Panelist Ellen Nielsen

Ellen Nielsen

Chevron

United States

Ellen Nielsen is the chief data officer at Chevron, where she focuses on creating a data-oriented culture partnered with value-chain thinking. She has over 30 years of global experience as an executive in IT, digital, data, procurement, and supply chain across multiple industries. Nielsen is a regular speaker at industry events and has received numerous awards and recognitions, including being named to CDO Magazine’s 2023 Global Data Power Women list. She was also ranked fifth on the 2023 DataIQ 100 list of the most influential people in data in the United States. She also serves on a variety of boards, including those of the Petroleum Industry Data Exchange and Women Leaders in Data & AI.

Learn more about Nielsen’s approach to AI via the Me, Myself, and AI podcast.

Voting History

Statement	Response
Organizations are sufficiently expanding risk management capabilities to address AI-related risks. Strongly disagree	“Businesses are merely scratching the surface of AI risk management. Responsible AI is a new challenge. Whereas operational or financial risks are defined, the fast-evolving nature of AI-related risks makes managing them more complex. It is crucial to understand the specific elements that require protection and safeguarding. Many companies have not undertaken that exercise. Consider a responsible AI trilemma: Any risk management framework hinges on three points — people, process, and technology. People: Continuous education is crucial for managing AI risk. The expense of training workers to manage AI-driven challenges may exceed a company’s capacity and resources, leading it to avoid investing. The demand for AI governance and risk experts is outpacing the supply. Process: Processes form the backbone of any risk management system. Policies and regulations on AI are still emerging, making it hard to incorporate effective AI risk management strategies that can adapt and evolve. Technology: AI calls for security beyond safeguarding data, to also protect the very insights that drive business strategies. The technologies aimed at managing these newer, subtler risks are themselves evolving.”

Statement

Response

Organizations are sufficiently expanding risk management capabilities to address AI-related risks. Strongly disagree

“Businesses are merely scratching the surface of AI risk management. Responsible AI is a new challenge. Whereas operational or financial risks are defined, the fast-evolving nature of AI-related risks makes managing them more complex. It is crucial to understand the specific elements that require protection and safeguarding. Many companies have not undertaken that exercise.

Consider a responsible AI trilemma: Any risk management framework hinges on three points — people, process, and technology.

People: Continuous education is crucial for managing AI risk. The expense of training workers to manage AI-driven challenges may exceed a company’s capacity and resources, leading it to avoid investing. The demand for AI governance and risk experts is outpacing the supply.

Process: Processes form the backbone of any risk management system. Policies and regulations on AI are still emerging, making it hard to incorporate effective AI risk management strategies that can adapt and evolve.

Technology: AI calls for security beyond safeguarding data, to also protect the very insights that drive business strategies. The technologies aimed at managing these newer, subtler risks are themselves evolving.”