Machine Learning Fairness
Type: Keynote / Breakout Talk
Time: 25min - 45min
Level: Beginner
Audience: All
As an AI-first company, Google aims to develop the benefits of machine learning for everyone.
Building inclusive machine learning algorithms is crucial to help make the world’s information universally useful and accessible.
ML fairness is a critical consideration in machine learning development. This session will present a few lessons Google has learned through our products and research and how developers can apply these learnings in their own efforts.
This session will enable developers to proactively think about fairness in product development.
You can find a video of this talk here: https://talks.codemotion.com/machine-learning-fairness---what-can-we-
About the Author
Lee Boonstra is an AI Software Engineer & Advocate in the Google Cloud Office of the CTO (Applied Innovation Factory). They specialize in secure multi-agent systems, frontier LLMs, and voice technology. Lee is the author of reference books for O'Reilly and Apress, and the viral Kaggle/Google Prompt Engineering whitepaper.