Questions about racism for online dating
This is an example of the more general problem of image understanding: a computer program analyzes a photo, makes a determination about the photo, then emits some kind of meaningful judgement (say, “the person in this photo is likely between the ages of 18 and 23”).The relationship between the photo and the response is determined by a set of parameters, which are tuned during a learning phase — hence “machine learning”.This is the same as the rationale for giving students a midterm exam with questions they haven’t seen before, rather than just reusing examples that have been worked through in class.Every machine learning system has parameters — or there is nothing to learn. Increasing the number of parameters can allow a system to learn more complex relationships, making for a more powerful learner and, if the relationships between input and output are complex, a lower error rate.Whether intentional or not, this “laundering” of human prejudice through computer algorithms can make those biases appear to be justified objectively.A recent case in point is Xiaolin Wu and Xi Zhang’s paper, “Automated Inference on Criminality Using Face Images”, submitted to ar Xiv (a popular online repository for physics and machine learning researchers) in November 2016.” In this way, by playing a game of Marco Polo with parameters, a computer can optimize itself to learn the task.
The laborer, Giuseppe Villella, was reportedly convicted of being a (bandit), at a time when brigandage — banditry and state insurrection — was seen as endemic.Villella died in prison in Pavia, northern Italy, in 1864.Villella’s death led to the birth of modern criminology.The practice of using people’s outer appearance to infer inner character is called .
While today it is understood to be pseudoscience, the folk belief that there are inferior “types” of people, identifiable by their facial features and body measurements, has at various times been codified into country-wide law, providing a basis to acquire land, block immigration, justify slavery, and permit genocide.Many of us in the research community found Wu and Zhang’s analysis deeply problematic, both ethically and scientifically. However, the use of modern machine learning (which is both powerful and, to many, mysterious) can lend these old claims new credibility.