AI has the potential to provide productive, efficient, and innovative solutions to our everyday problems, but it comes with its risks. These issues might have been avoided if humans had visibility into every stage of the system life cycle. Part of that life cycle involves training a machine learning (ML) model to help in making decisions. With visibility into model performance online and offline, these sorts of unwanted behaviors can be detected and managed early on. One of the main concerns with AI today is that issues are detected after the fact, usually when people have already been affected by them. This is a foundational problem in AI that needs a foundational fix. That’s where model performance management (MPM) comes in.
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