Can We End the Era of Unreadable Privacy Policies with AI?
With the length and complexity of today's privacy policies, it's no surprise that they are rarely read. So what if AI can read these policies on our behalf, simplify them, and let us know what to do about them? That is why we created Polisis, the first advanced AI platform for analyzing privacy policies, and PriBot, the first AI assistant for automatically answering questions about these policies. In this talk, I'll be making the case for using deep learning to alleviate the huge cost for understanding these complex documents in the case of both businesses and individuals. I'll also outline our vision towards turning these documents from a costly requirement into a competitive business opportunity.
Hamza Harkous is a Postdoctoral Researcher at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He is the creator of Polisis, the first and most advanced AI platform for automated analysis of privacy policies. He also created PriBot, the first chatbot for privacy policies. He obtained his Ph.D., from EPFL in 2017, where he worked on data-driven usable privacy. His general interests are at the intersection of deep learning, privacy and human computer interaction. He is currently working on taking this research to the next deployment stage. This will provide the opportunity for businesses to automate the full workflow of privacy practices' assessment.