Airport artificial intelligence can detect deception: or am i lying?

Abstract

Since the 9/11 terrorist attacks, research has enveloped numerous areas within the psychological sciences as a means to increase the ability to spot potential threats. While airports took to heightened security protocols, many academics looked deeper into ways of detecting deception within international airport settings. Various verbal and nonverbal systems were intensely scrutinised under the empirical magnifying glass with the aim of creating security environments that are better able to detect potential threats. However, in 2018, a €4.5 m grant from the European Union’s Horizon 2020 research and innovation programme, number 700,626, was awarded to further in vivo test the use of computational methods to detect deception from facial cues. The system is deemed a noninvasive psychological profiling system and stems from that of a system called ‘Silent Talker’ (Rothwell et al. in Appl Cognit Psychol 20(6):757–777, 2006). The ‘iBorderCtrl’ AI system uses a variety of ‘at home’ pre-registration systems and real time ‘at the airport’ automatic deception detection systems. Some of the critical methods used in automated deception detection are that of micro-expressions. In this opinion article, we argue that considering the state of the psychological sciences current understanding of micro-expressions and their associations with deception, such in vivo testing is naïve and misinformed. We consider the lack of empirical research that supports the use of micro-expressions in the detection of deception and question the current understanding of the validity of specific cues to deception. With such unclear definitive and reliable cues to deception, we question the validity of using artificial intelligence that includes cues to deception, which have no current empirical support.

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Notes

  1. 1.

    Note, between submission of article and publication, the iBorderCtrl system has been tested, and initial anecdotal evidence suggests that it resulted in a false positive (Gallagher and Jona 2019). We hope future developers of such technology will heed the advice in this article and/or contact the authors to discuss developing such systems.

References

  1. ActuIA. 2019. iBorderCtrl : A dangerous misunderstanding of what AI really is—ActuIA. https://www.actuia.com/english/iborderctrl-a-dangerous-misunderstanding-of-what-ai-really-is/. Accessed 5 Mar 2019.

  2. Adelson, R. 2004. Detecting deception. Monitor on Psychology 35: 7.

    Google Scholar 

  3. Albrechtsen, J.S., C.A. Meissner, and K.J. Susa. 2009. Can intuition improve deception detection performance? Journal of Experimental Social Psychology. https://doi.org/10.1016/j.jesp.2009.05.017.

    Article  Google Scholar 

  4. Barrett Feldman, L. 2014. Opinion|what faces can’t tell us. https://www.nytimes.com/2014/03/02/opinion/sunday/what-faces-cant-tell-us.html. Accessed 8 Mar 2019.

  5. Barrett Feldman, L. 2017a. How emotions are made: The secret life of the brain. Boston, MA: Houghton Mifflin Harcourt.

    Google Scholar 

  6. Barrett Feldman, L. 2017b. Why our emotions are cultural—not built in at birth. https://www.theguardian.com/lifeandstyle/2017/mar/26/why-our-emotions-are-cultural-not-hardwired-at-birth. Accessed 8 Mar 2019.

  7. Baskin, D.R., and I.B. Sommers. 2010. Crime-show-viewing habits and public attitudes toward forensic evidence: The “CSI effect”; revisited. The Justice System Journal. https://doi.org/10.2307/27977480.

    Article  Google Scholar 

  8. Bernal, N. 2018. AI lie detectors to be tested by the EU at border points. The Telegraph. https://www.telegraph.co.uk/technology/2018/11/01/ai-lie-detectors-tested-eu-border-points/.

  9. Best, S. 2017. The robot that knows when you’re lying: Scientists create an AI that can detect deception in the courtroom (and it’s already “significantly better” than humans). http://www.dailymail.co.uk/sciencetech/article-5197747/AI-detects-expressions-tell-people-lie-court.html. Accessed 12 Aug 2018.

  10. Bogaard, G., E.H. Meijer, A. Vrij, and H. Merckelbach. 2016. Strong, but wrong: Lay people’s and police officers’ beliefs about verbal and nonverbal cues to deception. PLoS ONE. https://doi.org/10.1371/journal.pone.0156615.

    Article  Google Scholar 

  11. Bond, C.F., and B.M. DePaulo. 2006. Accuracy of deception judgments. Personality and Social Psychology Review 10 (3): 214–234. https://doi.org/10.1207/s15327957pspr1003_2.

    Article  Google Scholar 

  12. Bringsjord, S., and B. Schimanski. 2003. What is artificial intelligence? Psychometric AI as an answer. In IJCAI International Joint Conference on Artificial Intelligence (pp. 887–893). http://www.cyc.com.

