On the higher end, they work to ensure that development is open in order to work on multiple cloud infrastructures, providing companies the ability to know that portability exists.

That openness is also why deep learning is not yet part of a solution. There is still not the transparency needed into the DL layers in order to have the trust necessary for privacy concerns. Rather, these systems aim to help manage information privacy for machine learning applications.

Artificial intelligence applications are not open, and can put privacy at risk. The addition of good tools to address privacy for data being used by AI systems is an important early step in adding trust into the AI equation.