You don't read privacy policies. And of course, that's because they're not actually written for you, or any of the other billions of people who click to agree to their inscrutable legalese. Instead, like bad poetry and teenagers' diaries, those millions upon millions of words are produced for the benefit of their authors, not readers—the lawyers who wrote those get-out clauses to protect their Silicon Valley employers.

But one group of academics has proposed a way to make those virtually illegible privacy policies into the actual tool of consumer protection they pretend to be: an artificial intelligence that's fluent in fine print. Today, researchers at Switzerland's Federal Institute of Technology at Lausanne (EPFL), the University of Wisconsin and the University of Michigan announced the release of Polisis—short for "privacy policy analysis"—a new website and browser extension that uses their machine-learning-trained app to automatically read and make sense of any online service's privacy policy, so you don't have to.

'What if we turned privacy policies into a conversation?' Hamza Harkous, EPFL

In about 30 seconds, Polisis can read a privacy policy it's never seen before and extract a readable summary, displayed in a graphic flow chart, of what kind of data a service collects, where that data could be sent, and whether a user can opt out of that collection or sharing. Polisis' creators have also built a chat interface they call Pribot that's designed to answer questions about any privacy policy, intended as a sort of privacy-focused paralegal advisor. Together, the researchers hope those tools can unlock the secrets of how tech firms use your data that have long been hidden in plain sight.

"What if we visualize what’s in the policy for the user?" asks Hamza Harkous, an EPFL researcher who led the work, describing the thoughts that led the group to their work on Polisis and Pribot. "Not to give every piece of the policy, but just the interesting stuff... What if we turned privacy policies into a conversation?"

Plug in the website for Pokemon Go, for instance, and Polisis will immediately find its privacy policy and show you the vast panoply of information that the game collects, from IP addresses and device IDs to location and demographics, as well as how those data sources are split between advertising, marketing, and use by the game itself. It also shows that only a small sliver of that data is subject to a clear opt-in consent. (See how Polisis lays out those data flows in the chart below.) Feed it the website for DNA analysis app Helix, and Polisis shows that health and demographic information is collected for analytics and basic services, but, reassuringly, none of it is used for advertising and marketing, and most of the sensitive data collection is opt-in.

Polisis' AI-generated visualization of the privacy policy for Pokemon Go. Pribot

"The information is there, it defines how companies can use your data, but no one reads it," says Florian Schaub, a University of Michigan researcher who worked on the project. "So we want to foreground it."

Polisis isn't actually the first attempt to use machine learning to pull human-readable information out of privacy policies. Both Carnegie Mellon University and Columbia have made their own attempts at similar projects in recent years, points out NYU Law Professor Florencia Marotta-Wurgler, who has focused her own research on user interactions with terms of service contracts online. (One of her own studies showed that only .07 percent of users actually click on a terms of service link before clicking "agree.") The Usable Privacy Policy Project, a collaboration that includes both Columbia and CMU, released its own automated tool to annotate privacy policies just last month. But Marotta-Wurgler notes that Polisis' visual and chat-bot interfaces haven't been tried before, and says the latest project is also more detailed in how it defines different kinds of data. "The granularity is really nice," Marotta-Wurgler says. "It’s a way of communicating this information that’s more interactive."