The Criminality From Face Illusion
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Abstract (arXiv)
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 / Non-Criminal. 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.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jun 2020.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 2.
8 papers.
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- 2026Dataset Biases and Shortcut Learning in Motion-Based AI-Generated Video Detectioncited by 1
- 2026Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Setcited by 0
- 2026Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Set1 Sep 2026
- 2026Dataset Biases and Shortcut Learning in Motion-Based AI-Generated Video Detection1 Jul 2026
- 2025Reasoning LLMs for User-Aware Multimodal Conversational Agents2 Apr 2025
- 2023Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence4 Dec 2023
- 2022Algorithmic Fairness in Business Analytics: Directions for Research and Practice22 Jul 2022
- 2021AI and Blackness: Towards moving beyond bias and representation5 Nov 2021
- 2021A Survey on Bias in Visual Datasets16 Jul 2021
- 2021Hidden Technical Debts for Fair Machine Learning in Financial Services18 Mar 2021