The Usable Privacy Policy Project

Towards Effective Web Privacy Notice and Choice

Natural language privacy policies have become a de facto standard to address expectations of “notice and choice” on the Web. Yet, there is ample evidence that users generally do not read these policies and that those who occasionally do struggle to understand what they read. Initiatives aimed at addressing this problem through the development of machine implementable standards or other solutions that require website operators to adhere to more stringent requirements have run into obstacles, with many website operators showing reluctance to commit to anything more than what they currently do.

This NSF Frontier project builds on recent advances in natural language processing, privacy preference modeling, crowdsourcing, formal methods, and privacy interfaces to overcome this situation. It combines fundamental research with the development of scalable technologies to:

  1. Semi-automatically extract key privacy policy features from natural language website privacy policies, and
  2. Present these features to users in an easy-to-digest format that enables them to make more informed privacy decisions as they interact with different websites.

As such, this project offers the prospect of overcoming the limitations of current natural language privacy policies without imposing new requirements on website operators. Work in this project will also involve the systematic collection and analysis of website privacy policies, looking for trends and deficiencies both in the wording and content of these policies across different sectors and using this analysis to inform ongoing public policy debates. A transition phase will enable the transfer of these technologies to industry for large-scale deployment and to regulators and policy makers interested in tracking practices.

More about the Project

To learn more about the project have a look at our publications, activities, and recent news. The following resources provide an overview of the project goals and our overall approach:

Sadeh et al. The Usable Privacy Policy Project: Combining Crowdsourcing, Machine Learning and Natural Language Processing to Semi-Automatically Answer Those Privacy Questions Users Care About. Tech. report CMU-ISR-13-119, December 2013.

Sadeh et al. Towards Usable Privacy Policies: Semi-automatically Extracting Data Practices From Websites' Privacy Policies. Poster at SOUPS '14, July 2014.

Brief project overview video

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