Five Myths About Machine Learning You Need To Know Today

Ask most people outside academia or Silicon Valley what comes to mind when they hear the term “machine learning” and you’re likely to get a response that involves a movie like “The Matrix” or “Ex Machina.” You’re less likely to hear how it’s a great tool for fraud detection or supply chain optimization, and that’s too bad. Machine learning has a tremendous range of business applications, from optimizing data centers to predicting fine wine price changes to retail market basket analysis. With that in mind, I hope to cut through the science fiction clutter and misconceptions so you can consider how machine learning relates to your business.

Myth 1: Machine learning is only for PhDs

Many have heard about Andrew Ng’s popular graduate level machine learning course at Stanford, now available on Coursera. You won’t need to take that course to benefit from machine learning (although admittedly it’s a great course). Learning to write machine learning algorithms is quite different from learning to use them. After all, you don’t need to know how to program an app to use your iPhone. As with many technologies, the best platforms abstract away the obscure to present business users with applications that require minimal training. If you know your use case and basic concepts of machine learning, you are ready to go. The technical expertise to fine tune which algorithms make the most sense for a particular use case is left to data scientists. Users don’t need to know the math, just their business domain.

Myth 2: Machines will take over

All those movies where the robots understand themselves, learn through experience, and seek to dominate humanity? That is not machine learning! That is artificial intelligence and the distinction is important. Machine learning is a tool you can choose to accept and put to use. Just like you have the choice to use Facebook or not, there is a decision to be made and choices that determine how much it influences your life. My colleague John Thuma got it right when he described machine learning as the next penicillin. Machine learning is something that extends your capabilities, not the machine’s.

On the contrary, machine learning has a long history.