Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)
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.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningSimilar Papers 제목 키워드 기반
Goal-Oriented Design for Ethical Machine Learning and NLP
The argument made in this paper is that to act ethically in machine learning and NLP requires focusing on goals. NLP projects are often classificatory systems that deal with human subjects, which means that goals from pe…
BIG-bench Machine LearningCorrigendum and addendum to: How Populist are Parties? Measuring Degrees of Populism in Party Manifestos Using Supervised Machine Learning
This paper is a corrigendum and addendum to the previously published article: 'How Populist are Parties? Measuring Degrees of Populism in Party Manifestos Using Supervised Machine Learning' (Political Analysis, 1-17. doi…
The Criminality From Face Illusion
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 succ…
Experimental DesignClaude 3.5 Sonnet Model Card Addendum
This addendum to our Claude 3 Model Card describes Claude 3.5 Sonnet, a new model which outperforms our previous most capable model, Claude 3 Opus, while operating faster and at a lower cost. Claude 3.5 Sonnet offers i…
Code GenerationMMR totalmodelMulti-task Language Understanding+2Discretizing Numerical Attributes: An Analysis of Human Perceptions
Machine learning (ML) has employed various discretization methods to partition numerical attributes into intervals. However, an effective discretization technique remains elusive in many ML applications, such as associat…
AttributeData Visualization