  13. Brunswik, E. 1952. The conceptual framework of psychology. Psychological Bulletin 49 (6): 654–656.

    Article  Google Scholar 

  14. Burgoon, J.K. 2018. Microexpressions are not the best way to catch a liar. Frontiers in Psychology 9: 1672. https://doi.org/10.3389/fpsyg.2018.01672.

    Article  Google Scholar 

  15. Burgoon, J.K., D.B. Buller, A.S. Ebesu, C.H. White, and P.A. Rockwell. 1996. Testing interpersonal deception theory: Effects of suspicion on communication behaviors and perceptions. Communication Theory 6 (3): 243–267. https://doi.org/10.1111/j.1468-2885.1996.tb00128.x.

    Article  Google Scholar 

  16. Colwell, K., C.K. Hiscock-Anisman, A. Memon, L. Taylor, and J. Prewett. 2007. Assessment criteria indicative of deception (ACID): An integrated system of investigative interviewing and detecting deception. Journal of Investigative Psychology and Offender Profiling 4 (3): 167–180. https://doi.org/10.1002/jip.73.

    Article  Google Scholar 

  17. Debey, E., B. Verschuere, and G. Crombez. 2012. Lying and executive control: An experimental investigation using ego depletion and goal neglect. Acta Psychologica 140 (2): 133–141. https://doi.org/10.1016/J.ACTPSY.2012.03.004.

    Article  Google Scholar 

  18. DePaulo, B.M., J.J. Lindsay, B.E. Malone, L. Muhlenbruck, K. Charlton, and H. Cooper. 2003. Cues to deception. Psychological Bulletin 129 (1): 74–118. https://doi.org/10.1037//0033-2909.129.1.74.

    Article  Google Scholar 

  19. EDRi. 2019. Greece: Clarifications sought on human rights impacts of iBorderCtrl–EDRi. https://edri.org/greece-clarifications-sought-on-human-rights-impacts-of-iborderctrl/. Accessed 8 Mar 2019.

  20. Ekman, P. 1992. Telling lies: Clues to deceit in the marketplace, politics, and marriage. Design (Vol. Paperback). https://doi.org/10.1080/00029157.2011.10404358.

  21. Ekman, P. 2019. Facial action coding system|micro expressions. https://www.paulekman.com/product-category/facs/. . Accessed 8 Mar 2019.

  22. Ekman, P., and W.V. Friesen. 2016. Nonverbal leakage and clues to deception. Psychiatry 32 (1): 88–106. https://doi.org/10.1080/00332747.1969.11023575.

    Article  Google Scholar 

  23. Faul, F., E. Erdfelder, A.-G. Lang, and A. Buchner. 2007. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods 39 (2): 175–191. https://doi.org/10.3758/BF03193146.

    Article  Google Scholar 

  24. Freeborn, D. 2006. From old English to standard English : a course book in language variation across time. Studies in English language series. http://hotfile.com/dl/83728759/def5fc0/From.old.english.to.standard.english.rar.

  25. Gafurov, D., E. Snekkenes, and P. Bours. 2007. Spoof attacks on gait authentication system. IEEE Transactions on Information Forensics and Security. https://doi.org/10.1109/TIFS.2007.902030.

    Article  Google Scholar 

  26. Gallagher, R., and L. Jona. 2019. We tested Europe’s new digital lie detector. It failed. https://theintercept.com/2019/07/26/europe-border-control-ai-lie-detector/. Accessed 27 Aug 2019.

  27. Ghosh, P. 2019. AAAS: Machine learning “causing science crisis”—BBC News. https://www.bbc.co.uk/news/science-environment-47267081. Accessed 5 Mar 2019.

  28. Gold, S. 2012. Border control biometrics and surveillance. Biometric Technology Today 2012 (7): 9–11. https://doi.org/10.1016/S0969-4765(12)70149-2.

    Article  Google Scholar 

  29. Granhag, P.A., and M. Hartwig. 2015. The strategic use of evidence technique: A conceptual overview. In Detecting deception: Current challenges and cognitive approaches. (pp. 231–251). Hoboken: Wiley-Blackwell.

  30. Hadid, A. 2014. Face biometrics under spoofing attacks: Vulnerabilities, countermeasures, open issues, and research directions. In IEEE computer society conference on computer vision and pattern recognition workshops (pp. 113–118). https://doi.org/10.1109/CVPRW.2014.22.

