Implementing AI Ethics: What Can We Leverage from Privacy Frameworks?

An effective AI compliance and governance framework embeds AI ethics across the full AI lifecycle. Although strong governance enables risk management and value capture from AI investments, many companies and institutions struggle with practical implementation of ethics. Using perspectives from four industry players, diverse risk strategies and different implementation roles, this session examines what AI ethics means in practice. It explores how ethical risks were identified in AI implementations; which technical and non-technical mitigations, controls and governance structures were applied; and how existing frameworks, such as privacy frameworks, were leveraged across all lifecycle stages. We compare implementation strategies and evaluate their effectiveness including shortcomings. We answer whether AI ethics can be implemented through checklists or technical controls or requires continuous dialogue and which methodologies best support it. The session also addresses ethical challenges of agentic AI and its impact on human autonomy. Attendees gain practical insights for building sustainable, ethical AI governance throughout the AI lifecycle.

What you will learn:

• What is AI ethics in the various stages of the AI lifecycle. 
• Identify what to leverage while embedding AI ethics in your company or institution. 
• Applying different implementation strategies to support AI ethics.