Building Trustworthy AI Systems Through Technical Rigor and Ethical Design

As part of the AI Lunch & Learn Series, Dr David A. Rivkin will lead an in-depth exploration of Responsible AI, where ethical intent meets robust technical execution.

This live session provides a practical, end-to-end view of the AI lifecycle, from data governance and fairness-aware model development to production monitoring and incident response. Participants will gain real-time insights into how to balance accuracy with fairness, implement human-in-the-loop systems, and establish governance structures that make Responsible AI a consistent, repeatable practice rather than an ad-hoc response.

What you’ll gain from this live webinar:

• Practical insights into Responsible AI across the full AI lifecycle
• The six core pillars: Fairness, Transparency, Privacy, Accountability, Reliability, and Human agency
• Technical approaches to fairness-aware training, evaluation, monitoring, and incident response
• Best practices for cross-functional collaboration and AI governance
• Why Responsible AI is a continuous practice, not a one-off compliance exercise

Who should attend:

• AI, ML, and data professionals
• Product, UX, and digital leaders working with AI systems
• Governance, risk, compliance, and ethics professionals
• Technology decision-makers and AI practitioners
• Researchers, students, and Responsible AI enthusiasts

Notes: Registration is required to receive the access link.

Sponsors: CX INSIGHT

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Host or Publisher WA AI Hub