Design for Context with Machine Learning
summary
An explanation of how machine learning models work and what questions they can answer, aimed at designers; it compares design and ML as pattern-recognition practices and argues for designers learning to use AI as a tool. It describes Booking.com’s practical challenge of balancing information density across 43 languages and 220+ countries, and gives real examples of using design to enable and surface ML-driven personalization without adding product complexity.
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chapters (6)
- 0:00Introduction
- 3:53Empathy in design
- 8:10What is machine learning
- 13:29Empathy and patterns in practice
- 16:44Booking date recommendation
- 19:43Q&A
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