We are only a few weeks into the new year and it didn’t take long to get the first viral meme in the #10YearChallenge. The premise behind the meme is simple: You post a picture of yourself in 2009 alongside a current picture in 2019.
A lot of people got in on the side-by-side comparisons from celebrities to environmental activists to Mariah Carey, for whom time is not a concept. But while people were busy digging up old photos of themselves, others raised concerns about the #10YearChallenge, including the data-gathering implications of the meme.
The #10YearChallenge is Not a Data-Gathering Exercise…We Think
The first person to raise the alarm was author and speaker Kate O’Neill. In a viral tweet, O’Neill hinted that the #10YearChallenge could be used as a tool to improve facial recognition algorithms.
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 (@kateo) January 12, 2019
O’Neill later penned a column for Wired where she added color to her tweet. In reply to those who responded that the meme is harmless from a data standpoint since Facebook already has its users photos, O’Neill put forth that the specific pictures posted by a user could make it easier for a facial recognition algorithm to identify and replicate accurate age progression. By participating in the meme, we are effectively doing a lot of work for an algorithm by providing it with pictures, their exact contexts, and a set period of time between photos.
O’Neill also went on to suggest that facial recognition algorithms could be used for benign and risky means in equal measure. For example, she points out that facial recognition technology helped police locate over 3,000 missing children last year in New Delhi. She also gives the example of advertisers using facial recognition to target specific demographics.
But while your face could be scanned to purchase new socks or whatever, there is also the case of facial recognition technology being used by law enforcement and corporations to profile individuals. Just recently, Amazon shareholders urged the company to cease selling its facial recognition tech, Rekognition, to law enforcement agencies citing privacy concerns.
Elsewhere in the article, O’Neill gives another profiling example. “Age progression could someday factor into insurance assessment and health care,” she writes. “For example, if you seem to be aging faster than your cohorts, perhaps you’re not a very good insurance risk. You may pay more or be denied coverage.”
Should We Be Worried?
Despite these worries, Facebook released a statement clarifying that they are not behind the #10YearChallenge. “The 10 year challenge is a user-generated meme that started on its own, without our involvement,” said Facebook in a tweet. “It’s evidence of the fun people have on Facebook, and that’s it.”
Sure. Beyond Facebook’s somewhat creepy, non-reassuring tweet on their involvement, the #10YearChallenge and O’Neill’s Wired column has brought privacy, data, and facial recognition algorithms into the spotlight and has prompted a conversation about how this technology is currently being implemented.
Some of the more high profile uses of facial recognition technology have come courtesy of Taylor Swift. Video kiosks at her tour stops allowed fans to watch tour rehearsal videos but were also equipped with facial recognition cameras that were used by her team to sniff out known stalkers of the pop star.
So should we be worried about the #10YearChallenge and facial recognition algorithms? Yes and no. The meme itself is for the most part harmless. But it is certain that facial recognition tech will be more ubiquitous as time goes on, and it’s up to people to be aware of how it is used and the larger data implications it holds.