Artificial intelligence (AI) is transforming how we design, build, work and live. AI, like all technology, is neutral until it's applied. But how humans design and use AI, and manage potential biases, have raised pertinent questions around trust, fairness and transparency. While AI governance focuses on the visibility of machine learning models by making them more interpretable and explainable, automation in machine learning operations (MLOps) enables the governance-by-design that AI governance demands.
In this white paper, we unpack what AI governance is and is not, and review global developments in implementation. We also share insights on how AI governance can be incorporated into MLOps, with guidance for how governments and businesses can accelerate the use of artificial intelligence responsibly.
- What is AI governance and how does it relate to MLOps?
- Attributes of well-governed AI systems
- Building an AI governance culture
- AI Governance: 10 key concepts