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Episode 23: Statistical and Algorithmic Thinking in the AI Age

Vanishing Gradients

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Algorithmic Fairness, Causal Inference, and Decision Spaces

The chapter explores Birxin's paradox, talent vs. attractiveness in celebrity culture, and statistical thinking in algorithmic fairness. It delves into the complexity of algorithmic fairness, emphasizing transparency, scalability, and decision-making opacity. Further, it discusses the significance of causal inference in decision-making processes and the challenges in applying causal methods, highlighting the importance of understanding causal relationships for accurate interventions.

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