A canonical problem in computer science is to find the shortest route to every point in a network. A new approach beats the ...

Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling ...

Deep-learning algorithms suffer from a fundamental problem: They can adopt unwanted biases from the data on which they're trained. In healthcare, this can lead to bad diagnoses and care ...

Stanford found itself in hot water last week after deploying a faulty Covid-19 vaccine distribution algorithm. But the fiasco offers a cautionary tale that extends far beyond Stanford’s own doors — ...

That question in the headline was the challenge posed by a group of open knowledge junkies in Germany who wanted to understand how a person’s Schufa was calculated. Schufa is a credit bureau that ...

Artificial intelligence has given us algorithms capable of recognizing faces, diagnosing disease, and of course, crushing computer games. But even the smartest algorithms can sometimes behave in ...

Over the past few months, we’ve documented how the vast majority of AI’s applications today are based on the category of algorithms known as deep learning, and how deep-learning algorithms find ...

As organizations increasingly replace human decision-making with algorithms, they may assume these computer programs lack our biases. But algorithms still reflect the real world, which means they can ...