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

Illustration: Jordan Speer

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.”

Once you’ve made your picks, Pinterest’s machine learning software crafts a home feed full of images, or “pins,” that it predicts will appeal to you. This is a crucial moment: Pinterest says its internal data shows that if people see pins they like right away, there’s a good chance they’ll become active users, returning to the site regularly for fresh content related to their interests, viewing ads tailored to those interests, and curating their own “boards” of related pins. If people fail to find anything that interests them at first glance, they may never come back.

For the 50 million new users who join Pinterest each year, the sign-up process is the first taste of one of Silicon Valley’s most successful yet least scrutinized algorithms. The code that powers Pinterest’s home feed, search results, and notifications — determining what images and ideas users see at every turn — is similar in kind to that which underpins Facebook’s News Feed, YouTube’s…