Detecting Deception the Detection of Research Proposal

  • Length: 10 pages
  • Sources: 10
  • Subject: Physics
  • Type: Research Proposal
  • Paper: #34179664

Excerpt from Research Proposal :



In that regard, the future applications of Ekman's principles and techniques for identifying concealment of emotions and deception of intentions may improve the accuracy, efficiency, and speed of facial analysis. In general, computer applications are much more capable of analyzing such information accurately than even the best-trained human beings (Ekman, 2003). Deliberate attempts to employ anti-detection techniques to counter the methods of detection introduced by Ekman may indeed be possible with respect to human beings, however, the increased precision with which computers perform the same fundamental analyses of facial expressions is likely much more difficult to circumvent through deliberate facial manipulations.

First, the highly complex mathematical formulae through which computer facial scanning software perform the same analyses of facial expressions use much more precise objective data than those capable of being considered by human beings (Safir,

2003). Second, whereas human detection relies almost exclusively on the examination of each individual separately, computer analysis incorporating facial recognition software

allows systematic comparison of multiple individuals in the same environment (Safir,

2003).

This elemental difference between human and automatic computerized facial analysis allows facial pattern recognition software to automatically compare successive individuals, that dramatically increase the effectiveness of facial recognition because it provides an additional independent method of comparison between the levels of stress and other elements capable of reflection in facial expression (Ekman, 2003; 2006). in

addition to increasing the accuracy of deception recognition through facial scanning, this aspect of computerized facial expression analysis also addresses some of the principal ethical concerns in relation to personal privacy of innocent individuals as well as in relation to the erroneous attribution of deliberately deceptive facial expressions in circumstances where those facial expressions are attributable to the stresses of external environment (such as air travel) rather than to nefarious intentions (Ekman, 2006; Safir,

2003).

Ethical Considerations in Practical Application of Deception Detection Techniques

There are several ethical considerations associated with the widespread use of facial recognition techniques. First, as explained by Ekman (2006), there are benign explanations for deliberate concealment of internal emotional states, including the desire to hide extreme anguish such as that associated with emotional losses that have nothing at all to do with terrorism or other illegal activities. The ethical concern in that respect is that airline passengers, for just one of many possible examples, could be targeted for increased scrutiny by security personnel at the worst possible time in their lives and without any cause, at least from the perspective of their intentions. Second, civil libertarians are fundamentally opposed to involuntary intrusions into the private aspects of human life, and suggest that public surveillance and analysis of facial expressions constitutes an invasion of personal privacy because it is tantamount to reading people's minds without their consent (Ekman, 2006).

With respect to the first ethical concern, it is anticipated that the sophisticated analyses of which computerized facial recognition scanning will soon be capable will eliminate false positives associated with benign concealment of internal emotional states, in addition to being able to distinguish outward facial (and other behavioral) signs associated with the ordinary stress of circumstances and those consistent with nefarious intent (Ekman, 2006; Safir, 2003). Likewise, with respect to the second major ethical concern, well-established principles of the difference between the reasonable expectation of privacy (REP) in public areas and those associated with non-public areas already provide the basis for the moral and legal (i.e. constitutional) validity of employing facial recognition scanning techniques in public areas and high-value potential terrorist targets

(Dershowitz, 2002).

Ultimately, facial recognition scanning for outwardly-detectable signs of concealment of emotional state and intentions is an invaluable tool for law enforcement and counterterrorism agencies. Granted, the limitations of human capabilities, even with training in the specific recognition techniques that have proven effective, raise legitimate issues of ethical concern. However, with the imminent development of more sophisticated methods of applying the techniques introduced by Ekman, it is anticipated that computerization of the process will dramatically increase it usefulness while at the same time resolving any legitimate potential ethical concerns.

Conclusion

During the course of human evolution, human beings developed various means of deliberately concealing their true feelings and reactions using many of the same methods of artificially manipulating their physical postures, vocal intonations, and facial expressions as those typically employed by other nonhuman animal species. Beginning in the 1970s, psychologist Paul Ekman introduced the concept of micro-expressions that he had identified as characteristic mannerisms associated with the deliberate attempt to conceal true reactions and emotions in human beings that have since been widely acknowledged by other researchers as one of many evolved survival mechanisms in the species.