  31. Hartwig, M., and C.F. Bond. 2011. Why do lie-catchers fail? A lens model meta-analysis of human lie judgments. Psychological Bulletin 137 (4): 643–659. https://doi.org/10.1037/a0023589.

    Article  Google Scholar 

  32. Henig, R.B. 2006. Looking for the lie. https://www.nytimes.com/2006/02/05/magazine/looking-for-the-lie.html?_r=1. Accessed 12 Aug 2018.

  33. Henrich, J., S.J. Heine, A. Norenzayan. 2010. Most people are not WEIRD. Nature 466: 29. https://www.nature.com/articles/466029a.

    Article  Google Scholar 

  34. Homo Digitalis. 2019. Homo Digitalis Reporting to the Hellenic Parliament on the use of the IBORDERCTRL system at the Greek border. https://www.homodigitalis.gr/posts/2771. Accessed 5 Mar 2019.

  35. Honts, C.R., M. Hartwig, S.M. Kleinman, and C.A. Meissner. 2009. Credibility assessment at portals: Portals committee report. Final Report of the Portals Committee to the Defense Academy for Credibility Assessment.

  36. Hurley, C.M., and M.G. Frank. 2011. Executing facial control during deception situations. Journal of Nonverbal Behavior 35 (2): 119–131. https://doi.org/10.1007/s10919-010-0102-1.

    Article  Google Scholar 

  37. iBorderCtrl. 2019. Technical framework. https://www.iborderctrl.eu/Technical-Framework. Accessed 27 Feb 2019.

  38. Jansen, A.S.P., X.V. Nguyen, V. Karpitskiy, T.C. Mettenleiter, and A.D. Loewy. 1995. Central command neurons of the sympathetic nervous system: Basis of the fight-or-flight response. Science 270 (5236): 644–646. https://doi.org/10.1126/science.270.5236.644.

    Article  Google Scholar 

  39. Jones, D. 2010. Psychology. A WEIRD view of human nature skews psychologists’ studies. Science 328 (5986): 1627. https://doi.org/10.1126/science.328.5986.1627.

    Article  Google Scholar 

  40. Jupe, L.M., and M. Hartwig. 2019. Deception, anxiety and folk beliefs: An examination of the asymmetrical anxiety heuristic. Manuscript in Preperation.

  41. Keatley, D. 2018. Pathways in crime: An introduction to behaviour sequence analysis. New York: Springer.

    Google Scholar 

  42. Kleinberg, B., A. Arntz, and B. Verschuere. 2019. Being accurate about verbal credibility assessment. https://doi.org/10.31234/OSF.IO/H6PXT.

  43. Kohli, N., D. Yadav, M. Vatsa, R. Singh, and A. Noore. 2016. Detecting medley of iris spoofing attacks using DESIST. In 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems, BTAS 2016. https://doi.org/10.1109/BTAS.2016.7791168.

  44. Leal, S., and A. Vrij. 2008. Blinking during and after lying. Journal of Nonverbal Behavior 32 (4): 187–194. https://doi.org/10.1007/s10919-008-0051-0.

    Article  Google Scholar 

  45. Levine, T.R., K.B. Serota, and H.C. Shulman. 2010. The impact of Lie to Me on viewers’ actual ability to detect deception. Communication Research 37 (6): 847–856. https://doi.org/10.1177/0093650210362686.

    Article  Google Scholar 

  46. Lovell-Badge, R. 2013. Nine out of ten statistics are taken out of context|Understanding Animal Research|Understanding Animal Research. http://www.understandinganimalresearch.org.uk/news/communications-media/nine-out-of-ten-statistics-are-taken-out-of-context/. Accessed 5 Mar 2019.

  47. Luke, T.J. 2018. Lessons from Pinocchio: Cues to deception ay be highly exaggerated. Perspectives on Psychological Science 14: 646–671. https://doi.org/10.31219/OSF.IO/XT8FQ.

    Article  Google Scholar 

  48. Mann, S., A. Vrij, R. Bull, A. Vrij, and R. Bull. 2018. True lies: police officers’ ability to detect suspects’ lies. Investigating the Truth 147: 172. https://doi.org/10.4324/9781315169910-10.

    Article  Google Scholar 

  49. Marcel, S., M. Nixon, and S. Li. 2014. Handbook of Biometric Anti-Spoofing. http://link.springer.com/content/pdf/10.1007/978-1-4471-6524-8.pdf.

