Responsible AI in the Enterprise

7

Interpretability Toolkits and Fairness Measures – AWS, GCP, Azure, and AIF 360

Throughout this book, we have discussed the rationale for why responsible AI and AI governance are increasingly becoming critical disciplines for enterprises that wish to leverage AI. We also provided an overview of the methods that can be used to test that the machine learning models underpinning AI are safe, fair, and fit for purpose, along with introducing an AI assurance framework – AI STEPS FORWARD.

Leading cloud AI providers – the hyperscalers (namely AWS, Google, and Microsoft) – have recognized the need for AI explainability, and each has developed explainability toolkits designed to be used with its respective ML/AI development and MLOps environments. At ...