If were to address ourselves as to the nature of “true”, we are no doubt inclined to say that it’s the antonym of “false”. And “false” is associated with telling a lie, something that doesn’t fall under the incidence of truth. How can we figure out if something is lying or telling the truth? Shenanigans depart with a novel lie detector which is capable of accurately determining if someone suffers from Pinnochio’s disorder.
More traditional means of detecting if someone is lying or not are based on observing certain subtle gestures. Sweaty palms, avoiding eye-contact, these were all considered signs that the person in front of you might not be actually telling the truth. But it would seem that these points of view are all but obsolete, if not erroneous.
According to several new behavioral study, it would seem that people who either hiding something or have an inclination towards not speaking truthfully, have other means of expressions. For example, certain studies have revealed that liars will not avoid eye contact. In fact, they will look straight into your eyes when they’ll make their statements. Moreover, it would seem that a liar will be far more expressive than a person who is telling the truth. These facial expressions include grinning, nodding and scowling. It has been also determined that such a person is waving his hands more than other.
Now, in terms of lie detection, specialists said that it is easier to look at the simple body language in order to see if the person in front of you is telling the truth or not. But, taking the technological high ground, several researchers from the University of Michigan have come up with a non-intrusive way to detect a liar.
Using a highly advanced computer program, Rada Mihalcea, a professor from the University of Michigan has devised a lie detector that is actually capable of rooting out a liar in 75 percent of the cases. For the program to yield results, Mihalcea has fed it with approximately 120 real-life examples of people lying in court. These examples were supplied by The Innocence Project.
The professor said that the video examples were necessary because they could not duplicate this effect in lab conditions. Moreover, the professor stated that people could be convinced to lie if they receive a certain incentive, but the reaction wouldn’t be the same. So, by feeding the machine with video examples and providing it with a learning algorithm, the professor, and her team managed to develop a lie detector that is capable of ascertaining if a person is lying or not.
And to top it all up, the team actually confronted the machine with a human. They were both tasked with determining if a person tells the truth or is lying. The human lie detector got it right in 50 percent of the cases while the machine managed to uncover more than 75 percent cases.