Am I accepting it because it is useful, or because it sounds authoritative?
Automation bias and appropriate reliance
People can rely too heavily on automated advice, or fail to use reliable help. The useful target is reliance that matches the system’s actual capabilities in the situation.
An everyday example
A fluent summary gets approved without checking its numbers. On another task, a correct calculation is discarded simply because AI produced it.
Original illustration, not an observed participant case.
Where the idea stops
Neither trusting everything nor rejecting everything demonstrates good judgment.
Something to try
Compare an output with its source. Keep supported claims, correct contradicted claims, and leave unsupported claims unresolved.
Practise on a fictional case →Go deeper: the builder’s view
For builders: test both false acceptance and false rejection. Measure the combined human-system outcome, including verification time.
Source and interpretation
This is a plain-language interpretation with an applied example; it is not a quotation or an endorsement from the source.
Lee & See — Trust in Automation: Designing for Appropriate Reliance (2004) ↗Catalog v0.1 · checked 2026-10-29