This article critiques the flawed reliance on generative AI and superficial research methods that prioritize speed over quality. It argues that these approaches lead to confirmation bias and missed opportunities for real problem-solving, ultimately transferring responsibility rather than addressing underlying issues. The author emphasizes the importance of understanding the systems we work in and recognizing genuine needs versus mere wants.

Generative AI, particularly in the form of digital twins, can enhance user research efficiency by simulating individual behaviors and preferences based on personal data. Digital twins can predict responses for specific individuals and reveal broader population trends, although ethical considerations surrounding consent and bias must be carefully addressed. As the technology evolves, it holds potential for transforming UX research practices.