Algorithm Aversion
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
People tolerate errors made by algorithms far less than errors made by humans. If a human doctor makes a mistake, we consider it an 'accident'; if an AI doctor makes the same mistake, we deem the algorithm 'completely unreliable' and abandon it, even if the algorithm's average accuracy is far higher than that of humans.
SCAFFOLDING EFFECT
Reduce cognitive load
AI deployment strategy. When introducing AI-assisted decision-making, it is necessary to set extremely low 'expectations'. Because a single conspicuous failure (AI hallucination) can destroy users' trust in the entire system.
Anchor fast decisions
It refers to the phenomenon that people tend to distrust and are reluctant to adopt algorithmic advice even when algorithms are more accurate, especially when algorithms make mistakes, they are more likely to be rejected.
MINIMUM ACTION
In progress 0/4Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Algorithm_aversionverified
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