Machine Learning Street Talk (MLST) cover image

Sara Hooker - The Hardware Lottery, Sparsity and Fairness

Machine Learning Street Talk (MLST)

00:00

Navigating AI Bias and Fairness

This chapter explores the complexities of AI research, particularly the impact of model compression and deep neural networks on data bias and fairness. It emphasizes the significance of recognizing the representation of protected attributes in datasets and how this influences model performance. The speakers advocate for innovative methods to identify and mitigate bias, highlighting the interconnectedness of interpretability, fairness, and data representation in machine learning.

Transcript
Play full episode

The AI-powered Podcast Player

Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
App store bannerPlay store banner
Get the app