#IamthefutureofAI: Michelle Carney
In this blog post, we feature Google’s Senior UX Researcher, Michelle R. Carney as she reveals interesting details about how she made her way in machine learning and user experience, the specific issues she encounters on a daily basis, and the barriers she overcame throughout her career. She also shares her thoughts on the importance of equity and diversity plus she shares sensible advice for individuals interested in making a positive impact within the AI space.
This interview is part of Women in AI Ethics (WAIE)’s “I am the future of AI” campaign launched with support from the Ford Foundation and Omidyar Network to showcase multidisciplinary talent in this space by featuring career journeys and work of women as well as non-binary folks from diverse backgrounds building the future of AI. By raising awareness about the different pathways into AI and making it more accessible, this campaign aspires to inspire participation from historically underrepresented groups for a more equitable and ethical tech future.
Can you share an incident that inspired you to join this space?
When I was working in machine learning (ML), it was rare that we thought about the holistic experience of the users. As we move towards a future where ML is ubiquitous, it is important that we also consider who are we designing this future for, and who gets to participate in this future. As a part of my practice as a User Experience (UX) Researcher on machine learning, I advocate for our users and to take on the challenge to redesign machine learning features that are radically different than what we’ve previously seen.
How did you land your current role?
I kept being turned down for roles in ML or UX because I do both ML and UX — as one hiring manager told me “If you do both ML and UX, you must not be good at either!”
What?! I got incredibly lucky and Amazon took a chance and hired me as the first ML and UX double hire, and from there I’ve paved my career in being a UXR for ML — mostly doing conceptual testing of ML models before they’re built.
What kind of issues in AI do you tackle in your day-to-day work?
I primarily work on the approachability and accessibility of ML. Some of my recent projects include Tone Transfer and TensorFlow Lite for Microcontrollers. I also teach at Stanford School of Design (d.school) on Designing Machine Learning.
If you have a non-traditional or non-technical background, what barriers did you encounter and how did you overcome them?
Technically, my undergrad degree is in Molecular and Cellular Biology and Cognitive Sciences, and my practical expertise was in building Neural Networks. But, because I “lacked a CS degree” I was denied ML and Data Science jobs. I was able to overcome this by finding people who believed in the work I do and supporting each other. I am incredibly fortunate because of the women who came before me and helped me get the role I have today.
Michelle R. Carney is the Senior UX Research at Google. She’s the Founder of Machine Learning and UX Meetup, a mix of data scientists, designers, machine learning scientists, PMs, and more excited about creating a future of human-centered smart products. She’s also a member of FeministAI and a former Fellow of the Algorithmic Fairness and Opacity Group at UC Berkeley.
