S4-E5: AI in UX Research: Invisible Bias
Send us Fan Mail Invisible Bias - Data Quality, Representation and AI Distortion We can analyse thousands of interviews, survey responses and behavioural data points in minutes. But what happens when the data is incomplete, certain voices are missing, or important nuances disappear during analysis? In this episode, Emmanuelle explores how AI can inherit, amplify and conceal existing biases in research, creating convincing insights that may not reflect the full complexity of human experience. In this episode: How data quality and representation shape AI-generated insights Why missing voices and minority perspectives matter How AI can distort qualitative and quantitative research The hidden biases in analytics, segmentation and predictive models Why human judgement remains essential when interpreting AI-generated findings Because AI can identify patterns, but researchers must still question what those patterns leave out. Masterclass series: The Influential Researcher 4th, 11th and 18th November Free Introductory session on the 7th October. For more information and to book your seat Code for community discount UXRC2026 Click HERE 📖 The UX Research Powerhouse, Vol. 1 — The Foundation of UX Research Strategic Leadership Launching in November 2025, A playbook and manifesto for research leaders, with a 365-day leadership roadmap, tools to measure impact, and a bonus chapter on AI. 📘 Get the book on Amazon: here Emmanuelle's LinkedIn Instagram






