Evidence and limits
Finding: Participants lost confidence in an algorithm faster than in a human after observing comparable mistakes, even when the algorithm performed better.
Impact: Strengthen matched error-history presentation. Reject adoption rate as performance evidence.
Boundary: Forecasting choices do not cover open-ended work. Next: how should systems show comparative failure rates without encouraging blanket reliance?
Flags: forecasting tasks; observed-error framing
Record State: Catalog review recorded; not a performance endorsement
What was reviewed: Structure and relevance screened; not a full evaluation