The 'Criminality from Face' Illusion

被引：10

作者：

Bowyer, Kevin W. ^{[1
]}

King, Michael C. ^{[2
]}

Scheirer, Walter J. ^{[1
]}

Vangara, Kushal ^{[2
]}

机构：

[1] Department of Computer Science and Engineering, University of Notre Dame, Notre Dame,IN,46556, United States

[2] Department of Computer Science, Florida Institute of Technology, Melbourne,FL,32901, United States

来源：

IEEE Transactions on Technology and Society | 2020年 / 1卷 / 04期

关键词：

Machine learning - Forecasting - Image analysis;

D O I：

10.1109/TTS.2020.3032321

中图分类号：

学科分类号：

摘要：

This article contains examples of offensive and abusive language as a necessary part of illustrating its research findings. 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. © 2020 IEEE.

引用

页码：175 / 183