AI Privacy: How to manage the privacy risks of AI systems

Organisations use AI and machine learning to inform decisions and automate critical processes, like medical diagnosis.

There are significant privacy risks, because large amounts of sensitive data are often processed, and more data usually means better performing AI.

This session explores the state-of-the-art privacy engineering techniques which practitioners can employ to mitigate the risks of AI systems, promote data minimization, and ensure AI is privacy-preserving by design.

While there can be trade-offs between safeguarding privacy and implementing wider responsible AI principles, like transparency and fairness, we discuss sector specific best practices.