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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Importance of Fairness in Machine Learning
This chapter emphasizes the significance of fairness in machine learning to prevent unintended harm and discrimination. It discusses examples of biases and harms that can occur in various machine learning applications, including issues with interpretability and transparency. The chapter also explores strategies for overcoming fairness challenges by involving diverse stakeholders and integrating fairness metrics in model training.
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