10 Surprising Ways Machine Learning is Being Used Outside Tech – Part 2
2 May 2017
As machine learning (ML) continues to take over the tech world, companies and researchers outside the tech bubble have started using ML in strange and surprising ways. We already covered a few unusual ML applications, from diagnosing psychopathy to getting an edge in the Tour de France. Here are five more unexpected ways machine learning is being used:
6. Preventing money laundering
Companies like PayPal employ analysts who are constantly on the lookout for signs of money laundering. An analyst who detects an anomalous transaction that looks like laundering follows a standard procedure: they devise both a “good story” (that explains why the transaction might be legitimate) and a “bad story” (that explains why it might not be). But, as with any manual system, it’s imperfect.
That’s why PayPal has designed a machine learning system to prevent money laundering. Using deep learning and other tools, the system can adjudicate between legitimate and illegitimate transactions with greater accuracy than a human analyst.
7. Figuring out which message board threads will be closed
If you’re a programmer or you work with computers, you’ve probably relied on Stack Overflow for answers to your programming questions. Like any online forum, though, Stack Overflow gets its fair share of posts that are spammy, inflammatory, or just off topic. And given the volume of posts they see each day, moderators sometimes struggle to parse out the good from the bad.
That’s why Stack Overflow held a contest where users were asked to create a machine learning program that could predict when a thread would be locked. The winner user created a model that could predict thread closures with astonishing accuracy.
8. Predicting hospital wait times
Anyone who’s ever languished in the purgatory of an ER waiting room knows about the unpredictability of hospital wait times. Sometimes it’s three minutes, sometimes it’s three days, and there’s no telling when or why…until now.
A group of researchers have developed a machine learning algorithm that can predict hospital wait times. The system weighs different variables — whether it’s a holiday weekend, how cold it is outside, how many people are on staff — to calculate how long a patient will be there. The accuracy of the system increases over time, as it learns how many people come in on Saturdays, or how many staffers tend to call in sick on a given day.
9. Calculating auction prices
It’s often pretty easy for experts to predict the sale price of a precious item like an historical artifact, a famous painting, or a rare car. But what about a bulldozer? Used machinery, like bulldozers and earthmovers, goes up for auction all the time. However, price varies considerably between auctions.
Thanks to recent innovations in machine learning, though, it’s not going to be a problem for much longer. Models trained on wide range of data, from the size of a bulldozer’s tires to the historical auction prices of similar equipment, can predict final sale prices with over 60% accuracy.
10. Predicting earthquakes
About 10,000 people die in earthquakes each year, so researchers are always on the hunt for ways to predict earthquakes and their magnitude. A pair of scientists at Los Alamos National Laboratory have taken a crucial first step in that direction.
The researchers created a laboratory earthquake simulation: a model consisting of blocks separated by a chasm, or “fault line.” They then trained a machine learning algorithm to detect acoustic emissions from the model. In other words, by learning what an earthquake “sounds” like just before it happens, the model knew how to “listen” for future earthquakes. The ML model performed with astonishing accuracy, even detecting when an earthquake was not imminent – a feat that has largely eluded geologists.