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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
Me now: ponders how all this data could be mined to train facial recognition algorithms on age progression and age recognition
Most common rebuttal in my mentions: "That data is already available. Facebook's already got all the profile pictures."
Of course. And I'm not trying to say this is a crisis or that it's inherently dangerous. But just for fun, let's play this out.
Of course. And I'm not trying to say this is a crisis or that it's inherently dangerous. But just for fun, let's play this out.
Let's just imagine that you wanted to, say, train a facial recognition algorithm on age-related characteristics. You'd ideally want a broad and rigorous data set with lots of people's pictures. It'd help if you knew they were taken a fixed number of years apart — say 10 years.
Sure, you could mine Facebook for profile pictures and look at posting dates or EXIF data. But that's a lot of noise; it'd help if you had a clean then-and-now. What's more, the photo posting date and even EXIF data wouldn't always be reliable for when the pic was actually taken.
Why? People could have scanned offline photos. People might have uploaded pictures multiple times over years. Some platforms strip EXIF data for privacy; people's captions are helpfully adding that context back, as well as other context about where and how the pic was taken.
Thanks to this meme, there's now a very large data set of carefully curated photos of people from ~10 years ago and now. Is it bad that someone could use it to train a facial recognition algorithm? Not necessarily. It could help with finding missing kids, to cite one benign use.
Like most emerging technology, facial recognition's potential is mostly mundane: age recognition is probably most useful for targeted advertising. But also like most tech, there are chances of fraught consequences: it could someday factor into insurance assessment and healthcare.
I'm not saying anyone should panic or feel bad. It's simply worth becoming more mindful of how our data can be used. We don't need to be wary of everything; we just need to think critically, and learn more about the potential our data has at scale. We're all still learning.
Finally, if you're fascinated with this topic, you would probably be interested in my book, #TechHumanist. Here's an excerpt. amzn.to/2D6TFgV 
