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.