Today, we’re diving deep into one of the most pressing challenges of our time: how to build artificial intelligence responsibly.
My guest is Quentin Reul, a leader in AI ethics and governance, and an active contributor to the IEEE working group on AI Ethics Oversight. Quentin has spent years helping organizations unlock the potential of data and AI while keeping responsibility, transparency, and trust at the core.
In this conversation, we’ll unpack some of the most urgent headlines in generative AI—from models resorting to manipulation and unsafe outputs, to the governance gaps that make these risks possible. Quentin will help us cut through the noise, explaining in plain language why these systems behave the way they do, what Responsible AI really means in practice, and how companies can start embedding ethical principles before—not after—something goes wrong.
We’ll also explore the debates shaping the future of AI: additive vs. subtractive approaches to governance, the promise of hybrid neuro-symbolic systems, and the processes leaders often overlook in their rush to innovate. And finally, we’ll look ahead—what guardrails and cultural shifts will be needed to ensure AI remains not just powerful, but also sustainable and trusted?
So, whether you’re an AI builder, policymaker, or just someone trying to make sense of the headlines, this episode will give you both a framework and a forward-looking perspective.
Let’s dive in with Quentin Reul.