Privacy Policies serve as essential blueprints outlining how organizations handle user data. Yet, their lengthy nature and the use of complex language can pose challenges for users trying to fully grasp what they're agreeing to.  PrivacyCheck utilizes the power of Natural Language Processing Machine Learning models to summarize the complexities of privacy policies, score them on 10 user control questions and compare them to the standards of the European Union’s General Data Protection Regulations (GDPR). To improve the quality of the extension, our group made vast improvements to the models in use and the algorithms used to train these models utilizing new and advanced LLM (Large Language Model) technologies. We also implemented a new feature called “Custom Metrics” that allows users to grade privacies based on what values matter the most to them personally and what they seek in the summarization of privacy policies.

Team Members:

Kashif Bandali

Kartik Chatlani

Isha Chaudhary

Jake Leverett

Safin Rashid

Sahas Veera