More recently, the phenomenon first identified by Ekman has been successfully

incorporated into security, law enforcement, and counterterrorism applications the need for which increased dramatically after the infamous terrorist attacks of September 11,

2001 and the subsequent initiation of the Global War on Terror under the lead of the domestic United States law enforcement community and military. In that regard, the principal value of the use of micro-expression recognition techniques is that they are readily capable of being taught very quickly in a manner that substantially increases the ability of individuals involved in interdicting potential terrorists and other criminals to identifying them and distinguishing them from among larger groups of innocent individuals.

The law enforcement and counterterrorism techniques implementing Ekman's micro-expression recognition principals have already been used with considerable success in airport passenger screening, border protection, and general law enforcement applications. Currently, those principals are also being adapted for eventual widespread use in automatic computerized applications capable of being deployed in high-volume public areas and at high-value potential terrorist targets. The addition of computer technology to the field will greatly enhance the ability of security and counterterrorism entities to screen large volumes of individuals much faster than reliance on human agents,

while simultaneously reducing false positives by virtue of the greater differentiation and comparison techniques possible through mathematics-based computer software. Finally,

this evolution of micro-expression recognition from human agents to computerized processes also thereby substantially resolves the potential ethical concerns that have been raised in connection with the widespread use of facial recognition for law enforcement and counterterrorism purposes without unnecessarily violating the rights, privileges, and privacies of innocent individuals in the process.

References

Adams, S.H. "Communication Under Stress: Indicators of Veracity and Deception in Written Narratives" Ph.D. Dissertation Virginia Polytechnic Institute and State

University; (2002).

DePaulo, B.M., Kirkendol, S.E., Tang, J., and O'Brien, T.P. "The Motivational Impairment Effect in the Communication of Deception" Journal of Nonverbal Behavior, Vol. 12, No. 3: 177 -- 202; (1988).

DePaulo, B.M., Lindsay, J.J., Malone, B.E., Muhlenbruck, L., Charlton, K., and Cooper, H. "Cues to Deception" Psychological Bulletin, Vol. 129, No. 1: 74 -- 118; (2003).

Dershowitz, a. (2002). Shouting Fire: Civil Liberties in a Turbulent Age. New York: Little Brown & Co.

Ekman, P. "How to Spot a Terrorist on the Fly" New York Times Magazine, October

29, 2006: B03.

Ekman, P. "Darwin, Deception, and Facial Expression" New York Academy of Science

Annals, Vol. 1000: 205-221; (2003).

Ekman, P., and O'Sullivan, M. "Who can catch a liar?" American Psychologist, Vol. 46,

No. 9: 913-920; (1991).

Ekman, P., O'Sullivan, M., and Frank, M.G. "A few can catch a liar" Psychological

Science, Vol. 10, No. 3: 263 -- 266; (1999).

Frank, M.G., and Feeley, T.H. "To Catch a Liar: Challenges for Research in Lie

Detection Training" Journal of Applied Communication Research, Vol. 31: 58 -- 75;

(2003).

Granhag, P.A., and Stromwoll, L. (2005). The Detection of Deception in Forensic

Contexts. Cambridge, UK: Cambridge University Press.

DePaulo, B.M., Lindsay, J.J., Malone, B.E., Muhlenbruck, L., Charlton, K., and Cooper, H. "Cues to Deception" Psychological Bulletin Vol. 129, No.1: 74 -- 118; (2003).

Leach, a., Talwar, V., Lee, K., Bala, N., and Lindsay, R.C. "Intuitive' Lie Detection of Children's Deception by Law Enforcement Officials and University Students"

Law and Human Behavior Vol. 28, No. 6: 661-685; (2004).

Mann, S., Vrij, a., and Bull, R. "Suspects, Lies and Videotape: An Analysis of Authentic High-Stake Liars" Law and Human Behaviour, Vol. 26, No. 3: 365 -- 376; (2002).

Park, H.S., Levine, T.R., McCornack, S.A., Morrison, K.,…

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