"Truth Machines" from Polygraphs to Neural Analysis: Technologically-Assisted Cheating and Deception Detection in Historical Focus

Jo Ann Oravec, University of Wisconsin-Whitewater

This presentation explores the "truth machine" notion and applications in historical, social, and technological context. Use of polygraphs on employees has often been prohibited or constrained in many US and international contexts; however, some forms of “virtual polygraphy” have emerged that have not been explicitly banned in many of their implementations. Despite many technical and legal obstacles, new technological capabilities for detecting lies, deception, and false impersonation have been integrated into various organizational systems, increasing the “personal transparency” of employees and often of clients as well. Some of these deception-detection mechanisms capture employee documents, profiles, and personal characteristics and behaviors for later use in system analytics or in other applications, possibly presenting privacy invasions. Informing employees about the systems’ intents and requesting consent about deception detection has the potential to challenge some individuals to “game” the systems and attempt to subvert the detection mechanisms involved. The presentation explores the early history and legal standings of polygraphs; it extends the discussion to examine the efforts of ProctorU, Converus (EyeDetect), and Examity Corporations as well as recent neural research in deception detection. (ProctorU and Examity initiatives were once primarily focused on student cheating, but have expanded in applications to workplace settings.) Issues of whether the full intent of the systems can be communicated in a comprehensible fashion are of special concern in efforts to obtain informed consent and to implement the systems humanely. Big data, profiling, surveillance, and predictive analytics in deception detection systems may change radically the relationships between individuals and organizations, introducing new potentials for bias and disempowerment. Some references: Oravec, J. A. (2018). Secrecy in educational practices: Enacting nested black boxes in cheating and deception detection systems. Secrecy and Society, 1(2), 5. Schrage, M. (2011). The future of lie detection in the workplace. Harvard Business Review. Retrieved from https://hbr.org/2011/08/most-managers-wouldnt-dream-of.html

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 Presented in Session 65. Health, Law and Technology