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Automation bias

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TL;DR. Occurs when humans overly trust automated systems, even when they make mistakes, favoring their outputs over non-automated information.

Technical Definition

Occurs when humans overly trust automated systems, even when they make mistakes, favoring their outputs over non-automated information.

How it works

Automation bias describes the phenomenon where human decision-makers place too much trust in the recommendations of automated systems. This can lead them to ignore or dismiss correct information that contradicts the system's output, even if the automated system is in error. It highlights the importance of critical evaluation even when using advanced technology.

Related Concepts

  • Decision Making — Choosing actions or recommendations under uncertainty, often using probabilistic or utility-based reasoning.
  • Bias (ethics/fairness) — Unfair prejudice or favoritism towards certain groups or things, which can influence data, system design, and user interactions.

Further Reading

  • Google ML Glossary