Engineering researchers of Dartmouth College have developed a new approach for detecting a speaker’s intent to mislead. Which could be developed to extract opinions from fake news from other uses.
It was published recently as part of a paper in the Journal of Experimental & Theoretical Artificial Intelligence.
The researchers also developed a unique approach and resulting algorithm that can even tell deception apart from all benign communications by retrieving the universal features of deceptive reasoning.
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However, the framework is only currently limited by the amount of data needed to measure
a speaker’s deviation from their past arguments.
Santos believes that the framework could be further developed to help readers distinguish and also closely examine the intent of fake news, allowing the reader to determine if a reasonable, logical argument is used or if the opinion is playing a strong role.
Santos hopes to examine the flow effect of misinformation, including its impacts in further studies.
The researchers use the popular 2001 film Ocean’s Eleven in the study to illustrate how the framework could be used to examine a deceiver’s arguments, which in reality may go against his true beliefs, resulting in a false final expectation.
For example, a group of thieves breaks into a bank vault while also revealing to the owner that he is being robbed in order to negotiate in the movie.
The thieves even supply the owner with false information, namely that they will only take half of the money if the owner doesn’t call the police.
However, the thieves expected the owner to call the police, which he does, so the thieves then disguise themselves as police to steal the entire of the vault contents.
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This shows how the thieves were able to deceive the owner and expect his actions due to the fact that the thieves and owner had different information and therefore perceived the scene differently.
But in popular culture, both verbal and non-verbal behaviors such as facial expressions are often used to determine if someone is lying or not, but those cues are not always reliable.