Truth is not absolute with AI deception technology

" Deception analysis, which utilizes algorithms to classify facial micro expressions (there are seven universal micro expressions: disgust, anger, fear, sadness, happiness, surprise and contempt), coupled with vocal patterns to indicate an individual’s truthfulness, is attempting to find its way into the criminal justice process. Deception systems currently being tested by the Department of Homeland Security try to detect changes in a suspect’s eye movement, voice and body posture to assess the individual’s likelihood of acting deceptively.

However, as with polygraph examinations — commonly known as “lie detector tests” — results from these deception analyses can be skewed by various physiological and psychological factors. AI-based deception systems face a similar criticism: To date, there is no scientific evidence of a consistent relationship between an individual’s internal mental state, his or her intent, and any kind of external inducements. As a result, models and algorithms designed to predict or identify deceptiveness may be deemed unreliable."

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