Human-Centred Privacy in Machine Learning

Privacy-preserving machine learning has the potential to balance individuals’ privacy rights and companies’ economic goals. However, such technologies must inspire trust and communicate how they can match the expectations of the subjects of the data.  In this talk, I present the breadth of privacy vectors for machine learning and the implications of my work on user perspectives of the space.