Kind and helpful Machine Learning through UX research

Meet Michelle Carney, a Machine Learning User Experience Researcher at Google. Join us as we learn how her careers in music, neuroscience, teaching, and machine learning have informed her ability to understand how people use Machine Learning tools, and provide better feedback to help make these tools more useful, helpful, kind, and inclusive of all types of user experiences. Resources: Visual Blocks for ML: https://goo.gle/3OfanzO Tone Transfer: https://goo.gle/3On9xku PAIR Guidebook: https://goo.gle/3Mx4Gff Machine Learning and UX (MLUX) Meetup Resource: https://goo.gle/mluxresources What is Machine Learning + UX?: https://goo.gle/42KWHB3 Stanford d.school on Designing Machine Learning: https://goo.gle/3OeRaOJ TensorFlow website → https://goo.gle/3BwLZSN Michelle Carney Links Twitter: https://goo.gle/3WfxMDc Linkedin: https://goo.gle/432u0PG Machine Learning and UX (MLUX) Meetup Resources: https://goo.gle/mluxresources What is MLUX?: https://goo.gle/42KWHB3 MLUX twitter (@mluxeetup): https://goo.gle/436wGMo MLUX meetup (you can see all of our past talks here!): https://goo.gle/41QpMts MLUX youtube (all of our past recordings!): https://goo.gle/42Ipt5a MLUX linkedin company page: https://goo.gle/45c5oWM Guest bio: Michelle Carney is a Computational Neuroscientist turned User Experience (UX) Researcher, whose practice focuses on the intersection of Data Science and UX. Currently a Senior UX Researcher on Google’s Tensorflow Team, Michelle's projects focus on combining Machine Learning and UX. Her work includes Magenta’s latest Tone Transfer project and People + AI Research team. Outside of work, Michelle organizes the Machine Learning and UX Meetup, and teaches at the Stanford d.school on Designing Machine Learning.