When it comes to recommendation systems, everybody's looking to increase accuracy: the Netflix Prize was awarded last July for an algorithm that improved the accuracy of the service's ...

The issues and pitfalls presented by social algorithms are well-known and have been well-documented. So, really, what are we going to do about it?

In a newly published preprint study, researchers propose a "fairer" product recommendation algorithm that's ostensibly less biased against certain shoppers.

The unveiling of the algorithm comes after an unknown user posted portions of Twitter's source code to GitHub.

YouTube’s recommendations algorithm can lead you down some very weird rabbit holes, suggesting videos that feel weirdly personal and off-target at the same time. Today, Mozilla will introduce a ...

Companies, nonprofit organizations, and governments design algorithms to learn and predict user preferences. They embed these algorithms in recommendation systems that help consumers make choices ...

Recommendation algorithms on sites like Facebook and YouTube can send users down rabbit holes, spread falsehoods, and foster conspiracy theories.

For the subset of users who understand the impact of the algorithms enough to try to appease them, the answer, then, is yes—that makes one boring; but the “that” is not the users’ predictability but ...

Before Netflix got into the business of producing its own programming, it spent a lot of time emphasizing its recommendation software, the algorithms that would learn your taste and suggest the ...