What I found impressive was that Apple Photos, given pictures of my cousins when they were 50 or more years old, was able to identify pictures of them as kids. On the other hand, it could never consistently distinguish between my two older brothers (although to be fair, they were identical twins). It also insists that a beagle I once owned was a cat. I mean, sure, he sometimes slept on his back with his paws in the air like a cat, but he was all dog.

On the other hand, it has no understanding of time. I have thousands of photos of me from the 1970s up through today, and Apple Photos is remarkably good at identifying me in all of them. And yet when my daughter was born it started identifying her, as a baby, as me. You'd think you could build a model to grasp the idea that a photo of a baby taken in 2015 is probably not of me.

I raise you the photo of a photo edge case.

Metadata is 2015, photo is 1960

But you shouldn't optimize for the edge case! (All of my 20k+ photos, dating back to 1905, have correct metadata + GPS).

I would argue that AI is exactly how you should handlr these edge cases, but likely a fine tuned model.

There would be hints that a photo is from the 60s vs 15s, a human would be able to tell in many cases even without other context.

That is exactly the use case AI is meant to excel at, something that is arguably hard to do algorithmically but is possible for an ML model

I hate to say it, but you are the edge case. Most users are not fixing dates of photos (especially pre-digital scans) or adding GPS data to photos which didn’t originally have it.

I'd suspect there are more people removing metadata from photos that have it than are adding metadata to photos that don't have it.

A photo from 1960 was scanned at <some later date>.