First, here’s what they reported finding last year: The question about Ms. Williams’s smiling was far from an exception. Across all the categories analyzed and all the questions, the algorithm revealed that female players were much more likely to be asked questions unrelated to tennis. Once we remove the more standard, rote (or “typical”) questions, roughly 70 percent of the questions unrelated to tennis were posed to female players.
(This point is driven home in a popular parody video of male athletes being asked nonsports questions.)
We asked the researchers to apply their algorithm to this year’s Open. Here are some typical questions or rote questions asked of male tennis players:
“What would you expect from a match like that?”
“How does it feel to be back in the second week of the U.S. Open?”
Here are some typical or rote questions asked of female players:
“What do you think of the match that’s coming up?”
“You have been through injuries and you have had some tough matches here, but what makes it special to play here at the U.S. Open?”
The researchers’ algorithm also identifies the most atypical, even bizarre questions asked of the athletes.
Asked of men:
“There were some moments you were doubting yourself or not?”
“What does it mean to you if you are indeed an inspiration for people who are not tall?”
Asked of women:
“Do you know of players who get their nails done on-site?”
“Was there anything in particular you bought when you went shopping?”
How did an algorithm “know” to single out these questions? How did it decide what was and what was not related to tennis?
To understand this, it helps to know why algorithms are useful for processing language. The first task in this example is to find individual topics or words that we conjecture are unrelated to tennis. Imagine doing that without a computer. Exactly because language is rich, questions can differ in a dizzying array of ways. Searching with our own eyes through all these possibilities could take impossibly long. An algorithm, on the other hand, could try thousands of such paths.
This by itself is a remarkable skill. But it still needs guidance…