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Debiasing Judgements Using a Distributed Cognition Approach: A Scoping Review of Technological Strategies.

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  • 1The University of Edinburgh, UK.

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Summary

Technological debiasing strategies, viewed through distributed cognition, offer a novel system-level approach to minimize cognitive bias in high-stakes decision-making. Most reviewed strategies proved effective, highlighting potential for real-world application.

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Cognitive biascognitive engineeringdecision makingperformancereasoning

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Area of Science:

  • Cognitive Science
  • Human-Computer Interaction
  • Systems Engineering

Background:

  • Cognitive biases impact high-stakes decision-making.
  • Technological debiasing shifts focus from individuals to system design.
  • Distributed cognition theory provides a framework for understanding information flow in decision environments.

Purpose of the Study:

  • Synthesize research on technological debiasing strategies.
  • Introduce a novel classification system based on distributed cognition.
  • Discuss theoretical implications for mitigating cognitive bias.

Main Methods:

  • Systematic literature search across six databases.
  • Classification of debiasing strategies (group composition, information design, procedural) and cognitive biases.
  • Analysis of 80 articles covering 100 debiasing investigations and 91 cognitive biases.

Main Results:

  • 80% of technological debiasing strategies were effective; 14% ineffective, 6% partially effective.
  • Information design strategies were most frequently studied, followed by procedural and group composition.
  • Identified gaps and future research directions in technological debiasing.

Conclusions:

  • Technological debiasing, framed by distributed cognition, reconceptualizes cognitive bias mitigation.
  • The proposed classification system aids in understanding and applying debiasing strategies.
  • Findings can inform the design of high-stakes work systems to reduce judgment errors.