Google’s Michelle Carney talks on ways data science and UX can better collaborate.
Increasingly, AI and ML are shaping the way we build products and design experiences.
And increasingly, user-centric organizations will need to inject qualitative data into the creation of models, algorithms, and interactions.
In this webinar, Google’s Michelle Carney walks us through the “whys” and “hows” of making UX-driven machine learning more human.
Michelle has worked at the intersection of UX and ML for Amazon and Google, and has lectured on the topic at Stanford University's d.school. She's the founder of the MLUX Meetup and has worked as a Computational Neuroscientist, UX researcher and UI engineer.
Ben is the product evangelist at dscout, where he spreads the “good news” of contextual research, helps customers understand how to get the most from dscout. He has a doctorate in communication studies, studying “nonverbal courtship signals”, a.k.a. flirting. No, he doesn’t have dating advice for you.