Differential Privacy in the Real World: Differential privacy is making headlines thanks to the pioneering work of companies like Apple and Google, and it is now being used by companies of all sizes to provide data privacy guarantees. It is no secret that machine learning models can memorize (overfit) training data and that through carefully crafted adversarial inputs machine learning models can be subverted by an attacker. Combine these facts with a model that aggregates data from a multitude of customers and you have an AI-driven disaster waiting to happen. In this talk we will cover a defensive measure called “differential privacy” that is a potential solution to such threats. In this talk Yevgeniy will explain the core concepts of differential privacy and share a behind the scenes look at companies are successfully implementing differential privacy in their products.
Session Summary
Differential Privacy in the Real World
MLconf 2018 San Francisco
Yevgeniy Vahlis
Borealis AI
Head of Applied Machine Learning
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