Predicting unethical behavior from interview responses : machine learning models versus human judges

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.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Wang, Sibo,M. Eng.Massachusetts Institute of Technology.

Advisor dc:contributor.advisor

• Thomas W. Malone.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/123114

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/123114