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.
Descriptors:
Subject Categories:
- Medicine and Medical Research
- Psychology