Prof. Dr. Anna Lea Dyckhoff

 

Many of the jobs we will have in a few years may not exist yet. AI is changing not only how we work, but also what it means to learn, understand, and develop expertise. Research can be summarized instantly, ideas produced on demand, and customer journey maps generated automatically. But what happens when we start removing the human process that happens along the way?

 

“In my work with students, I see how much learning happens when things are not quite so smooth: when interdisciplinary project teams encounter uncertainty, disagreement, unexpected user feedback on unfinished prototypes, or ideas that simply do not work as expected.”

 

When experiments fail and teams struggle, they encounter something that is impossible to generate instantly with AI: diverse perspectives, the emotions of real conversations, the need to negotiate what matters, and the challenge of finding alignment. Through this process, they gradually develop judgment about what meaningful outcomes might be.

 

This talk explores where efficiency creates real value, and where a little friction, uncertainty, and even slowness in the process help us understand what we are actually trying to solve. Because sometimes the messy process is not standing in the way of the solution. It is part of the solution.

 

If UX is primarily a set of deliverables, AI can produce many of them remarkably quickly. If UX is an approach to understanding, learning, and navigating uncertainty, the process becomes more important, not less.

 

LinkedIn: https://www.linkedin.com/in/anna-lea-dyckhoff-19539714/