automation bias
What It Means
Automation bias happens when people trust AI systems too much and stop thinking critically about the results. Instead of using AI as a tool to help make decisions, employees begin accepting AI outputs without question, even when those outputs might be wrong or incomplete.
Why Chief AI Officers Care
This creates significant business risk because bad AI decisions can go unchecked, leading to financial losses, compliance violations, or damaged customer relationships. It also reduces the human expertise in your organization over time, as people stop developing their judgment skills and become overly dependent on automated systems.
Real-World Example
A bank's loan officers start automatically approving all loans that the AI system recommends, without reviewing the applicant's full financial picture or considering market conditions the AI might not account for. This leads to approving risky loans that a human would have caught, resulting in higher default rates.
Common Confusion
People often think automation bias only happens with obviously flawed AI systems, but it actually occurs most with systems that work well most of the time. The better the AI performs generally, the more likely people are to stop questioning its occasional mistakes.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, automation bias occurs when clinicians over-rely on AI diagnostic tools or clinical decision support syst...
Finance: In finance, automation bias occurs when analysts and decision-makers over-rely on algorithmic trading systems, credit sc...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"over-relying on the outputs of AI systems"Source: David_Leslie_Morgan_Briggs
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