much it resembles a typical case.
RLHF
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models.
Regressive Bias
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean.
Category Size Bias
A cognitive bias where people judge the likelihood of an event based on the size of its category rather than its actual probability.
Prospect Theory
A behavioral economic theory that describes how people choose between probabilistic alternatives that involve risk, where the probabilities of outcomes are known.
Anchoring
Anchoring (also known as Focalism) is a cognitive bias where individuals rely heavily on the first piece of information (the "anchor") when making decisions.
Egocentric Bias
A cognitive bias where people rely too heavily on their own perspective and experiences when making decisions.
Subadditivity Effect
A cognitive bias where the total probability assigned to a set of events is less than the sum of the probabilities assigned to each event individually.