
What Machine Learning Teaches You About User Behaviour (If You Let It)
Working on ML-driven products changed how I think about users. Not as groups with shared preferences, but as people in states. Here’s what that shift means for how you design.
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Working on ML-driven products changed how I think about users. Not as groups with shared preferences, but as people in states. Here’s what that shift means for how you design.

Eighteen months of iteration and the product is a patchwork of decisions nobody fully owns. Constant iteration without direction isn’t learning. Here’s why the best design work starts slow.

AI can process 40 interview transcripts in 20 minutes. What it can’t do is tell you whether you asked the right questions, or catch what a participant didn’t say. Here’s where the line actually sits.

Nobody tells you about the leadership tax when you get promoted. The meetings, the reviews, the resourcing conversations. None of it is the work. All of it is necessary. Here’s how to manage the cost.

Some of the best designers I’ve worked with were nearly invisible. Not because they weren’t contributing, but because they let the work speak for itself. Here’s why that’s a leadership problem, not a them problem.

AI in automotive isn’t coming. It’s already here, already shaping what people experience, already making decisions most users don’t know are being made. My chapter in AI Everywhere, Vol. 1 asks who’s really in control.

Twenty-six authors. Fourteen countries. One shared conviction that the AI conversation needs more voices in it. Here’s what the SheWritesAI community built, and why the model itself is worth paying attention to.

Twenty-six authors. Fourteen countries. One book that asks what AI is actually doing to the world we live in. AI Everywhere, Vol. 1 is out now, and I’m proud to be part of it
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