The #10yearchallenge is the new trend on Facebook. Users are flooding their News Feed with photos from 2009 and 2019 to show how much they've changed in the past few years. It sure sounds fun. But could this new challenge be just another tool that trains Facebook's machine learning algorithms to recognize your facial features?
Technology expert Kate O'Neil has launched a new case into whether the #10yearchallenge is actually an elaborate scheme to gather your age-related characteristics and data more generally.
“Imagine you want to train a facial recognition algorithm on age-related features, and more specifically age progression (e.g., what a person is likely to look like as they age). Ideally, you would want a broad dataset with images of many people. It would also help a lot if you knew that a certain number of years had passed between the images taken, say 10 years,” he wrote in a post on Wired.
He also acknowledged that user data, especially past and present profile photos, is already available on the social network. But a side-by-side comparative analysis of photos makes it much easier for ML algorithms to learn about users' facial data.
He also points out that photos posted by a user on the social networking platform may be older or newer, as Facebook does not include EXIF data (photo source data). A movement involving a large number of users, however, makes things easier.
Facebook denied having any involvement with the #10yearchallenge.
“The 10yearchallenge is a user-created challenge that started on its own, without our involvement. It’s proof that people are still having fun on Facebook, and that’s all,” the company said in a tweet.
Despite Facebook's denial, many users have extended their support to Kate's theory. Furthermore, Facebook's record on maintaining user privacy has already been widely questioned, after several security breaches occurred one after the other, as well as data collection by third-party companies such as the Cambridge Analytica scandal.
