What does it mean in everyday language?

People may lose confidence in a computerized recommendation after seeing it make a mistake, while remaining more forgiving of human mistakes.

An example

Hypothetical example: a person abandons a forecasting tool after one visible error and returns to a method that has a worse record across many predictions.

A more precise definition

Algorithm aversion describes reduced willingness to use algorithmic judgment relative to a human alternative. In foundational experiments, observing an algorithm make errors reduced its use despite its superior overall performance.

Key features

  • Concerns preference for a decision source
  • Can follow observing an algorithm's mistakes
  • Requires a meaningful comparison of performance

Where the definition stops

Rejecting a system is not necessarily irrational. Its performance, suitability, transparency, and the costs of its errors may provide good reasons not to use it.

How it relates to synthetic imprinting

Synthetic experiences may influence trust in either direction. This concept helps avoid assuming that realistic or fluent AI output always increases reliance.

Research context

Dietvorst, Simmons, and Massey demonstrated algorithm aversion in forecasting studies. The finding is context-dependent; other experiments show a preference for algorithmic advice.

Sources and further reading

  1. Algorithm aversion: People erroneously avoid algorithms after seeing them err. — Berkeley J. Dietvorst, Joseph P. Simmons, Cade Massey (2015). Journal of Experimental Psychology: General.

Cite this definition

APA: SyntheticImprinting.com. (2026). Algorithm Aversion. https://syntheticimprinting.com/terms/algorithm-aversion/

MLA: “Algorithm Aversion.” SyntheticImprinting.com, 2026, https://syntheticimprinting.com/terms/algorithm-aversion/. Accessed September 26, 2026.

Chicago: SyntheticImprinting.com. “Algorithm Aversion.” Last modified 2026-09-24. https://syntheticimprinting.com/terms/algorithm-aversion/.

What the status means

Established Concept

A concept used in academic or professional literature. This label does not mean every claim about it is settled.

How evidence labels work

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