Detection of deception researchers needs to collaborate with experienced practitioners

Catching a Liar Through Facial Expression of Fear

High stakes can be stressful whether one is telling the truth or lying. However, liars can feel extra fear from worrying to be discovered than truth-tellers, and according to the "leakage theory," the fear is almost impossible to be repressed. Therefore, we assumed that analyzing the facial expression of fear could reveal deceits. Detecting and analyzing the subtle leaked fear facial expressions is a challenging task for laypeople. It is, however, a relatively easy job for computer vision and machine learning. To test the hypothesis, we analyzed video clips from a game show "The moment of truth" by using OpenFace (for outputting the Action Units (AUs) of fear and face landmarks) and WEKA (for classifying the video clips in which the players were lying or telling the truth). The results showed that some algorithms achieved an accuracy of >80% merely using AUs of fear. Besides, the total duration of AU20 of fear was found to be shorter under the lying condition than that from the truth-telling condition. Further analysis found that the reason for a shorter duration in the lying condition was that the time window from peak to offset of AU20 under the lying condition was less than that under the truth-telling condition. The results also showed that facial movements around the eyes were more asymmetrical when people are telling lies. All the results suggested that facial clues can be used to detect deception, and fear could be a cue for distinguishing liars from truth-tellers.

Unraveling the Misconception About Deception and Nervous Behavior

In this article, we attempt to unravel the misconception about deception and nervous behavior. First we will cite research demonstrating that observers believe lie tellers display more nervous behaviors than truth tellers; that observers pay attention to nervous behaviors when they attempt to detect deception; and that lie tellers actually feel more nervous than truth tellers. This is all in alignment with a lie detection approach based on spotting nervous behaviors. We then will argue that the next, vital, step is missing: Research has found that lie tellers generally do not display more than truth tellers the nervous behaviors laypersons and professionals appear to focus on. If observers pay attention to nervous behaviors but lie tellers do not come across as being nervous, lie detection performance is expected to be poor. Research has supported this claim. We finally discuss ideas for research into lie detection based on non-verbal behaviors.

Cumulative Disadvantage: A Psychological Framework for Understanding How Innocence Can Lead to Confession, Wrongful Conviction, and Beyond

False confessions are a contributing factor in almost 30% of DNA exonerations in the United States. Similar problems have been documented all over the world. We present a novel framework to highlight the processes through which innocent people, once misidentified as suspects, experience cumulative disadvantages that culminate in pernicious consequences. The cumulative-disadvantage framework details how the innocent suspect's naivete and the interrogator's presumption of guilt trigger a process that can lead to false confession, the aftereffects of which spread to corrupt evidence gathering, bias forensic analysis, and virtually ensure wrongful convictions at trial or through pressured false guilty pleas. The framework integrates nascent research underscoring the enduring effects of the accumulated disadvantages postconviction and even after exoneration. We synthesize findings from psychological science, corroborating naturalistic evidence, and relevant legal precedents to explain how an innocent suspect's disadvantages can accumulate through the actions of law enforcement, forensic examiners, prosecutors, defense attorneys, judges, juries, and appeals courts. We conclude with prescribed research directions that can lead to empirically driven reforms to address the gestalt of the multistage process.