Privacy Preserving Machine Learning: Maintaining confidentiality and preserving trust

A diagram with the title: Privacy Preserving Machine Learning: A holistic approach to protecting privacy. In the center of the diagram, there is a circle with the word “Trust.” There are five callouts coming from the circle. Moving clockwise, they are: Privacy & confidentiality; Transparency; Empower innovation; Security; Current & upcoming policies and regulations.

Machine learning (ML) offers tremendous opportunities to increase productivity. However, ML systems are only as good as the quality of the data that informs the training of ML models. And training ML models requires a significant amount of data, more than a single individual or organization can contribute. By sharing data to collaboratively train ML models, we can unlock value and develop powerful language models that are applicable

 

 

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