Polygraph

This page is an evolving compilation of my previous research on polygraphs (aka “lie detectors”). After completing National Science Foundation-supported dissertation and post-doctoral research on bias in decision-making technologies and policing, I left academia and live happily as an artist in Berlin. However, if someone would like to pick up where I left off, here’s what I learned. This page is intended as a resource to other researchers.

 

Literature Review

The first thing you need to know if you’re interested in polygraphs as an academic is that your lit review has been done for you—by the National Academy of Sciences (2003), no less. It’s not going to be outdated anytime soon, because there is no vibrant culture of peer-reviewed polygraph science in existence. Since the scientific consensus is that polygraphs are insufficiently evidence-based, that’s unlikely to change.

 

Graduate Work (2010-2014)

Here’s my Ph.D. dissertation from the University of Virginia, which I defended Jan. 2014, supported by an NSF Doctoral Dissertation Research Improvement Grant among other awards/honors. The take-away is that bias can seep into technology-mediated processes—but we also have to worry about the more qualitative ways that values can set the terms of these processes themselves. In other words, to the policy-maker: There’s always a man behind the technological curtain. But what are you doing asking him to read your fortune in the first place? And to the young researcher: Don’t get too caught up measuring technology-centered bias effects when structural inequalities more than explain unjust outcomes. (Alex Vitale says this better.)

Here’s a bit of an off-topic off-shoot from the medical decision diagnosis comparative case study: “Overriding Race and Class Bias: Equity in Technology-Mediated Diagnosis.” It indicates that even much more scientifically moored, obviously useful tools such as medical decision-making tools can be vulnerable to bias.

Here are the results of a survey of Virginia state-licensed polygraphers that I conducted as part of my pre-doctoral research for two graduate methods classes: “Virginia Polygrapher Survey 2010-2011.” They indicate that polygraphers are demographically like law enforcement management: overwhelmingly white, male, older, conservative, and current or former law enforcement—and that one in five of them reports believing that some groups of people (e.g., blacks) are more likely to pass or fail the polygraph than other groups.

 

Post-Graduate Work (2016)

Here’s my subsequent Science Creative Quarterly extension of problems with polygraph programs to the broader contexts of mass surveillance and refugee screening. This is a simple extension of the Bayes’ Rule application from the NAS 2003 polygraph report that shows mass screenings for low-prevalence problems have the potential to harm security and human rights alike.

Here’s a curated re-release of federal polygraph documents that I made open-source, that then disappeared… Suggesting that I should perhaps put my research on my own website this time. (Hi.) I shared related files, including many obtained through years of Freedom of Information Act (FOIA) requests and FOIA lawsuits against several federal agencies, interviews, and other muckraking with McClatchy for a multi-part national investigative series here. The lawyer and reporter in this case did not use encryption as a general practice or upon my request, and the documents I made open-source later disappeared from both their websites. So one lesson there is to use good infosec and work with people who do.

Another note on FOIA: The federal system is broken. Even with NSF support for my dissertation research, I never got the data I needed to test for bias in federal polygraph programs. Instead I paid a lot of money to lose. Except I eventually “won” a Pyrrhic Freedom of Information victory for American educational requestors, so you can play the same game too? Don’t. It’s a losing game. Especially if you have a defined research agenda with specific hypotheses you’d like to test with specific data—unlike a journalist who can just go fishing for interesting stuff and hope to get lucky—FOIAing state and local agencies in the U.S. is generally a better bet.

Here’s a paper I was honored to present by invitation at an American Studies Symposium at Osaka University in Japan (2016), alongside keynote speaker/lie detection history rockstar Ken Alder. “Lie Detectors On Trial? Science, Security, and Accountability in the Era of the Hague Invasion Act.” It reformulates polygraph programs as an interesting corruption problem more than anything else, since the scientific consensus has basically always been against them—yet the programs grow and grow.

 

Interviews (2008-2011)

My dissertation research began as a series of interviews about polygraphs that I filmed, intending to make a documentary on the subject. But then I wanted to know the scientific answers to the questions that the anecdata suggested, so I wrote a dissertation trying. Now some of the people I interviewed at the start of this process are dead (of natural causes), and they generously gave me their time while they were alive… So it seems right to share what they shared with me, even though it’s not a finished product…

These interviews (tapes and transcripts) are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Thanks again to all my interviewees.

(Below this line is under construction, with additional links/content coming soon.—6 Feb. 2018/vw)

Stephen Fienberg. In Memorium. Video. Transcript.

Rose McDermott. Video. Transcript.

Witness to Innocence—death row exonerees Shabaka Waqlimi (aka Joe Green Brown), Clarence Brandley, Herman Lindsey, Derrick Jamison, Juan Melendez, and Dave Keaton. In Memorium Dave Keaton and Mamie Brown. Video (part 1 of 2/in process). Transcript.

Jim Woolsey. Video. Transcript.
John F. Sullivan. Video. Transcript.
George Maschke. Video. Transcript.
Ilana Greenstein. Video. Transcript.
Mark Zaid. Video. Transcript.

Jeff Stein. Video. Transcript.
Tim Longo. Video. Transcript.
Jim Coan. Video. Transcript.

Share