Machine Learning Programs’ CEO, Tom Murphy, discusses the benefits of machine learning and how it is revolutionising the insurance industry with actionable insights to help its customers work smarter.
So, what exactly IS machine learning?
Machine learning loosely refers to a collection of techniques and algorithms. The easiest way to explain it is to tell you how it differs from the standard methods used today. (I promise, there is no math or tech in this article!)
In every computer language there are simple statements like: “If A is true then do B, otherwise do C”. The programmer gives the computer a set of instructions and the computer starts at the top and works down, doing what it is told.
If you’ve ever seen a robot repeatedly following its instructions yet oblivious to the chaos it’s creating, that gives you some idea of the brittleness of standard programming techniques. They are really good when you are certain what you want the machine to do; but not so good for occasions where you want it to use some judgement.
How is machine learning different?
Suppose someone is looking at a picture of a cat, or maybe a dog, but they can’t be sure, and they want you to help them determine which it is. I might say “If it has ears, then it’s a cat, otherwise it’s a dog”. But that won’t work as dogs have ears too.
“If it has fur it’s a cat”, wouldn’t work either…. nor does spots, nor the number of legs, nor whiskers. Actually, it turns out it’s very hard to explain to someone how to decide if a given picture is of a cat or a dog. It’s hard to instruct someone else but if you could see the picture, you would easily identify it.
If you think about it, it’s a combination of lots of different things, where no one aspect can be pointed at as being definitive. With these combinations, you can 99.9% of the time tell cats from dogs by looking. It’s subtle, possibly indescribable, but you know.
Since we are not able to describe how to identify one from the other, we cannot program a computer to do this task. The computer is the same as the person looking at the pictures. If you can’t explain how to identify them, you can’t code a computer to do it either.