A new MIT study suggests an algorithm can predict someone’s behavior faster and more reliably than humans can.

Research scientists at MIT created the Data Science Machine to search for patterns and choose which variables are the most relevant. Their paper on the project results (pdf) was presented at the IEEE Data Science and Advanced Analytics conference in Paris last year.

Humans typically are required to select the relevant data points for analysis… but in 3 competitions with human teams, machines have made more accurate predictions that nearly two-thirds of human teams (615 of 906).

While humans worked on their predictive algorithms for months, the machine took two to twelve hours to produce each of its competition entries.

For example, when one competition asked teams to predict whether a student would drop out during the next ten days, based on student interactions with resources on an online course, there were many possible factors to consider. Teams might have looked at how late students turned in their problem sets, or whether they spent any time looking at lecture notes. But instead, MIT News reports, the two most important indicators turned out to be how far ahead of a deadline the student began working on their problem set, and how much time the student spent on the course website. These statistics weren’t directly collected by MIT’s online learning platform, but they could be inferred from data available.

The Data Science Machine performed well in this competition, as well as in two other competitions; one in which participants had to predict whether a crowd-funded project would be considered “exciting” and another if a customer would become a repeat buyer.

Kanter told MIT News that there are many possible uses for his Data Science Machine. “There’s so much data out there to be analyzed,” he said. “And right now it’s just sitting there not doing anything.”