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Time Pressure Increases Automation Reliance in a Face Matching Task.

Alysha J Hua1, Peter J B Hancock2, Daniel J Carragher1

  • 1School of Psychology, Faculty of Health and Medical Sciences, The University of Adelaide, SA, Australia.

Quarterly Journal of Experimental Psychology (2006)
|November 21, 2025
PubMed
Summary
This summary is machine-generated.

Time pressure increases reliance on automated facial recognition (AFR) systems. Humans improved accuracy with AFR assistance, especially under high time pressure, but still struggled to correct system errors.

Keywords:
automated systemsdecision-makingface identificationhuman-algorithm teaming

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Area of Science:

  • Cognitive Psychology
  • Human-Computer Interaction
  • Biometrics

Background:

  • Automated facial recognition (AFR) systems are widely used for identity verification.
  • Human operators often rely on AFR systems as decision aids.
  • Previous research indicates time pressure negatively impacts human face matching accuracy.

Purpose of the Study:

  • To investigate how time pressure affects human reliance on AFR system decisions.
  • To determine if increased time pressure leads to greater automation reliance.
  • To assess the impact of AFR assistance on human accuracy under varying time constraints.

Main Methods:

  • 129 participants completed a face matching task under high (2s), medium (5s), and low (10s) time pressure.
  • Participants made unaided decisions, then reviewed an AFR system's decision (92.3% accurate), and submitted an aided decision.
  • Stimuli disappeared after the allocated time, simulating real-world operational constraints.

Main Results:

  • Human accuracy improved with AFR assistance across all time pressure conditions.
  • The greatest accuracy improvements were observed under higher time pressure.
  • Aided human accuracy remained lower than the AFR system's standalone accuracy.
  • Participants struggled to override incorrect AFR system decisions, leading to decreased accuracy.

Conclusions:

  • Increased time pressure enhances human reliance on automated facial recognition systems.
  • While AFR assistance improves human performance, it does not fully compensate for time pressure effects.
  • Effective human oversight of AFR systems requires strategies to mitigate over-reliance and improve error correction capabilities.