The 10 Year Challenge and What We Feed the Feed

Archive note: this is a backdated post, written years later while rebuilding this site. It’s dated to the moment it covers, but the hindsight is real.

If your feed looks like mine this month, it’s wall-to-wall #10YearChallenge — everyone’s 2009 profile photo next to their 2019 one. Glow-ups, hairline jokes, the occasional brave soul posting their Friendster-era look. Harmless fun, and I’ve enjoyed scrolling it like everyone else.

Then a piece in Wired, by Kate O’Neill, asked the question that’s been rattling in my head since: what if we just helped train facial-recognition systems — for free, with labels attached?

The uncomfortable shape of the meme

Think about what the meme produces, from a data perspective: two photos of the same person, cleanly labeled with a ten-year gap, posted voluntarily, at massive scale. If you wanted to teach software how faces age — for ad targeting, for surveillance, for whatever — you could hardly design a better data-collection campaign. No consent forms, no payment, and the subjects do the labeling themselves.

Facebook has denied starting the trend or using it that way, and to be fair, they already have our photos with timestamps. Maybe the meme adds nothing. But the denial isn’t really the point. The point is that nobody participating — me included — even thought about it until someone asked. That reflex gap is the story.

What I’m taking from it

I wrote last year about the mystery of social media — how the feed shapes us in ways we don’t notice. This month added a corollary I want to write down:

Viral participation is data donation. Every quiz, filter, and challenge produces structured data about you. The fun is the interface; the dataset is the product. That’s not paranoia — it’s just literally how these platforms make money, said out loud.
“I have nothing to hide” misses the mechanism. The risk isn’t an individual secret leaking; it’s aggregate capability quietly improving — systems getting better at recognizing, predicting, and aging everyone’s face, trained on cheerful volunteers.
Asking the question shouldn’t feel rude. The healthiest thing about the Wired piece was the reaction: half “interesting point,” half “let people have fun.” Both are right. You can post the meme and understand what it feeds. What you can’t do is opt out of the consequences of what everyone feeds it together.

As a developer, I sit on the other side of this too. We build the forms, the uploads, the engagement loops. “What could this data train?” is a question worth asking at the design stage, not the apology stage.

Anyway. My 2009 self had a worse haircut and no idea what Git was. Some progress is safe to publish.