Applying AI Governance in CV
In the previous chapter, we covered best practices for designing an end-to-end CV pipeline. We discussed how you can use these guidelines throughout the ML life cycle to build, deploy, and manage reliable and scalable CV workflows.
In this chapter, we will discuss AI governance and its importance in CV. You may be asking, “How is AI governance relevant to my role as an AI/ML practitioner?” Security and compliance are only a small facet of the components of an AI governance strategy. The lack of existence of an organizational AI governance strategy has implications across the entire ML life cycle. From data collection to deploying and monitoring models, as an AI/ML practitioner it’s your responsibility to work with other business stakeholders to ensure ML models are performing as expected, and to address problems that arise quickly and efficiently.
The increasing speed and scale of model development and deployment has created...