Instead of joining in, I posted the following semi-sarcastic tweet:
Of those who were critical of my thesis, many argued that the pictures were already available anyway. The most common rebuttal was: “That data is already available. Facebook’s already got all the profile pictures.”
Of course they do. In various versions of the meme, people were instructed to post their first profile picture alongside their current profile picture, or a picture from 10 years ago alongside their current profile picture. So, yes: these profile pictures exist, they’ve got upload time stamps, many people have a lot of them, and for the most part they’re publicly accessible.
But let’s play out this idea.
Sure, you could mine Facebook for profile pictures and look at posting dates or EXIF data. But that whole set of profile pictures could end up generating a lot of useless noise. People don’t reliably upload pictures in chronological order, and it’s not uncommon for users to post pictures of something other than themselves as a profile picture. A quick glance through my Facebook friends’ profile pictures shows a friend’s dog who just died, several cartoons, word images, abstract patterns, and more.
In other words, it would help if you had a clean, simple, helpfully-labeled set of then-and-now photos.
What’s more, for the profile pictures on Facebook, the photo posting date wouldn’t necessarily match the date that the picture was taken. Even the EXIF metadata on the photo wouldn’t always be reliable for assessing that date.
Why? People could have scanned offline photos. They might have uploaded pictures multiple times over years. Some people resort to uploading screenshots of pictures found elsewhere online. Some platforms strip EXIF data for privacy.
In other words, thanks to this meme, there’s now a very large data set of carefully curated photos of people from roughly 10 years ago and now.
Of course, not all the dismissive comments in my Twitter mentions were about the pictures being already available; some critics noted that there was too much crap data to be usable. But data researchers and scientists know how to account for this. As with hashtags that go viral, you can generally place more trust in the validity of data earlier on in the trend or campaign— before people begin to participate ironically or attempt to hijack the hashtag for irrelevant purposes.
As for bogus pictures, image recognition algorithms are plenty sophisticated enough to pick out a human face. If you uploaded an image of a cat 10 years ago and now—as one of my friends did, adorably—that particular sample would be easy to throw out.
Is it bad that someone could use your Facebook photos to train a facial recognition algorithm? Not necessarily; in a way, it’s inevitable. Still, the broader takeaway here is that we need to approach our interactions with technology mindful of the data we generate and how it can be used at scale. I’ll offer three plausible use cases for facial recognition: one respectable, one mundane, and one risky.
The benign scenario: facial recognition technology, specifically age progression capability, could help with finding missing kids. Last year police in New Delhi, India reported tracking down nearly 3,000 missing kids in just four days using facial recognition technology. If the kids had been missing a while, they would likely look a little different from the last known photo of them, so a reliable age progression algorithm could be genuinely helpful here.
Like most emerging technology, there’s a chance of fraught consequences. Age progression could someday factor into insurance assessment and healthcare. 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.
It’s tough to overstate the fullness of how technology stands to impact humanity. The opportunity exists for us to make it better, but to do that, we also must to recognize some of the ways in which it can get worse. Once we understand the issues, it’s up to all of us to weigh in.
So is this such a big deal? Are bad things going to happen because you posted some already-public profile pictures to your wall? Is it dangerous to train facial recognition algorithms for age progression and age recognition? Not exactly.
Regardless of the origin or intent behind this meme, we must all become savvier about the data we create and share, the access we grant to it, and the implications for its use. If the context was a game that explicitly stated that it was collecting pairs of then-and-now photos for age progression research, you could choose to participate with an awareness of who was supposed to have access to the photos and for what purpose.
Humans are the connective link between the physical and digital worlds. Human interactions are the majority of what makes the Internet of Things interesting. Our data is the fuel that makes businesses smarter and more profitable.
We should demand that businesses treat our data with due respect, by all means. But we also need to treat our own data with respect.
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