Natural language privacy policies have become the de facto standard to address expectations of “notice and choice” on the Web. However, users generally do not read these policies and those who do struggle to understand them. Initiatives, such as P3P and Do Not Track aimed to address this problem by developing machine-readable formats to convey a website's data practices. However, many website operators are reluctant to embrace such approaches.
New study shows dearth of privacy opt-out choices and offers solution to empower users to readily identify choices often buried deep in the text of privacy policies
The Internet of Things (IoT) and Big Data are making it impractical for people to keep up with the many different ways in which their data can potentially be collected and processed. What is needed is a new, more scalable paradigm that empowers users to regain appropriate control over their data.
Have you ever seen a sign that reads "this area under camera surveillance" and wondered whether the cameras are coupled to facial recognition or scene recognition software, who that footage might be shared with, and for how long it is retained? Until today, there was no standard mechanism to communicate this type of information to people. Yet smart sensors are everywhere. They are part of what is now referred to as the Internet of Things (“IoT”) with billions of devices already deployed today. The IoT Privacy Infrastructure developed at Carnegie Mellon University has been designed to address this problem.
The Walt Disney Company has a rich tradition of bringing great stories, characters and experiences to our guests around the world, and our sites and applications are createdto entertain and connect guests with the best that we have to offer on the platforms and devices our guests prefer.
Smartphone users are often unaware of the data collected by apps running on their devices. We report on a study that evaluates the benefits of giving users an app permission manager and sending them nudges intended to raise their awareness of the data collected by their apps. Our study provides both qualitative and quantitative evidence that these approaches are complementary and can each play a significant role in empowering users to more effectively control their privacy.
Livehoods offer a new way to conceptualize the dynamics, structure, and character of a city by analyzing the social media its residents generate. By looking at people's checkin patterns at places across the city, we create a mapping of the different dynamic areas that comprise it. Each Livehood tells a different story of the people and places that shape it.
This tool allows you to query our entire collection of 115 human-annotated privacy policies. For example, you can look for all the first party collection/use practices identified by our human annotators across the corpus of 115 privacy policies. Choose one of the sample questions below and see how the filters are modified to capture your question.