From the digital assistants like Siri in our phones to the algorithms that recommend us things to buy on Amazon, artificial intelligence is truly ingrained in the function of our technological society. Some of the most innovative forms of media exist because machine learning has exponentially become more prominent, and it is no surprise researchers at Stanford University use it to learn more about humans and their political patterns.
These researchers identified a unique association among U.S. voters and the type of cars they own. If a city has a higher percent of sedans than pickup trucks, then there is an 88% chance the city will vote Democrat in the 2020 presidential election. And vice versa, if a city has a higher percent of pickup trucks than sedans, then there is an 82% it will vote Republican.
Ultimately, the power of tracking data has proven to be of the utmost value for marketing, so it shouldn’t be too surprising to see machine learning applied in academic contexts. The researchers simply want to push the technology and explore the depths of what deep learning can be.
“For the first time in history, we have the technology to extract insights from very large amounts of visual data,” Harvard’s Nikhil Naik said on the New York Times. “But while the technology is exciting, computer scientists need to work closely with social scientists and others to make sure it’s useful.”