That said, I think we need a healthy skepticism towards image classification results, too. State-of-the-art architectures like Inception seem to work by learning features that reliably discriminate each object from all others, but fall short of defining that object.
They are good at, say, recognizing a dog no matter what posture the dog is in – but they do this not through an understanding of body kinesiology (”a dog’s body can deform in this way and still be a dog, but not that one”), they do it by identifying the least deformable part of a dog and then looking just for that part. This is why Deep Dream images were so full of dog heads, specifically. (And of eyes in general.)
The characterizations they learn are like the “featherless biped” definition of a human – actually very good at discriminating humans from other things in almost every circumstance, yet clearly not capturing the fundamental concept, which means they produce false positives on things that are not even close to human (like Diogenes’ plucked chicken).
Auto-generating “plucked chicken” examples has become its own pursuit in neural net research, under the name of “adversarial examples.” A recent paper (many thanks to whichever tumblr user put this on my dash) shows that you can get your robo-Diogenes to produce 3D objects that are basically always misclassified by some network, even when seen from different angles and under different lighting.
For example, they made this weird turtle, which the network reliably thinks is a rifle (seriously), in all three of these pics and many others:
It’s easy to come up with a plausible-sounding story for why this worked. This turtle has a pattern on its back, but it’s not the very distinctive pattern we’re used to seeing on turtles. And so of course the network learned to recognize turtles by looking for that pattern, because it’s a great way to reliably tell them apart from other roundish things with four feet and a head. But this is a “featherless biped” type of definition, and can be defeated by a turtle that doesn’t have the pattern.