Integrating and Upholding Secure, Responsible and Resilient Data and AI Systems

Trust must be designed into digital services from the outset — not retrofitted after risk emerges. This session explores how strong data governance, clear guardrails, and transparent, accountable AI practices form the foundation for responsible innovation— enabling progress without compromising public trust.

Protecting privacy and maintaining transparency and trust in citizen-facing AI and data initiatives (designing transparency into services by default)
Data governance as the foundation for AI - Establishing policies, standards, and oversight mechanisms to ensure safe and ethical AI adoption
Striking the balance between innovation and risk to ensure lasting progress and retained trust
Adhering to guardrails, guidance and frameworks
Why trust is government’s most fragile asset
How to handle mistakes in a digital-first world