Neural network identifies criminals by facial features

A study from Shanghai Jiao Tong University found that a machine could be trained to identify criminals based on their facial features, raising ethical concerns regarding uses of AI. The researchers used 1856 photographs of real people, half of whom were criminals. They found that via supervised machine learning, the system was able to correctly separate criminals from non-criminals based on photographs alone. They divided the sample and used 90% of the photographs to train the machine, then used the remaining 10% for testing. Results of the testing showed a very high (above 80%) accuracy across all identifiers. ‘Figure 10. (a) and (b) are ”average” faces for criminals and noncriminals generated by averaging of eigenface representations ; (c)and (d) are ”average” faces for criminals and non-criminals generated by averaging of…


Link to Full Article: Neural network identifies criminals by facial features

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