The Data Minimization Principle in Machine Learning

Explore the concept of data minimization in machine learning through this 59-minute Google TechTalk presented by Ferdinando Fioretto. Delve into the challenges of implementing this principle, endorsed by global data protection regulations, in practical machine learning applications. Examine an optimization-based formalization attempt and its empirical analysis, revealing potential gaps between privacy expectations and actual benefits. Investigate the application of data minimization in high-stakes inference tasks, focusing on a sequential algorithm that identifies minimal attribute sets for accurate predictions. Gain insights into the importance of formalizing privacy legal principles for actionable deployment in the field of machine learning.

The Data Minimization Principle in Machine Learning