But as more and more experiences are built with ML, it's clear that UXers still have a lot to learn about how to make users feel in control of the technology, and not the other way round. In the Google UX community, we've started an effort called "human-centered machine learning" (HCML) to help focus and guide that conversation. Born out of our work with UX and AI teams at Google (and a healthy dose of trial and error), these points will help you put the user first, iterate quickly, and understand the unique opportunities ML creates. When doing user research with early mockups, have participants bring in some of their own data -- e.g. This can result in "conspiracy theories" where people form incorrect or incomplete mental models of a system and run into problems trying to manipulate the outputs according to these imaginary rules.