What will Michaël Pilaeten be discussing?
The launch of the ISTQB CTAL-Agile syllabus
Generative AI is transforming how we design, build, and test software — but with this advancement comes a new category of risks: biased outputs, inconsistent behaviour, cultural blind spots, and unpredictable edge cases. These aren’t simply technical defects; they are quality failures that occur when systems aren’t tested with the full spectrum of real-world diversity in mind. In this talk, Romina Pierce, Head of Operations at Sixsentix and MBA in Compliance, Data Protection & IT, explores why Diversity, Equity & Inclusion (DEI) have become essential components of modern quality engineering.
Romina illustrates how many AI failures result not from poor coding but from narrow perspectives during design and testing. Homogeneous teams often miss cultural nuances, alternative user behaviours, linguistic variations, accessibility needs, or fairness considerations. For testers and quality engineers, this creates an opportunity: DEI-driven thinking expands test coverage and exposes risks that traditional methods overlook.
This session examines where bias enters AI systems — in training data, prompts, edge cases, and human feedback loops — and how diverse perspectives improve robustness, reliability, and user trust. Romina shows how DEI leads to more representative test scenarios, broader validation strategies, and higher-quality outcomes for intelligent systems.
Participants will also explore how GenAI shifts the meaning of “quality.” Instead of checking functional correctness alone, testing now must evaluate fairness, consistency, explainability, and inclusivity. Romina provides examples of how testers can integrate inclusive thinking into AI-focused test strategies, ensuring models behave predictably for all users — not just the majority.
The result is a fresh perspective on how DEI strengthens quality engineering: by reducing blind spots, uncovering hidden risks, and ensuring AI systems reflect the real world they serve.
