From the course: Foundations of Responsible AI
Join today to access over 26,000 courses taught by industry experts.
Privacy-preserving architectures
From the course: Foundations of Responsible AI
Privacy-preserving architectures
- Privacy is not just a matter of compliance. It's a foundational element of system design that affects reliability, user trust, and organizational risk. In most environments, the way you handle personal or sensitive data influences whether a product can scale, whether it'll hold up under regulatory scrutiny, and maybe most importantly whether users will continue to engage with it at all. This video focuses on how to approach privacy from an architectural perspective. The goal is not just to check a box, but to reduce unnecessary exposure. To ensure control over how data is used and to design systems that hold up under pressure. There are four design strategies that teams can use to build privacy into the system from the very beginning. The first is data minimization. Start by collecting only what's necessary. Many systems are built on broad data capture with the assumption that the more information, the better, but data that isn't needed creates risk. If your model performs equally…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.