Machine learning (ML) is the science of helping computers discover patterns and relationships in data instead of being manually programmed. As ML involves more and more in our daily life, UX design for ML product/service not only focuses on better affordance for users, but how to construct a symbiosis relationship between users and ML systems.
In this talk, we will revisit early concept of UX design with machine learning - Licklider's man-computer symbiosis, to Mavin Minsky's architecture of human intelligence, finally to Affect Design by Dom Norman and Daniel M. Russell. Our focus will be how to stay focused on users with Human-Centered Machine Learning Design process, and how to design AI/ ML assistant experience for IoT product/service.
Han-Shen Chen is an award-winning UX design lead at Google, foundation & home intelligence team, who has extensive experiences in UX/product design with machine learning. He recently completed the 2018 Google ML Incubator Program, and now also works with Google People and AI Research Team on several Human-Centered Machine Learning projects.
Before joining Google, he worked as Lead Product Designer at Microsoft, and Associate UX Design Director at IBM Watson, where he led several Watson cognitive system/virtual assistant design projects for global companies.
Related Lecture Experience:
Co-Instructor of Google Taiwan AI Bootcamp TensorFlow workshop 2018
Instructor of Google Taiwan Teacher AI Bootcamp 2018
Speaker of Microsoft AI Series 2017
Instructor of Microsoft AI Training Course 2017
Instructor of Parsons School of Design BFA course "Cognitive AI Interface"