10378: Ensure Your AI Models Are Trustworthy for Enterprise Use Cases on IBM zSystems

Project and Program: New and Innovative Technologies, Machine Learning/AI

Tags: Proceedings, SHARE Orlando 2024, 2024

AI has been increasingly prevalent in enterprises to support human decision making and improve the efficiency. Though AI shows great promise on help us to uncover valuable insights, we need to be cautious to make sure AI is trustworthy and lower the risk of unexpected results, especially when applying AI in enterprise use cases. This includes but not limited to ensure the AI systems are fair, robust, and explainable. In this session, we will discuss and show case how we can leverage Watson Machine Learning for z/OS to seamlessly ensure the AI models, which are deployed on IBM zSystems to serve for Z applications, can be closely monitored for fairness, accuracy, and each of the decision made by those models is explainable. -- Presented by Jia Li; Andrew Sica

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