Accession Number:

AD1076610

Title:

Confirmation Bias Estimation from Electroencephalography with Machine Learning

Descriptive Note:

Technical Report

Corporate Author:

AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH WRIGHT-PATTERSON AFB United States

Personal Author(s):

Report Date:

2019-03-01

Pagination or Media Count:

177.0

Abstract:

Cognitive biases are known to plague human decision making and can have disastrous effects in the fast-paced environments of military operators. Traditionally, behavioral methods are employed to measure the level of bias in a decision. However, these measures can be hindered by a multitude of subjective factors and cannot be collected in real-time. This work investigates enhancing the current measures of estimating confirmation bias with additional behavior patterns and physiological variables to explore the viability of real-time bias detection. Confirmation bias in decisions is estimated by modeling the relationship between Electroencephalography EEG signals and behavioral data using machine learning methods.

Subject Categories:

  • Medicine and Medical Research
  • Psychology

Distribution Statement:

APPROVED FOR PUBLIC RELEASE