Interpreting Privacy Policies with Artificial Intelligence

A team of researchers from EPFL in Switzerland, University of Wisconsin and University of Michigan developed a deep learning-based program that can automatically read and make sense of any online service’s privacy policy.

“Our program uses simple graphs and color codes to show users exactly how their data could be used. For instance, some websites share geolocation data for marketing purposes, while others may not fully protect information about children. Such clauses are typically buried deep in their data protection policies,” says Hamza Harkous, a post-doc working at EPFL’s Distributed Information Systems Laboratory and the project lead.

Using TITAN X GPUs and the cuDNN-accelerated TensorFlow deep learning framework, the team trained their convolutional neural networks on over 130,000 online privacy policies from apps on the Google Play Store. For more details about their deep learning architecture, read their recent paper, “Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning“.

Once trained, their software is able to sour through a privacy policy in seconds and displays the results in easy-to-read visuals that you can get an understanding which data a website would be authorized to collect and for what purpose.

Their program called Polisis can be used for free of change as a browser extension or directly on their website by inserting the website’s url. They also have an online chatbot called PriBot where you can enter questions about a website’s data protection policy.

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About Brad Nemire

Brad Nemire
Brad Nemire is on the Developer Marketing team and loves reading about all of the fascinating research being done by developers using NVIDIA GPUs. Reach out to Brad on Twitter @BradNemire and let him know how you’re using GPUs to accelerate your research. Brad graduated from San Diego State University and currently resides in San Jose, CA. Follow @BradNemire on Twitter