Fairness in Machine Learning with Hanna Wallach - TWiML Talk #232
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Exploring the Mismatch between Industry Practitioners and Academic Literature in Machine Learning Lifecycle
This chapter delves into the differences between academia and industry in terms of data collection and model control within the machine learning lifecycle. It explores how industry professionals often have more influence over data collection but less control over models, emphasizing the importance of resources for addressing fairness, accountability, and transparency in machine learning.
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