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According to Hyman (1989) deception implies that an agent acts or speaks so as to induce a false belief in a target or victim

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Introduction

According to Hyman (1989) deception implies that an agent acts or speaks so as to induce a false belief in a target or victim. Deception can occur in everyday life. Whether it is telling someone they look nice or not telling them that they look fat. This is an important process for forming relationships and general social interaction. However, although this is useful for social interaction, it is a serious problem in other areas. Deception can be a problem when people actively deceive in job applications, giving evidence and in court. Being able to detect whether a person is lying or not in a criminal situation in very relevant for the legal system to work effectively. Many people claim to be able to tell whether someone is lying or not by particular signs. However research shows that this may not be the case. In the earliest research into deception, Eckman (1969) suggested that deception could be detected by leakage cues. It was suggested that when these 'micro-expressions' occur, the person reveals their true feelings. Further studies looked into verbal and non verbal cues. Some examples of verbal cues include higher pitch voice, speech hesitations and taking longer to answer questions. Some examples of non-verbal cues include twitching, pupil dilation, avoiding eye contact and increased sweating. However, Ekman (1974) later stated that no body movement, facial expression or voice change is an indisputable sign of deceit. ...read more.

Middle

However there are many problems with the system studies show it is not infallible. Firstly, it has been found by many studies that although the CQT is fairly accurate at detecting deception it cannot detect truthfulness in an innocent person better than chance (Kleinmuntz & Szucho, 1984b). This suggests that the odds may be stacked again the innocent person. Additionally there may problems with the people who actually analyse the information. An earlier study by Szucho and Kleinmuntz (1981) showed that the best interpreter classified 18% of truthful subjects as untruthful. The worst interpreter incorrectly classified 55% of truthful subjects as untruthful. This has serious implications as it provides further evidence that innocent people may be convicted of crimes they did not commit. Research has shown that the rate of false positive scores is consistently higher than of false negative results and overall accuracy of the polygraph falls to 80-90% at best. Additionally, according to Faigman, Fienberg and Stern (2003), over-confidence in polygraph accuracy may lead to jurors believing it as scientific fact if admitted as evidence. Fortunately the US courts do not have to allow polygraph results to be admitted as evidence. However one occasion when it was admitted showed a further problem with this deception detector. A convicted criminal called Floyd 'Buzz' Fay was wrongly convicted using the polygraph on the basis of a failed polygraph and subsequently trained fellow inmates to cheat the tool. ...read more.

Conclusion

However, this deception detection technique is also not infallible. It does not actually show that the person is lying; it only shows that they recognise the image. This could mean that they may have seen an item (murder weapon) but not have any conscious recollection of it. Furthermore, the National Research Council (2003) stated that due to the limited amount of study on accuracy, the use of the P300 in lie detection may have similar levels of accuracy to the polygraph. However, this is not the only brain scanning technique available at the moment. Work by Kosslyn et. al (2003) has shown that by using fMRIs specific areas of the brain activate when people are telling the truth or a lie. Furthermore, the study suggests that different regions activate depending on the type of lie. Recently in the news, it was reported that Dr. Jennifer Vendemia has received a $5 million grant from the US defence department for research into monitoring brainwaves to detect lying. Vendemia states that this system could have accuracy between 94-100% (Summers, 2005). Therefore, it seems the future for lie detector machines looks promising. Overall, both the human and non-human measures of lie detection have their strength and weaknesses. Although neither claims to be 100% accurate at present, both seem show signs of a future where lie detection is more accurate and less fallible. As seen in many areas of psychology, a collaboration of these techniques could be the most promising opportunity. ...read more.

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