Designing a Future with ML + UX
Sponsored by the Algorithmic Fairness and Opacity Group (AFOG)
Increasingly, AI and ML are shaping the way we build products and design experiences. How do we ensure that the ML products we build are designed by and for people? In this talk, Michelle will share the industry trends and resources she is seeing as an organizer of the Machine Learning and UX meetup, and best practices she uses as a UX Researcher at Google.
Michelle R. Carney is a user experience researcher at GoogleAI and a lecturer at the Stanford d.school. She is a computational neuroscientist turned UX practitioner who focuses on how data drives design decisions and how to design human-centered experiences for data science and machine learning. Michelle holds a master's in information management and systems from the UC Berkeley School of Information with a focus in data science and user experience research for UX. She is a former fellow at UC Berkeley's Center for Technology, Society & Policy (CTSP) and the Algorithmic Fairness and Opacity Working Group (AFOG). Michelle is also the organizer and founder of the popular Bay Area ML/UX Meetup.
