Archives October 1, 2019

YouTube is Experimenting With Ways To Make Its Algorithm Even More Addictive

While YouTube has publicly said that it’s working on addressing problems that are making its website ever so addictive to users, a new paper from Google, which owns YouTube, seems to tell a different story.

It proposes an update to the platform’s algorithm that is meant to recommend even more targeted content to users in the interest of increasing engagement. Here’s how YouTube’s recommendation system currently works. To populate the recommended-videos sidebar, it first compiles a shortlist of several hundred videos by finding ones that match the topic and other features of the one you are watching. Then it ranks the list according to the user’s preferences, which it learns by feeding all your clicks, likes, and other interactions into a machine-learning algorithm. Among the proposed updates, the researchers specifically target a problem they identify as “implicit bias.” It refers to the way recommendations themselves can affect user behavior, making it hard to decipher whether you clicked on a video because you liked it or because it was highly recommended. The effect is that over time, the system can push users further and further away from the videos they actually want to watch.

To reduce this bias, the researchers suggest a tweak to the algorithm: each time a user clicks on a video, it also factors in the video’s rank in the recommendation sidebar. Videos that are near the top of the sidebar are given less weight when fed into the machine-learning algorithm; videos deep down in the ranking, which require a user to scroll, are given more. When the researchers tested the changes live on YouTube, they found significantly more user engagement. Though the paper doesn’t say whether the new system will be deployed permanently, Guillaume Chaslot, an ex-YouTube engineer who now runs AlgoTransparency.org, said he was “pretty confident” that it would happen relatively quickly.

Optic Nerve: millions of Yahoo webcam images intercepted by GCHQ

Optic Nerve is a mass surveillance programme run by the British signals intelligence agency Government Communications Headquarters (GCHQ), with help from the US National Security Agency, that surreptitiously collects private webcam still images from users while they are using a Yahoo! webcam application. As an example of the scale, in one 6-month period, the programme is reported to have collected images from 1.8 million Yahoo! user accounts globally. The programme was first reported on in the media in February 2014, from documents leaked by the former National Security Agency contractor Edward Snowden, but dates back to a prototype started in 2008, and was still active in at least 2012.[1][2]

The leaked documents describe the users under surveillance as “unselected”, meaning that data was collected indiscriminately in bulk from users regardless of whether they were an intelligence target or not. The vast majority of affected users would have been completely innocent of any crime or suspicion of a crime.