학술논문

The “Criminality From Face” Illusion
Document Type
Periodical
Source
IEEE Transactions on Technology and Society IEEE Trans. Technol. Soc. Technology and Society, IEEE Transactions on. 1(4):175-183 Dec, 2020
Subject
Engineering Profession
General Topics for Engineers
Artificial intelligence
Ethics
Prediction algorithms
Neural networks
NIST
Face recognition
Computer vision
Machine learning
Artificial intelligence (AI)
computer vision
criminality prediction
facial analytics
machine learning
technology ethics
Language
ISSN
2637-6415
Abstract
The automatic analysis of face images can generate predictions about a person’s gender, age, race, facial expression, body mass index, and various other indices and conditions. A few recent publications have claimed success in analyzing an image of a person’s face in order to predict the person’s status as Criminal/Noncriminal. Predicting “criminality from face” may initially seem similar to other facial analytics, but we argue that attempts to create a criminality-from-face algorithm are necessarily doomed to fail, that apparently promising experimental results in recent publications are an illusion resulting from inadequate experimental design, and that there is potentially a large social cost to belief in the criminality from face illusion.