Methods, systems, and computer programs are presented for notifying users of identified bias when the users make decisions. One method includes an operation for tracking, by a bias machine-learning program (MLP), the activities of a user. A set of features is defined for detecting bias, where the features include user profile information, user environment information, history of activities and decisions of the user, community information, and a knowledge base that includes facts. Additionally, the bias MLP detects a decision of the user based on the tracked activities, and analyzes the decision for bias when making the decision. The analysis is based on the decision, facts relevant to making the decision, and the features utilized by the bias MLP. When a bias is detected, a notification is presented to the user of the detection of the bias, with one or more reasons for the detected bias.
IDENTIFICATION OF DECISION BIAS WITH ARTIFICIAL INTELLIGENCE PROGRAM