# Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)

arXiv: https://arxiv.org/abs/1611.04135 · HTML: https://mlsanity.com/paper/1611.04135/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2016.

## Built on by (most cited first, 14 of 14)

- [Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals](https://mlsanity.com/paper/2210.01790/) (2022)
- [A Prompt Array Keeps the Bias Away: Debiasing Vision-Language Models with Adversarial Learning](https://mlsanity.com/paper/2203.11933/) (2022)
- [Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning](https://mlsanity.com/paper/2202.05338/) (2022)
- [A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms](https://mlsanity.com/paper/2206.14983/) (2022)
- [About Face: A Survey of Facial Recognition Evaluation](https://mlsanity.com/paper/2102.00813/) (2021)
- ["Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?](https://mlsanity.com/paper/2107.02278/) (2021)
- [Ethical Considerations for Responsible Data Curation](https://mlsanity.com/paper/2302.03629/) (2023)
- [Beyond transparency: computational reliabilism as an externalist epistemology of algorithms](https://mlsanity.com/paper/2502.20402/) (2025)
- [Pre-Trained Language Transformers are Universal Image Classifiers](https://mlsanity.com/paper/2201.10182/) (2022)
- [Visual Privacy: Current and Emerging Regulations Around Unconsented Video Analytics in Retail](https://mlsanity.com/paper/2302.12935/) (2023)
- [Deep Learning and Ethics](https://mlsanity.com/paper/2305.15239/) (2023)
- [Facing Identity: The Formation and Performance of Identity via Face-Based Artificial Intelligence Technologies](https://mlsanity.com/paper/2410.12148/) (2024)
- [The Return of Pseudosciences in Artificial Intelligence: Have Machine Learning and Deep Learning Forgotten Lessons from Statistics and History?](https://mlsanity.com/paper/2411.18656/) (2024)
- [Fuck the Algorithm: Conceptual Issues in Algorithmic Bias](https://mlsanity.com/paper/2505.13509/) (2025)

## Abstract (arXiv)

In November 2016 we submitted to arXiv our paper "Automated Inference on Criminality Using Face Images". It generated a great deal of discussions in the Internet and some media outlets. Our work is only intended for pure academic discussions; how it has become a media consumption is a total surprise to us. Although in agreement with our critics on the need and importance of policing AI research for the general good of the society, we are deeply baffled by the ways some of them mispresented our work, in particular the motive and objective of our research.