  50. Marono, A., D.D. Clarke, J. Navarro, and D.A. Keatley. 2017. A behaviour sequence analysis of nonverbal communication and deceit in different personality clusters. Psychiatry, Psychology and Law. https://doi.org/10.1080/13218719.2017.1308783.

    Article  Google Scholar 

  51. Marono, A., D. Clarke, J. Navarro, and D. Keatley. 2018. A sequence analysis of nonverbal behaviour and deception. Journal of Police and Criminal Psychology 33 (2): 109–117. https://doi.org/10.1007/s11896-017-9238-9.

    Article  Google Scholar 

  52. McGrath, C. 2018, November 2. Lie detector scheme to boost fight against “terror threats” trialled at EU borders. The Express. https://www.express.co.uk/news/world/1040150/eu-news-lie-detector-scheme-fight-terror-threats-trialled-borders-hungary.

  53. McLennan, C.T. 2006. The time course of variability effects in the perception of spoken language: Changes across the lifespan. In Language and speech (Vol. 49, pp. 113–125). https://doi.org/10.1177/00238309060490010701.

  54. Nahari, G. (2018). The applicability of the verifiability approach to the real world. In P. R. J (Ed.), Detecting concealed information and deception: recent developments (pp. 329–349). https://doi.org/10.1016/B978-0-12-812729-2.00014-8.

  55. National Crime Agency. 2017. Identity crime. http://www.nationalcrimeagency.gov.uk/crime-threats/identity-crime. Accessed 14 Dec 2017.

  56. Nguyen, D.T., Y.H. Park, H.C. Lee, K.Y. Shin, B.J. Kang, and K.R. Park. 2012. Combining touched fingerprint and finger-vein of a finger, and its usability evaluation. Advanced Science Letters 5 (1): 85–95. https://doi.org/10.1166/asl.2012.2177.

    Article  Google Scholar 

  57. Nortje, A., and C. Tredoux. 2019. How good are we at detecting deception? A review of current techniques and theories. South African Journal of Psychology. https://doi.org/10.1177/0081246318822953.

    Article  Google Scholar 

  58. O’Sullivan, M., M.G. Frank, C.M. Hurley, and J. Tiwana. 2009. Police lie detection accuracy: The effect of lie scenario. Law and Human Behavior. https://doi.org/10.1007/s10979-008-9166-4.

    Article  Google Scholar 

  59. Ortony, A., and T.J. Turner. (1990). What’s basic about basic emotions? Psychological Review (Vol. 97). Retrieved from https://pdfs.semanticscholar.org/df84/be52a5c0a51db7e9545a0bdd2ab3c389cc3b.pdf.

  60. Poole, D.L., A.K. Mackworth, and R. Goebel. 1998. Computational intelligence: A logical approach (1st ed.). New York.

  61. Porter, S., and L. ten Brinke. 2008. Reading between the lies: Identifying concealed and falsified emotions in universal facial expressions. Psychological Science 19 (5): 508–514. https://doi.org/10.1111/j.1467-9280.2008.02116.x.

    Article  Google Scholar 

  62. Rothwell, J., Z. Bandar, J. O’Shea, and D. McLean. 2006. Silent talker: A new computer-based system for the analysis of facial cues to deception. Applied Cognitive Psychology 20 (6): 757–777. https://doi.org/10.1002/acp.1204.

    Article  Google Scholar 

  63. Rothwell, J., Z. Bandar, J. O’Shea, and D. McLean. 2007. Charting the behavioural state of a person using a backpropagation neural network. Neural Computing and Applications 16 (4–5): 327–339. https://doi.org/10.1007/s00521-006-0055-9.

    Article  Google Scholar 

  64. Rozin, P., L. Lowery, and R. Ebert. 1994. Varieties of disgust faces and the structure of disgust. Journal of Personality and Social Psychology (Vol. 66). Retrieved from https://pdfs.semanticscholar.org/123b/28a4b062a73daa4abef15e91e23b49382bf4.pdf.

  65. Samuel, A.L. 1959. Some studies in machine learning using the game of checkers. IBM Journal of Research and Development 3 (3): 210–229. https://doi.org/10.1147/rd.33.0210.

    Article  Google Scholar 

  66. Sartori, G., K. Tasios, A. Vrij, S. Leal, and R.P. Fisher. 2018. Verbal deception and the model statement as a lie detection tool. Frontiers in Psychiatry 9: 492. https://doi.org/10.3389/fpsyt.2018.00492.

