What is an automation bias?
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.
automation bias explained in plain English
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.
Example
Practitioners refer to automation bias when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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- attribute
Synonym for feature.
- bias
1.
- bias (math) or bias term
An intercept or offset from an origin.
- calibration layer
A post-prediction adjustment, typically to account for prediction bias.
- Confabulation
When an AI produces a confident, fluent answer that sounds true but is factually wrong — generating plausible language without a reliable link to reality.
- confirmation bias
The tendency to search for, interpret, favor, and recall information in a way that confirms one's pre-existing beliefs or hypotheses.
- counterfactual fairness
A fairness metric that checks whether a classification model produces the same result for one individual as it does for another individual who is identical to the first, except with respect to one or more sensitive attributes.
- coverage bias
See selection bias.
- demographic parity
A fairness metric that is satisfied if the results of a model's classification are not dependent on a given sensitive attribute.
- differential privacy
In machine learning, an anonymization approach to protect any sensitive data (for example, an individual's personal information) included in a model's training set from being exposed.