Towards effective, efficient and equitable privacy-preserving machine learning - Agrawal, N (2021)
Machine learning has assumed an increasingly important role in Artificial Intelligence in recent years. Moreover, in spheres such as online shopping, virtual personal assistants, recommendation systems amongst other things, it is quickly becoming part and parcel of our daily lives. The power of data combined with machine learning algorithms has driven widespread uptake of these AI methods. However, there have been sensitivity and privacy concerns over the data to be processed. This is especially salient in areas such as healthcare and finance. Privacy-preserving machine learning mitigates these privacy challenges through private computation over sensitive data. However, the process is not trivial or without trade-offs.