UX Research Club

S4-E5: AI in UX Research: Invisible Bias

• Season 4 • Episode 5

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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.

 

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