You might be familiar with the terms "seggs" and "unalive" if you've spent time on social media platforms. They're a part of ...

Detection often starts with cues users pick up during interactions, unexpected outcomes, repetitive patterns, or ...

Another possibility is to present a number of non-machine-learned algorithm examples and incorporate the people’s responses to those in the survey as well.

The linguist and author of “Algospeak” traces how content moderation is breeding a whole new way of speaking — and what it means for the future of language.

For example, algorithms used in facial recognition technology have in the past shown higher identification rates for men than for women, and for individuals of non-white origin than for whites.

Such algorithms are also useful in helping leaders make decisions involving trade-offs. They can present non-obvious choices and opportunities. Other machine learning algorithms examples would ...

I love both of these examples, because I love the idea that we can take our own democratic action to make the world a bit less complicated. Alas, it is not that simple.

A health care algorithm makes black patients substantially less likely than their white counterparts to receive important medical treatment. The major flaw affects millions of patients, and was ...

A study published Thursday in Science has found that a health care risk-prediction algorithm, a major example of tools used on more than 200 million people in the U.S., demonstrated racial bias ...