A group of Harrisburg University professors and a Ph.D. student have developed automated computer facial recognition software capable of predicting whether someone is likely to become a criminal.
With 80 percent accuracy and with no racial bias, the software can predict if someone is a criminal based solely on a picture of their face. The software is intended to help law enforcement prevent crime.
Ph.D. student and NYPD veteran Jonathan W. Korn, Professor Nathaniel J.S. Ashby, and Prof. Roozbeh Sadeghian describe their research in "A Deep Neural Network Model to Predict Criminality Using Image Processing."
"We already know machine learning techniques can outperform humans on a variety of tasks related to facial recognition and emotion detection," Sadeghian says. "This research indicates just how powerful these tools are by showing they can extract minute features in an image that are highly predictive of criminality."
The team's research will appear in a future book series from Springer, entitled "Transactions on Computational Science & Computational Intelligence."
"By automating the identification of potential threats without bias, our aim is to produce tools for crime prevention, law enforcement, and military applications that are less impacted by implicit biases and emotional responses," Ashby says. "Our next step is finding strategic partners to advance this mission."
"Crime is one of the most prominent issues in modern society. Even with the current advancements in policing, criminal activities continue to plague communities," Korn says. "The development of machines that are capable of performing cognitive tasks, such as identifying the criminality of person from their facial image, will enable a significant advantage for law enforcement agencies and other intelligence agencies to prevent crime from occurring in their designated areas."
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