10yearchallenge is the new rage on Facebook. Users are flooding the NewsFeed with photos from 2009 and 2019 to show how they’ve changed over the years. Sounds all fun right? But is the viral challenge just another tool to train Facebook’s machine learning algorithms about your facial data, already a controversial feature on the social networking platform?
Technology author Kate O’Neil has stirred a new debate whether #10yearchallenge is an elaborate plan to gather your age-related characteristics and face data.
“Imagine that you wanted to train a facial recognition algorithm on age-related characteristics and, more specifically, on age progression (e.g., how people are likely to look as they get older). Ideally, you’d want a broad and rigorous dataset with lots of people’s pictures. It would help if you knew they were taken a fixed number of years apart—say, 10 years,” she wrote in a post in Wired.
She also acknowledged that user data, especially profile photos from the past and current, is already available on the social network. But a comparative side-by-side photo analysis makes it a lot easier for ML algorithms to learn about users’ facial data.
She also pointed out that photos posted by user on the social networking platform may be older or new as Facebook does not include EXIF data (photo’s source data). A crowd-sourced movement, however, makes things easier.
Facebook has denied its involvement in the ongoing #10yearchallenge.
“The 10 year challenge is a user-generated meme that started on its own, without our involvement. It’s evidence of the fun people have on Facebook, and that’s it,” said the company in a tweet.
Despite Facebook’s denial, a lot of users have extended support to Kate’s theory. Moreover, Facebook’s record in keeping users’ privacy intact has already come under wide scanner with back-to-back security breaches as well as data harvesting by third-party companies such as Cambridge Analytica.