Governing models

Organizations using ML governance define a framework of rules and controls for managing the ML workflows pertaining to model development, production, and post-production monitoring. The commercial importance of ML is well established. Still, only a fraction of companies investing in ML are realizing the benefits. Some establishments have struggled to ensure that the outcomes of ML projects are well aligned with their strategic direction. Importantly, many organizations are subject to regulations, such as the recently implemented General Data Protection Regulation within the European Union and European Economic Area, which affect the use of these models and their outputs. Businesses, in general, need to steer their ML use to ensure regulatory requirements are satisfied and strategic goals and values are continually realized.

Having an established governance framework in place ensures that data scientists can focus on the innovative part of their role, which is solving...