Skip to main content
Article
Robustness of Multiple Indicators in Automated Screening Systems for Deception Detection
Journal of Management Information Systems
  • Nathan Twyman, Missouri University of Science and Technology
  • Jeffrey Gainer Proudfoot, Bentley University
  • Ryan M. Schuetzler, University of Nebraska at Omaha
  • Aaron Elkins, San Diego State University
  • Douglas C. Derrick, University of Nebraska at Omaha
Document Type
Article
Publication Date
4-1-2016
Abstract

This study investigates the effectiveness of an automatic system for detection of deception by individuals with the use of multiple indicators of such potential deception. Deception detection research in the information systems discipline has postulated increased accuracy through a new class of screening systems that automatically conduct interviews and track multiple indicators of deception simultaneously. Understanding the robustness of this new class of systems and the limitations of its theoretical improved performance is important for refinement of the conceptual design. The design science proof-of-concept study presented here implemented and evaluated the robustness of these systems for automated screening for deception detection. A large experiment was used to evaluate the effectiveness of a constructed multiple-indicator system, both under normal conditions and with the presence of common types of countermeasures (mental and physical). The results shed light on the relative strength and robustness of various types of deception indicators within this new context. The findings further suggest the possibility of increased accuracy through the measurement of multiple indicators if classification algorithms can compensate for human attempts to counter effectiveness.

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Management Information Systems on 13 April 2016, available online: http://www.tandfonline.com/doi/full/10.1080/07421222.2015.1138569.

Citation Information
Nathan Twyman, Jeffrey Gainer Proudfoot, Ryan M. Schuetzler, Aaron Elkins, et al.. "Robustness of Multiple Indicators in Automated Screening Systems for Deception Detection" Journal of Management Information Systems Vol. 32 Iss. 4 (2016) p. 215 - 245
Available at: http://works.bepress.com/rschuetzler/11/