Automation bias is the tendency of human decision-makers to overvalue or defer to recommendations from automated systems, even when those recommendations are incomplete or wrong. It is a governance risk because it can weaken human oversight and cause errors to be accepted without adequate scrutiny.
When a human decision maker favors recommendations made by an automated decision-making system over information made without automation, even when the automated decision-making system makes errors. See Fairness: Types of bias in Machine Learning Crash Course for more information.
The tendency to over-rely on automated systems, often ignoring contradictory information or failing to monitor system output critically.