(2019-10-14) How Pinterest Built One Of Silicon Valleys Most Successful Algorithms

Will Oremus: 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.

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.

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

Behind the scenes, however, Pinterest’s engineers and executives are grappling with the same kinds of tensions that have caused trouble elsewhere. The company’s leaders say they want to map a different route to success in Silicon Valley, one that’s less meteoric and more humane. But in its first year as a public company, it faces a pivotal challenge: How to grow beyond a user base that has historically skewed toward white, suburban women without alienating loyalists, stereotyping newcomers, or potentially allowing for the spread of misinformation and radicalization.

On Tuesday, the company will roll out a feature designed to address perhaps its algorithm’s most visible flaw: its tendency to draw the wrong conclusions from users’ past behavior, and pollute their feeds with stuff they don’t want to see anymore — like wedding dresses for a user who broke off her engagement, or nursery decor for a user who suffered a miscarriage. The feature, which Pinterest is calling the Home Feed Tuner, will let users review and manually edit their activity history and interests, essentially telling the algorithm what to remember and what to forget

Other trade-offs are proving trickier, however, like how to understand users deeply enough to keep them coming back for more, without boring them, boxing them in, or creeping them out.

Pinterest struggled at first to gain traction as a general-interest platform for sharing collections of images. That changed when Iowan co-founder Ben Silbermann attended a conference for female bloggers and influencers, who took to it instantly.

Initially, the home feed showed an assortment of the most popular pins from all users, based on the boards they followed, which was perfect for attracting like-minded newcomers, but not for diversifying the site’s appeal

Over the years, Pinterest had to redesign its systems and retrain its algorithms to better identify and target different types of users and map their interests. Hence the question about gender when you sign up

The question about language and region, for example, has helped Pinterest reach audiences outside the United States

But dicing users into ever finer subgroups carries its own risks, especially for groups that have historically been underrepresented on the site.

Pinterest is working on ways to help users see themselves in the product.

“We wanted to understand, would users want to proactively provide more about themselves to increase personalization? We found the answer is no — they just want the product to work for everyone,” Morgan says.

Mike Caulfield, a media literacy and online communications expert at Washington State University Vancouver. In 2017, he went looking for political culture on Pinterest, and what he found was just about as ugly as what you’d expect on any other social platform. There were boards full of fake news, ethnic stereotypes, and QAnon conspiracy theories.

Part of the problem, as explained by Middlebury College’s Amy Collier, is that spammers game Pinterest’s algorithm by putting viral political memes on the same board as, say, T-shirts they want to sell.

They thanked him for highlighting the problem and invited him to meet with company executives and share ideas for how to solve it. And then, at least on the anti-vaxx issue, they followed through.

In August, Pinterest changed how its search engine treats queries about vaccines. Rather than surfacing the most popular vaccine-related pins, Pinterest said it would now show only pins from major health organizations

To what extent that approach will scale to all of the other problems that face a platform with 300 million users remains to be seen

The conventional wisdom among social media companies is that you can’t put too much of the onus on users to personalize their own feeds.

Every action you take further refines the engagement optimization machine, and giving users access to its levers would only gum up the works

But what if optimizing engagement isn’t your ultimate goal?

The result of that project was “Tune Your Home Feed,” which it has already made available to some users

Pinterest will offer a level of customization that relatively few will care to employ. But Seyal says it became apparent in testing that those users overlapped heavily with the ones making the complaints. They also turned out to be some of Pinterest’s most loyal fans.

*What the company can do to mitigate these problems, he says, is to look carefully at the types of content its system tends to amplify, and adjust the algorithm’s parameters to prioritize some over others.

For instance, Pinterest’s algorithm treats “saves” of a given pin as a much stronger positive signal than clicks.*

Even within the category of clicks, the company’s software treats clicks to what it considers “high-quality” sites as more valuable than clicks to other sites. Whenever Pinterest tests a change to the algorithm, Seyal says, it looks at how that change affects outbound traffic to a hand-chosen index of reputable sites that are focused on topics such as lifestyle, fashion, and home decor.

Seyal says Pinterest has big ideas, too. “We could get so much better at doing what we do: new formats, new kinds of interactions, things other than pins.” He believes the future of Pinterest’s algorithm involves not only reflecting users’ tastes and styles, but helping to shape them, the way top fashion brands do. He looks to Spotify’s human-curated playlists, such as the influential RapCaviar, as a model.