Intelligent Machine Age: Advancing Robotics, Automation, Semiconductors, and Next-Gen Space & Automotive Technologies

Maria Yolanda Bile Nlang Profile

Maria Yolanda Bile Nlang

Maria Yolanda Bile Nlang

Biography

Maria Yolanda Bil Nlang is an AI Engineer and founder of Brise, a Brussels-based startup focused on providing a responsible AI infrastructure and consulting for conversational AI systems. Before launching Brise, she worked at leading consulting firms such as EY and Cognizant, where she contributed to projects in HR analytics, customer intelligence, predictive modelling, and enterprise chatbot development.?Her work lies at the intersection of ethical AI, human-centric design, and using technology and data to drive business impact.

 

Research Interest

* AI Ethics & Responsible AI * Automated Testing for Conversational AI

Abstract

Responsible AI in the Age of Autonomous Agents As conversational AI systems evolve to become more autonomous and integrated into business operations, the need for trustworthy AI practices including safety, privacy, security, fairness, and transparency is more urgent than ever. These systems must be unbiased, explainable, secure, respectful of user privacy, and include human oversight to ensure they effectively address user needs. Yet today, privacy is often violated. Testing and evaluation frameworks for conversational AI remain insufficient or underdeveloped. Many companies still lack practical tools to validate their systems beyond surface-level performance metrics and safeguard filters. Meanwhile, academic research ? although valuable ? is often difficult to apply in real-world product environments. This presentation explores: * The risks of deploying AI agents without responsible AI foundations * The gap between academic theory and practical implementation * The need for more applicable, business-friendly frameworks for testing AI systems * Why measuring ROI and user impact should be part of every responsible AI strategy The idea is to give participants a clearer view of what effective testing for conversational AI systems should look like.