New research shows that understanding users' intentions—rather than simply increasing data volume—can improve the suggestions generated by YouTube's "black box" algorithms.

When opening a short video information app and swiping across the screen, users expect to find content that is 'just what they want to see' — but the reality is often different: during commutes, users ...

Transparency does not require companies to disclose complex source codes, but rather to clearly and honestly explain to users ...

All you do is tap it off, and that's it. Now, your playlist will only play the music that you add to it. The order of content will be exactly what you set on it. And when the last track has finished ...

Algorithmic recommendation systems on social media sites like YouTube, Facebook and Twitter have shouldered much of the blame for the spread of misinformation, propaganda, hate speech, conspiracy ...

Gonçalo Perdigão, entrepreneur, consultant and author of Building Creative Machines, explores how generative A.I. is recoding the economics of creativity. Drawing on his cross-sector experience in ...

Back in June, Netflix’s VP of Product Innovation Carlos A. Gomez-Uribe and Chief Product Officer Neil Hunt co-published a paper entitled, “The Netflix Recommender System: Algorithms, Business Value, ...

Switch on your streaming service of choice or open the website for your preferred department store and a recommendation system is sure to kick in. “You liked this TV series, so we think you’ll like ...

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 ...

You probably didn't notice it, but on one day in December, your Netflix account got a lot more personal. That was the day that Netflix flipped the switch on its new global recommendation system.