AS A COMPUTER science PhD student, I am a disciple of big data. I see no ground too sacred for statistics: I have used it to study everything from sex to Shakespeare, and earned angry retorts for these attempts to render the ineffable mathematical. At Stanford I was given, as a teenager, weapons both elegant and lethal—algorithms that could pick out the terrorists most worth targeting in a network, detect someone’s dissatisfaction with the government from their online writing.

Computer science is wondrous. The problem is that many people in Silicon Valley believe that it is all that matters. You see this when recruiters at career fairs make it clear they’re only interested in the computer scientists; in the salary gap between engineering and non-engineering students; in the quizzical looks humanities students get when they dare to reveal their majors. I’ve watched brilliant computer scientists display such woeful ignorance of the populations they were studying that I laughed in their faces. I’ve watched military scientists present their lethal innovations with childlike enthusiasm while making no mention of whom the weapons are being used on. There are few things scarier than a scientist who can give an academic talk on how to shoot a human being but can’t reason about whether you should be shooting them at all.
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The fact that so many computer scientists are ignorant or disdainful of non-technical approaches is worrisome because in my work, I’m constantly confronting questions that can’t be answered with code. When I coded at Coursera, an online education company, I developed an algorithm that would recommend classes to people in part based on their gender. But the company decided not to use it when we discovered it would push women away from computer science classes.
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