The document discusses the need for privacy-aware machine learning, particularly in healthcare where sensitive data such as EHR and genomics is involved. It highlights federated learning as a technique that enables model training without moving data from its source, while addressing privacy concerns through secure methods like differential privacy. Tools and platforms that support these techniques, such as TensorFlow Federated and NVIDIA Clara, are also mentioned.