Understanding the AI lifecycle and the interplay of data, software, and hardware enables effective board oversight of AI initiatives.

Explore the critical elements of AI risk management from a board director's perspective. Learn how to establish context, assess risks, implement treatments, and maintain ongoing monitoring in the rapidly evolving landscape of AI technologies.

Explore the social aspects of ESG for tech companies, including data privacy, algorithmic bias, and organizational culture. Learn how board members can guide their organizations towards responsible social practices while maximizing business value.

Explore the evolution of Environmental, Social, and Governance (ESG) considerations and learn about the challenges in measuring ESG metrics, recent standardization efforts, and why ESG should be a top priority for corporate boards.

Understanding the implications of pre-trained models and their datasets is crucial for responsible AI governance.

Explore the critical role of data provenance in machine learning and AI, its impact on risk management and value creation, and why board members should care about this often overlooked aspect of data governance.