Episode 65

Building Trust in AI — Responsible Data Sharing, Governance, and Real-World Accountability

In this episode of the AI Loves Data Podcast, we sit down with James Robson, a specialist in data governance, responsible data sharing, and trust-building for mission-led organizations.

James works with charities, research institutions, and public-impact teams to help them navigate complex challenges around privacy, accountability, and ethical data use, ensuring that data is not only compliant but genuinely trusted.

We explore how organizations can move beyond “compliance theatre” to build systems that balance privacy, usefulness, and public value — especially when working with sensitive data in high-stakes environments.

Key Highlights:

• Responsible Data in Practice: What ethical and lawful data use actually looks like inside organizations.
• Beyond Compliance Theatre: Why checkbox compliance fails — and what to do instead
• Data Sharing & Trust: How to safely enable collaboration while protecting sensitive information.
• AI & Accountability: How AI is changing the landscape of governance, risk, and decision-making.
• Leadership & Decision-Making: Communicating risk and building trust across technical and non-technical teams.

🎧 Tune in to Episode 65 to learn how to build trustworthy data systems and responsible AI practices that stand up in the real world.

Be sure to mark your calendars for the annual ALD NYC on Dec 11, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of finance, banking and insurance: https://ailovesdata.com/newyork/