AI Tool Seeks To Help Users Understand Complex Privacy Policies

By Marilia Wyatt, CyberPrivacy

Carnegie Mellon University’s tool aims to help users understand vague and complicated privacy policies on the internet to inform their decisions about their data.

The  ‘Usable Privacy Policy Project’ extracts annotations from privacy policies by combining crowdsourcing, machine learning, and natural language processing techniques.  It also uses artificial intelligence algorithms to crawl websites’ privacy policies and identify those that have language about data collection and use, data retention and security, user choice to remove/edit data, third-party sharing,  among others. The AI capability also rates each privacy policy based on readability.

“Through our work we hope to overcome the limitations of current natural language privacy policies without imposing new requirements on service providers,” said Norman Sadeh Lead Principal Investigator Professor Carnegie Mellon University. “We found that the text of the policies is often vague and ambiguous, and people tend to struggle to interpret and determine what personal information is collected, how it’s used, and what other entities it’s shared with,” Sadeh said. “From a legal standpoint, this is problematic.”

The Project also seeks to help organizations improve their privacy policies, assist regulators to assess policies, and inform ongoing public policy debates.

The Project is funded by the National Science Foundation under its Secure and Trustworthy Computing (SaTC) program and includes several affiliate universities.  Learn about it here.

Further Reading:

Project Newsletter June 2016

(Video) Carnegie Mellon’s new AI reads privacy policies for you

(Video) Usable Privacy Policy Project: An Overview (December 2017)

Daniel J. Solove, UNDERSTANDING PRIVACY, Harvard University Press, May 2008

Alan Westin’s Legacy of Privacy and Freedom


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