    Article  Google Scholar 

  67. Soweon, Y., J. Feng, and A.K. Jain. 2012. Altered fingerprints: Analysis and detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (3): 451–464. https://doi.org/10.1109/TPAMI.2011.161.

    Article  Google Scholar 

  68. Su, L., and M. Levine. 2016. Does “lie to me” lie to you? An evaluation of facial clues to high-stakes deception. Computer Vision and Image Understanding. https://doi.org/10.1016/j.cviu.2016.01.009.

    Article  Google Scholar 

  69. Twyman, N.W., J.G. Proudfoot, R.M. Schuetzler, A.C. Elkins, and D.C. Derrick. 2015. Robustness of multiple indicators in automated screening systems for deception detection. Journal of Management Information Systems 32 (4): 215–245. https://doi.org/10.1080/07421222.2015.1138569.

    Article  Google Scholar 

  70. Vrij, A. 2000. Detecting lies and deciet: The psychology of lying and the implications for professional practice. Chichester: Wiley.

    Google Scholar 

  71. Vrij, A., R.P. Fisher, and H. Blank. 2017. A cognitive approach to lie detection: A meta-analysis. Legal and Criminological Psychology 22 (1): 1–21. https://doi.org/10.1111/lcrp.12088.

    Article  Google Scholar 

  72. Vrij, A., R.P. Fisher, H. Blank, S. Leal, and S. Mann. 2016a. A cognitive approach to elicit verbal and nonverbal cues to deceit. Cheating, Corruption, and Concealment: The Roots of Dishonesty. https://doi.org/10.1017/CBO9781316225608.017.

    Article  Google Scholar 

  73. Vrij, A., R. Fisher, S. Mann, and S. Leal. 2006. Detecting deception by manipulating cognitive load. Trends in Cognitive Sciences 10 (4): 141–142. https://doi.org/10.1016/j.tics.2006.02.001.

    Article  Google Scholar 

  74. Vrij, A., and G. Ganis. 2014. Theories in deception and lie detection. Credibility Assessment: Scientific Research and Applications. https://doi.org/10.1016/B978-0-12-394433-7.00007-5.

    Article  Google Scholar 

  75. Vrij, A., and P.A. Granhag. 2012. Eliciting cues to deception and truth: What matters are the questions asked. Journal of Applied Research in Memory and Cognition 1 (2): 110–117. https://doi.org/10.1016/J.JARMAC.2012.02.004.

    Article  Google Scholar 

  76. Vrij, A., L. Hope, and R.P. Fisher. 2014. Eliciting reliable information in investigative interviews. Policy Insights from the Behavioral and Brain Sciences 1 (1): 129–136. https://doi.org/10.1177/2372732214548592.

    Article  Google Scholar 

  77. Vrij, A., S. Leal, S. Mann, Z. Vernham, and F. Brankaert. 2015. Translating theory into practice: Evaluating a cognitive lie detection training workshop. Journal of Applied Research in Memory and Cognition 4 (2): 110–120. https://doi.org/10.1016/j.jarmac.2015.02.002.

    Article  Google Scholar 

  78. Vrij, A., S. Mann, S. Leal, Z. Vernham, and M. Vaughan. 2016b. Train the trainers: A first step towards a science-based cognitive lie detection training workshop delivered by a practitioner. Journal of Investigative Psychology and Offender Profiling 13 (2): 110–130. https://doi.org/10.1002/jip.1443.

    Article  Google Scholar 

  79. Wang, W.S.Y. 1979. Language change a lexical perspective. Annual Review of Anthropology 8 (1): 353–371. https://doi.org/10.1146/annurev.an.08.100179.002033.

    Article  Google Scholar 

  80. Widrow, B., and M. Hoff. 1960. Adaptive switching circuits. https://apps.dtic.mil/dtic/tr/fulltext/u2/241531.pdf.

  81. Woollacott, E. 2017, August 1. Better drugs, faster: The potential of AI-powered humans. BBC News. https://www.bbc.co.uk/news/business-40708043.

  82. Wu, Z., B. Singh, L.S. Davis, and V.S. Subrahmanian. 2017. Deception detection in videos. http://arxiv.org/abs/1712.04415.

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Jupe, L.M., Keatley, D.A. Airport artificial intelligence can detect deception: or am i lying?. Secur J 33, 622–635 (2020). https://doi.org/10.1057/s41284-019-00204-7

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Keywords

  • Lie detection
  • Airport security
  • Artificial intelligence
  • Machine learning
  • iBorderCtrl