""UX in AI" has become one of the most confusing buzzwords in our industry. Jakob Nielsen has famously talked about how UX is desperately needed for AI, but few can define what this means (or how to do it). Is it about designing chat interfaces and chatbots? Is it about working with algorithms or vibe coding? Is it about using Replit and Bolt instead of Figma?"
"The confusion is understandable. When people say "UX in AI," they're usually describing a collection of loosely related activities without a unifying framework. However, there is an existing AI use case that not only cuts through ambiguity but also demonstrates a clear path for UX designers to achieve these skills: digital twin modeling. "UX in AI" isn't an unimportant topic, but there might be a dozen different interpretations for what that means, such as:"
UX in AI has become an ambiguous label covering many activities, including chat interfaces, vibe coding, explainability, knowledge repositories, personalization, and conversational experiences. That breadth prevents mastery and leaves designers unsure which skills employers want. Digital twin modeling provides a concrete AI use case and a clear pathway for UX designers to develop applicable skills. The digital twin concept originated at NASA to monitor and maintain complex systems. Focusing on digital twins enables designers to bridge interface design, algorithmic understanding, and system modeling in practical, learnable ways. Learning digital twin workflows reveals measurable outcomes and design responsibilities within AI projects.
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