These kinds of adversarial examples are considered less threatening, because they don’t closely resemble the real world, where an attacker wouldn’t have access to a proprietary algorithm. For ...

Last month, Twitter users uncovered a disturbing example of bias on the platform: An image-detection algorithm designed to optimize photo previews was cropping out Black faces in favor of white ones.

Examples abound of AI systems behaving badly. Last year, Amazon was forced to ditch a hiring algorithm that was found to be gender biased; Google was left red-faced after the autocomplete ...

In addition, algorithms learn how to calculate the similarity of photos by practicing on pre-existing training sets of faces. So even if the features on which an algorithm focuses are race ...

In an article on Domingos’ Master Algorithm, Slate’s David Auerbach notes that “even within computer science, machine learning is notably opaque.” But it’s also increasingly central to ...

Bias is an age-old problem for AI algorithms, in part because they are often trained on data sets that are skewed or not fully representative of the groups they serve. Photo: ERIC GAILLARD/REUTERS ...