Non-Verbal Lies Flashcards
Introduction:
definition and intro
Deception can be defined as a successful or unsuccessful deliberate attempt, without forewarning, to create a belief in another which the communicator considers to be untrue. Popular opinion suggests telling a lie elicits nonverbal cues that are indicative of the lie (i.e. Pinocchio’s nose). Identifying nonverbal cues associated with lying only makes sense if there is a model that can explain the mechanism that elicits these cues.
Introduction:
outline the model and structure of the essay
According to Zuckerman et al., Multi-Factor Model (1981) the presence of three factors could influence cues to deception; Emotional reaction, Cognitive effort and Attempted behavioural control. Each of these factors may emphasize a different aspect of deception and lies may well feature all three factors. Nowadays, technology is used to measure emotional/physiological reactions using the polygraph and neurological reactions with electroencephalograms (EEG); and most recently, functional magnetic resonance imaging (fMRI). How good people are at detecting non-verbal deception will be further discussed using empirical evidence.
Polygraph
One of the suggested factors that could influence cues to deception proposed by the Multi-Factor Model is emotional reaction. Telling a lie is commonly associated with different emotions such as guilt, fear, delight which may may result in an increase in physiological arousal. Polygraph measures different physiological responses (heart rate/blood pressure, respiration & skin conductivity) and it plots response via an ink pen onto a piece of paper. The most commonly used method for detecting deception is based on the assumption that lies given by a person in response to critical questions posed during a polygraph examination will elicit an identifiable pattern of autonomic reactivity.
Polygraph:
Critics of this method
Critics of this method argue that a polygraph examination cannot detect lying because there is no evidence that lying produces a distinct physiological response. E.g. An honest person may be nervous when answering truthfully and dishonest may be non-anxious.
Polygraph:
Evidence study
In Patrick and Iacono’s (1991) study, criterion evidence was sought from polygraph office records and from independent police files for all 402 control question tests (CQTs) conducted during a 5-year period by federal police examiners. Based on blind scoring of the charts, the hit rate for criterion innocent subjects (65% of whom were verified by independent sources) was 55%; for guilty subjects (of whom only 2% were verified independently), the hit rate was 98%. Although the estimate for innocent subjects is reasonable, the estimate for the guilty subsample is not. Given these methodological precautions, the results of this study provide evidence for sampling bias (error due to the sample selection) as an important determinant of hit rates in field studies of the CQT. Thus, polygraph may not be the best technique for detecting deception.
EEG:
intro to cognitive effort
One technique, however, has been applied in an actual forensic situation and has drawn considerable media attention. According to the Multi-Factor Model, lying sometimes requires extra mental effort for example, liars must produce a credible verbal message and display credible nonverbal behaviour as well as, attend to the target to see whether they are still being believed, whilst keeping the dialogue going smoothly.
EEG:
evidence study
A technique named “brain fingerprinting” (Farwell & Donchin, 1991) measures cognitive effort during deception. It involves the application of the Guilty knowledge test (GKT) while using EEG as a measurement tool. The GKT is a multiple-choice test with items concerning knowledge that only a guilty subject could have. For example, “Was $500, $1,000, or $5,000 stolen?” If only a guilty suspect knows the correct answer, a larger physiological reaction to a correct choice would indicate deception. The signals picked up by the EEG, known as event related potentials (ERPs), can be measured on the scalp 300–500 ms after the subject is exposed to a stimulus; their precise origin is unknown, but they are associated with novelty and salience of incoming stimuli. Through this technique, Farwell claims to be able to tell whether a stimulus is familiar or unfamiliar to the subject. “Brain fingerprinting” is thus not really a liedetection technology. Thus far, it seems that we lack appropriate methods to reliably detect deception.
fMRI:
intro
The deception detection methods such as polygraph, rely solely on peripheral measures of anxiety thus, little is known about the brain mechanisms involved in generating lies. fMRI allows us to measure neural activation in specific areas of the brain, which offers a potentially valuable tool to detect lies as it is difficult to fake brain activation.
fMRI:
evidence study
For instance, Phan et al., (2005) conducted fMRI study to measure neural correlates of telling lies. Researchers used a novel real-time fMRI technology to simulate a polygraph experience in order to evoke performance anxiety about generating lies, and to determine the neural correlates of deception. The neural correlates of lying were examined in 14 adult volunteers while they performed a modified card version of the Guilty Knowledge Test (GKT), with the understanding that their brain activity was being monitored in real time by the investigators. Participants were instructed to attempt to generate lies that would not evoke changes in their brain activity.
fMRI:
evidence study- results + interpretation
The study found that subjects reported performance anxiety during the task. Additionally, deceptive responses were specifically associated with activation of the cortical frontal regions in the brain. These findings suggest the involvement of discrete regions of the frontal cortex during lying, and that the neural substrates responsible for cognitive control of behavior may also be engaged during deception. Indicating a possible new method for lie detection.
fMRI:
evidence study critique
However, neurotechnological means of lie detection suffer from many of the same weaknesses as conventional polygraphy. While monitoring brain activity directly, rather than monitoring peripheral responses such as skin conductance, may improve the measurement component of a lie-detection system, there is no assurance that changing the measurement component alone will result in improved overall performance for any particular application.
‘Devil’s advocate’
The empirical data supporting the idea of fMRI lie detectors is derived from a body of work still early in its development. Hence, when invited to play ‘Devil’s advocate’, the author has to critique a pivotal weakness within the current literature. Spence (2010) examined 16 peer-reviewed fMRI studies claiming to describe the neural correlates of lying. Most have demonstrated greater activation of prefrontal regions while participants lie relative to when they tell the truth. Most have failed to detect areas where truthfulness elicits specific activation (consistent with the view that truthfulness constitutes a ‘baseline’ in human cognition and communication; while lying requires something more). However, there is a great deal of variation between the findings described and there is an absence of replication by investigators oftheir ownfindings. Hence, basic issues of reliability need to be addressed before functional neuroimaging is applied to cases that matter in the ‘real world’.
Conclusion
fMRI lie detectors are no better than conventional methods at detecting lies, and suffer from the same pitfalls as the others. How good are we at detecting deception? Even with the advancement of neuroimaging technology, we are still not good at detecting deception.
