Up to now, machine-driven image recognition hasn't just been a science-fiction artifact brought to life, it's been a practical upgrade. Programs that can identify objects and even people help us learn about the world around us - or at least save time when labeling photos.
But Facebook's bout of bad publicity over a facial-recognition feature called Suggested Tags suggests how we can wind up on the other end of the image sensor. In the nightmarish future some critics of the social network now evoke, our mug shots become yet another searchable, indexable item on the Internet.
An op-ed on the Guardian newspaper's web site argued that Suggested Tags puts us well on the primrose path to the zero-privacy future of the film Minority Report, with "corporations bombarding passersby with holographic advertisements which crawled up the sides of walls, addressing them by name."
A post on PC World's site called this feature "downright creepy": "imagine, a world in which someone can simply take a photo of you on the street, in a crowd, or with a telephoto lens, and discover everything about you on the internet."
Ugh. But let's rewind first.
Back in December, Facebookannounced in a blog post that it would suggest tags for new photos. If it saw a Facebook friend in a picture whom you or others had tagged in earlier shots, it wouldsuggest that person's nameand invite you to keep, correct or drop that label.
Suggested Tags works like the facial-recognition options that have been in photo software since at least 2005 (when a since-shuttered Bay Area startup named Ojos launched one such application) and now constitute major features in Google's Picasa, Apple's iPhoto and Microsoft's Windows Live Photo Gallery. In all of these systems, once you identify people in enough photos, the software will take it from there and try to find them in other pictures.