Reduce data privacy issues with machine learning models

What this post added

Introduces IBM's open-source AI Privacy toolkit, specifically its data minimization capability for machine learning models. Details how the toolkit identifies the minimal set of features and their required detail for accurate predictions, reducing the need for extensive personal data. Explains the underlying method of removing or generalizing input features based on model knowledge. Provides a real-world application example in healthcare and mentions ongoing research and a published paper on the topic.