Automation Bias
We tend to favor decisions made by automated systems over decisions made by humans.
Automation bias is the propensity for humans to favor suggestions from automated decision-making systems and to ignore contradictory information made without automation, even if it is correct. This bias is observed in aviation, medical diagnosis, and navigation. Pilots who over-trust autopilot systems lose the manual flying skills needed when automation fails.
What it looks like in the wild.
- Everyday life GPS Blind Trust Drivers follow GPS directions into rivers, construction zones, or wrong-way one-way streets because they trust the system over their own judgment.
Someone has already built a business on this.
Biases are not only private errors. They are design targets — patterns deliberately engineered into interfaces because they reliably work.
- Algorithms and feeds Algorithmic Authority Credit scoring and hiring algorithms are presented as objective arbiters of quality when they embed and amplify the biases of their training data.
Recognising a definition is not the same skill as spotting it.
Two scenarios from the app, with distractors drawn from the same family of biases — which is what makes them hard.
A manager uses an automated hiring tool that ranks candidates. The tool consistently scores a highly qualified internal applicant low. The manager doesn't override the ranking and moves on to other candidates.
A security guard's camera system shows 'all clear'. The guard hears a noise in a dark corner but doesn't investigate, trusting the system's view.
Biases rarely arrive alone.
Understand more. Assume less.
188 biases, 18,869 scenarios, and a record of how you actually decide.
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