Date of Award
3-22-2019
Document Type
Thesis
Degree Name
Master of Science in Cyber Operations
Department
Department of Electrical and Computer Engineering
First Advisor
Brett Borghetti, PhD
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.
AFIT Designator
AFIT-ENG-MS-19-M-065
DTIC Accession Number
AD1076610
Recommended Citation
Villarreal, Micah, "Confirmation Bias Estimation from Electroencephalography with Machine Learning" (2019). Theses and Dissertations. 2290.
https://scholar.afit.edu/etd/2290