Learn how AI helps insurance companies, the importance of having a governance framework for AI, the role of CIOs in AI governance, and the future of AI in the insurance industry.
Learn how to scale model documentation methods for AI and complex modeling systems. Avoid the common mistakes that teams make early on.
Explore governance of foundation models and generative AI products. Learn about evaluating and governing these technologies in third-party management and model risk contexts.
In the aftermath of a worldwide IT incident, what can we learn about how to properly build and govern robust, performant, resilient AI systems, the right way.
What should you consider when teams tell you they’ve got AI “covered”? To increase your chances of success with AI, align your organization and projects around the following actions.
Learn about the goals of information theory, define the differences between metrics and divergences, explain why divergences are the wrong choice for monitoring, and propose better alternatives.
Many of the AI-based innovations used by enterprises are from specialty technology vendors. Get answers from a general counsel about why formal governance is critical to everyone's success with AI.
When is "easy" too good to be true? Learn more about the fine line between automating business operations and automating their governance.
Here is the supplement to our episode about non-parametric statistics. Learn from sample tests using Python 3.9 and popular scientific computing libraries.
Well-designed AI governance can increase the quality of AI systems and speed up their development while also mitigating or even avoiding risks. It increases ROI in a crucial area of technology research and development.
