Building Trustworthy AI Systems Through Technical Rigor & Ethical Design

VIRTUAL AI Lunch & Learn Series

As part of the VIRTUAL 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
  

About the Speaker
Dr. David A. Rivkin, PhD is a visionary AI research leader with over 35 years of experience driving breakthrough innovations in machine learning, large language models and responsible AI deployment. He led research strategy for major large language models, establishing research roadmaps that balanced cutting-edge innovation with production systems serving millions of users worldwide. Currently serving as Senior Director of AI/ML and Head of AI for Optum UK at UnitedHealth Group, Dr. Rivkin leads AI research for ambient clinical documentation and evaluation frameworks, establishing strategic partnerships with Oxford University, MIT, and Harvard Medical School, while serving on the UnitedHealth Group AI Review Board to shape enterprise-wide responsible AI and governance strategy. His pioneering work spans early Markov models at the DSP Group, and proprietary ML systems in Energy, Materials Science, Healthcare and Life Sciences, complemented by his role as an IEEE Distinguished Lecturer, IET Member, international lecturer on AI and previously an advisor to multiple US federal grant programs including the National Cancer Institute and NIH as well as several Australian states. David hold 4 patents in Machine Learning and AI with 5 more pending. Dr. Rivkin brings deep technical expertise and thought leadership to critical topics in AI evaluation, governance integration, and the practical implementation of responsible AI principles across healthcare and enterprise environments.

About WA AI HubNotes: Registration is required to receive the virtual access link.

WA AI Hub (Western Australian AI Hub - wahub.ai) is Western Australia's community-driven initiative making artificial intelligence accessible, inclusive, and practical for everyone, regardless of technical background.

Custom Team Training

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