How Pinterest Built One of Silicon Valley’s Most Successful Algorithms
Inside the company’s powerful recommendations tool — and its efforts to avoid the scandals facing its rivals
Like most social networks, Pinterest was built on assumptions and biases. Unlike most social networks, Pinterest admits it.
From the start, you tell the company how to profile you. The service asks two personal questions when you register — your age and gender — and how you answer them shapes everything that happens next. Based on your responses, along with your language, region, and bits of your browsing history, Pinterest chooses an array of topic categories it thinks you might be interested in and asks you to pick at least five.
Tell Pinterest you’re a woman in your thirties, and your suggested interests will include “Makeup,” “Hair Tutorials,” “Workout Plans,” and “Dinner Recipes.” Tell it you’re a man in your thirties, and you’ll get some very different choices: “Woodworking,” “Funny Pictures,” “Survival Skills,” and “Gaming.” Or you can type your own response into a “Non-Binary” selection — it allows you to input anything — and you’ll get a stock of gender neutralish options like “Animals,” “Home Decor,” “Hairstyles” for women, “Men’s Hairstyles,” and “Coffin Nails.”
