Automation Bias

A tendency to over-rely on an automated or AI-generated suggestion, especially when people stop checking the result independently.

Automation bias does not mean that people always blindly trust systems. It describes situations where an automated recommendation changes attention, judgment or the ability to notice errors. In AI use, it can appear when a model output starts to replace independent checking.

Why it matters

  • It helps explain why fluent or confident outputs can be accepted too quickly.
  • It connects AI literacy with human oversight and calibrated trust.
  • It shows that risk can come from the relation between person, system, task and workflow.
  • It matters most when AI output informs consequential decisions.

What not to simplify

Automation bias is not the same as every mistake involving AI. It should not be used to claim that people always trust automation, or that any use of an automated recommendation is wrong. Context, time pressure, interface design and expertise all matter.

Sources and context

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