From Evaluation to Mitigation: Building Safer Agents
As AI agents become more capable, measuring and mitigating risk is more important than ever. In this episode of Human in the Loop, our guest Mehrnoosh Sameki discusses the shift from evaluation to mitigation, the new open-source measurement framework ASSERT, and the role of agent control systems in building safer and more trustworthy agents.
MCP, Copilot Studio & Responsible AI
This episode explores the intersection of Model Context Protocol (MCP), Copilot Studio, and Responsible AI (RAI). We discuss how MCP is shaping the next generation of AI integrations, how organizations can build powerful agents with Copilot Studio, and why responsible AI principles must remain at the center of agent design, deployment, and governance. A practical discussion for developers, makers, and AI leaders looking to build intelligent systems that are both capable and trustworthy.
Data Poisoning - The Hidden Risk Shaping AI
This episode explores data poisoning and its growing impact on AI systems, from model backdoors to agent memory risk. Ioana and Chris chat with Microsoft's Giorgio Severi about how adversaries manipulate data, why these attacks are hard to detect, and what it takes to build layered defenses that keep AI systems reliable, safe, and trustworthy.
Better Data, Better AI: The Foundation for Responsible AI
For this episode of Human in the loop, we talked with Dux Raymond Sy (Chief brand officer, AvePoint) to explore why a foundation of trusted data is crucial in the AI era. We chatted about how to avoid data traps, how to prepare for a future full of AI assistants, and turn AI hype into real results without compromising trust.
Designing for Everyone: AI, Disability and the Human Perspective
In this episode of Human in the Loop, Christina Mallon joins us to unpack why disability is best understood as a mismatch between people and systems. We explore inclusive design, responsible AI, and why average users don't exist with a focus on how continuous human oversight matters long after launch.
From Data Quality to Agentic AI: What Works in Practice
This episode explores what organizations need to get right with their data, the difference between automation and generative AI, and how agentic systems can support real workflows. We break down practical steps for readiness, governance, and using tools like MCP servers and multi-agent models effectively.
Navigating AI Risk in Every Organization
In this episode of Human in the Loop, we sit down with Meredith from Applied Information Sciences to explore what it truly takes to bring AI into organizations responsibly. From securing sensitive data to navigating shadow AI, she shares practical guidance shaped by years of working with highly regulated industries. Together, we unpack the evolving role of AI policies, the importance of human‑in‑the‑loop safeguards, and how emerging agentic systems are reshaping expectations for security and governance.
Unlocking AI's Promise Responsibly With Saidot
In this episode of Human in the Loop, we sit down with Meeri Haataja, CEO and co-founder of Saidot, to explore what responsible AI governance really looks like inside organizations. From navigating regulatory frameworks to embedding transparency and accountability into AI development, Meeri shares practical insights for businesses at every stage of their AI journey. Whether you're scaling a startup or steering enterprise innovation, her advice on aligning technical ambition with ethical clarity is essential listening.
Why Trustworthy AI Starts With All of Us: Podcast Launch
In this very first episode, hosts Chris Huntingford and Ioana Tanase talk with Altrese Hawkins-Gopie about what responsible AI really means, why it matters for everyone (not just techies), and how we can all play a part in building trustworthy AI.