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The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
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Gaze bias differences capture individual choice behaviour.

Armin W Thomas1,2,3, Felix Molter2,3,4,5, Ian Krajbich6

  • 1Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany.

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Summary
This summary is machine-generated.

People often choose items they look at longer. This study found gaze bias varies greatly between individuals, impacting choice accuracy. Understanding this gaze-choice link improves decision-making models.

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Area of Science:

  • Cognitive psychology
  • Decision science
  • Behavioral economics

Background:

  • Simple choices, like selecting fruit, involve complex cognitive processes.
  • Previous research links group-level gaze allocation to choice behavior, with longer viewing predicting selection.
  • Individual variability in this gaze-choice relationship remains largely unexplored.

Purpose of the Study:

  • To quantify the individual differences in the gaze bias effect during simple choices.
  • To investigate how the strength of gaze bias influences choice accuracy.
  • To develop a computational model accounting for individual gaze bias variability.

Main Methods:

  • Conducted four simple choice experiments involving visual stimuli.
  • Recorded participants' gaze allocation during decision-making.
  • Applied a computational model to analyze individual gaze-choice associations and predict behavior.

Main Results:

  • A gaze-choice association was present in most individuals but varied significantly in strength.
  • Individuals with a stronger gaze bias exhibited poorer performance in selecting the optimal choice.
  • The computational model successfully explained and predicted individual differences in choice behavior by incorporating gaze bias variability.

Conclusions:

  • Individual differences in gaze bias are substantial and impact decision-making effectiveness.
  • A stronger link between what we look at and what we choose can lead to suboptimal choices.
  • Computational models that account for individual gaze bias offer a more accurate understanding of choice behavior.