Could the #10YearChallenge Really Improve Facial Recognition Tech?

Over the past week, the #2009vs2019 meme challenge, alternately known as the #10yearchallenge and #HowHardDidAgeHitYou, has become the latest social media trend ripe for think piece fodder. Me 10 years ago: probably would have played along with the profile picture aging meme going around on Facebook and Instagram Me now: ponders how all this data could be mined to train facial recognition algorithms on age progression and age recognition — Kate O'Neill January 12, 2019 The post generated enough buzz and discussion on Twitter that O’Neill expanded it into an article in Wired, in which she argued that Facebook or another data-hungry entity could exploit the meme to train facial recognition algorithms to better handle age-related characteristics and age progression predictions. Writing in New York magazine, Max Read argues, “If you’re one of the 350 million people or so who’s been on Facebook since 2009—or if you’ve uploaded older photos to the platform after joining—the world’s biggest social network already knows what you look like now, in the past, and probably in the future, too.” Indeed, Facebook automatically collects data from pictures that users upload for its facial recognition features. Read further posits that if Facebook were to engineer a meme trend like #2009vs2019, the goal would more likely be to boost its stagnant user engagement numbers, rather than to improve its facial recognition software. Alexis C. Madrigal writes in the Atlantic, however, “Facebook isn’t building an age-progression machine-learning system; it almost certainly already has one.” The idea, again, is that having people post age-separated photos in this limited meme context really isn’t going to augment what’s already possible with Facebook’s massive trove of user pictures.