Join us on July 30 in NYC for a breakfast & panel
Facebook’s facial recognition capabilities are about to get a little creepier
If you’re the type of person who ducks out of photos to avoid being tagged, Facebook is on to you. The company’s artificial intelligence lab is developing an experimental algorithm that detects users’ identities based on body shapes, hair and clothes instead of faces.
The idea mimics humans ability to recognize people in the same way we use clues without seeing faces. In an interview with the New Scientist, Yann LeCun, Facebook’s head of A.I. gave the example of Mark Zuckerberg who is identified “very easily, because he always wears a gray T-shirt.”
Facebook uploaded 40,000 photos from Flickr, some of them showing people’s faces and others partially obscured, and ran them through a “sophisticated neural network.” The algorithm was able to detect people’s identities 83 percent of the time.
The intent isn’t to be creepy, claims LeCun. The tool could be used to alert people that pictures of them have been uploaded to the Internet without their knowledge. More practically, the tool will be used to ease the burden of tagging multiple photos at once.
Still, Facebook might have trouble convincing users that this yet-to-be-released tool isn’t invading people’s privacy. It’s already embroiled in controversy in Europe over its facial recognition services: European regulators have blocked the release of Facebook’s new photo-sharing app Moments over its facial recognition abilities, which the company has nailed down to human-like accuracy.
So, if you’re trying to avoid Facebook, perhaps the best solution for now is to never leave the house.
Image courtesy of YouTube.
More in Media
Publisher ad supply fell by up to 40% in Q2 as AI search choked the open web
Publisher ad supply fell by up to 40% in Q2 of 2026 as AI‑era, zero‑click search choked the flow of traffic to news and other open‑web sites, per U.S. and U.K. benchmarking data from Ozone, shared exclusively with Digiday.
Inside the newsroom push to turn print reporters into video talent
As reporter-led video becomes a priority, publishers are investing in newsroom training to help journalists deepen audience relationships.
WTF is SPUR’s publisher-run Content Telemetry Framework?
SPUR is publisher‑run and fixated on one thing: turning AI’s use of their content from opaque scraping into a transparent, usage‑based licensing system they control.