January 2019

Demystifying Machine Learning with Your Dog

When someone learns what I do I often find myself explaining why despite what they may have heard, AI is not becoming conscious and taking over the world. I usually try demystifying machine learning by making an analogy to something familiar that would never be considered capable of that kind of domination. So when a fellow dog owner and I had this conversation recently at the dog park, I used our dogs as the example, and although it’s an imperfect analogy, it seems to do the trick.

How a dog learns

If you want your dog to do something on command, you start by getting her to do it, and then saying something or showing her something at the same time and giving her a treat. After seeing this over and over, your dog starts picking up a pattern, and forming an association between the auditory signal (e.g. vocal command) or visual signal (e.g. hand gesture) and the desired action.

So if you’re successful, when you say sit, she realizes it’s not just random noise, but that there’s a significant correlation of getting a reward if she takes your word as input, and outputs her butt on the ground.

Ask any dog owner however, and they’ll tell you it’s not over yet. She may have mastered sitting in your living room when you say the word just so, but has no idea what to do with when you try the same thing in the kitchen, or on the field outside, or when someone else says it.

She memorized a behavior under one very specific set of circumstances, but hasn’t learned she needs to apply it in others that aren’t exactly the same. To her sitting in the living room isn’t the same as in the field, and she only knows to do it in places where it’s been taught. The input to her isn’t just the word, but the conditions under which it was said too. That’s why you need to repeat the same training under different conditions – places, times of day, emotional states, people, and ways of saying it. The more inputs (conditions under which you ask her to sit) you give her, the better she will learn to sit when the input isn’t exactly the same as what you’ve taught her before. She learns to generalize.

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