Predicting unethical behavior from interview responses : machine learning models versus human judges
Name
1128184807-MIT.pdf
Size
1.15 MB
Format
Adobe PDF
Checksum (MD5)
563ccdbb2c810d25d2f7c4376a46c5da
Author(s)
Wang, Sibo,M. Eng.Massachusetts Institute of Technology.
Advisor(s)
Thomas W. Malone.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
How can we evaluate peoples moral character? Judging someones moral character can be a difficult task, especially through only short interactions such as an interview. In this thesis, I examined the possibility of using machine learning techniques to predict peoples propensity to commit certain unethical behavior based on analyzing their responses to interview questions aimed at testing their moral character. I experimented with a number of machine learning algorithms and text analysis techniques and created models for predicting unethical behavior based on the interview response texts. The model results are then compared to 1. human judge ratings of the interviewees moral character and 2. human judge predictions of the interviewees tendency to cheat based on reading the same interview responses. Overall, we showed that machine learning models can explain parts of the variance in unethical behavior that were not explained by human judge ratings.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 53-54).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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