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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Judgment and Decision Making

Background:

  • Wisdom-of-the-inner-crowd (WIC) phenomenon suggests individuals' judgments improve via specific strategies.
  • Existing WIC strategies, like dialectical bootstrapping, face measurement and robustness challenges.
  • Enrico Fermi's "guesstimation" approach offers a novel framework for WIC research.

Purpose of the Study:

  • Introduce and evaluate Fermian strategies for enhancing WIC.
  • Compare Fermian strategies against dialectical bootstrapping.
  • Investigate moderators like memory aids and data trimming on WIC strategies.

Main Methods:

  • Developed a novel task-environment for estimation.
  • Implemented and compared a similarity-based Fermian strategy with dialectical bootstrapping.
  • Manipulated the presence of a memory aid and applied data trimming techniques.

Main Results:

  • A similarity-based Fermian strategy significantly enhanced WIC more than dialectical bootstrapping.
  • Memory aids differentially impacted strategy performance.
  • Data trimming was found to be a significant factor.
  • Overprecision in WIC estimations was documented for the first time.

Conclusions:

  • Fermian strategies offer a powerful new method for improving individual estimation accuracy.
  • Understanding moderators like memory aids and data trimming is crucial for optimizing WIC.
  • The study confirms that collective intelligence (two persons) surpasses self-estimation (asking oneself twice).