It was your typical battle between man and machine as the Massachusetts Institute of Technology (MIT) announced this past week that its Data Science Machine proved in a recent 906-team prediction-based data analysis competition that it was more accurate than 615 human teams. Though the Data Science Machine didn’t take top honors at the competition, it did mark a big victory for computer-based data analysis.
According to results provided by EurekaAlert, the Data Science Machine performed very well in two of the three facets of the competition, notching 94-percent and 97 percent prediction accuracy scores. In the third facet of the competition, the computer scored a “more modest” 87 percent.
While other human teams posted accuracy percentages both higher and lower than the Data Science Machine, competition organizers noticed one huge difference between the computer’s work and the human teams’ work: time.
Sources who were involved in the competition were quoted as saying that the Data Science Machine was able to do in half a day what took teams of human scientists “months.”
Where the teams of humans typically labored over their prediction algorithms for months, the Data Science Machine took somewhere between two and 12 hours to produce each of its entries.
In speaking with Science Recorder, MIT graduate student Max Kanter said that scientist didn’t see the computer as a replacement for human analysis, but as a “complement to human intelligence.”
With “so much data” waiting to be analyzed, the Data Science Machine and other computers like it can help humans analyze and understand data that’s “just sitting there not doing anything.”
We view the Data Science Machine as a natural complement to human intelligence. There’s so much data out there to be analyzed. And right now it’s just sitting there not doing anything.
In an interview with the U.K.-based newspaper Daily Mail, Harvard University professor Margo Seltzer disagreed, saying she believes that computers like the Data Science Machine “is going to become the standard quickly — very quickly.”