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Vanishing Gradients

Episode 16: Data Science and Decision Making Under Uncertainty

Dec 14, 2022
JD Long, agricultural economist and quant, discusses decision making under uncertainty in data science, common mistakes, heuristics for decision-making, and the impact of cognitive biases. Topics include coupling data science with decision-making, model building, storytelling, and the intersection of cognitive biases.
01:23:15

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Enhancing decision-making with risk, uncertainty, and probabilistic thinking in data science.
  • Avoid outcome bias by focusing on decision quality, not just results.

Deep dives

Understanding Decision Making Under Uncertainty

Decision-making under uncertainty involves using knowledge of risk, uncertainty, probabilistic thinking, and causal inference to enhance data science and machine learning for better decision-making. Considering factors like risk, uncertainty, and simulation can improve decision-making processes.

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