“Cloud VPN” could be an easy shorthand for securing cloud-based resources. Or it could be an overused buzzword bolted …
Hands up, how many of you have participated in Facebook’s “
That’s what Wired thinks, anyway. And its reasoning seems plausible.
Facebook’s 10 year challenge has gone viral. The company laid out the challenge by asking users to post two profile pictures side-by-side, 10 years apart. The idea is to show how much (or how little) you’ve changed during the past decade.
Everyone has gotten in on the act, including celebrities. You probably have too. So why does Wired suggest there could be something sinister behind it?
It all started with a tweet, where Wired editor Kate O’Neill, somewhat jokingly at the time, talked about how the data Facebook now has could be mined to train its facial recognition algorithms on age progression and age recognition.
“My intent wasn’t to claim that the meme is inherently dangerous,” said O’Neill in her Wired article. “But I knew the facial recognition scenario was broadly plausible and indicative of a trend that people should be aware of. It’s worth considering the depth and breadth of the personal data we share without reservations.”
Some argued that Facebook has this data anyway, so why would the challenge help them tweak their facial recognition algorithms? After all, these photos have already been uploaded to Facebook, so they’re in the system. If Facebook wanted to pull profile photos over a 10 year period and use it to help with facial recognition, in theory, it already could.
As O’Neill points out, however, there’s no guarantee a Facebook profile photo from 10 years ago actually dates back to that period. Profile pics can range from baby photos to college photos. They can be of other people
With the challenge, people are offering up the side-by-sides on a plate, noting in their text when each photo was taken. This makes it far easier to mine the data for accurate age progression or age recognition 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.
It would help if you had a clean, simple, helpfully labeled set of then-and-now photos.”
Whether this is indeed a ploy for your age progression data or not, it wouldn’t be the first time our data from Facebook’s platform has been mined. We all remember the Cambridge Analytica scandal, where 70 million users’ personal data was extracted via silly games and surveys hosted on Facebook.
At the time, we thought that by offering details about ourselves we were finding out “what Harry Potter character we were most like.” In reality, we were handing over data to third parties. That data was then sold and used against us.
We now live in a world where our data is valued at a premium. Facebook may not have conducted this 10 year challenge to improve its facial recognition algorithm, but the fact that it could highlights the need to be more mindful about what we willingly share online.