Welcome to Decoding Causality, where conversations unravel the mysteries of cause and effect. Inspired by the ideas explored in The Book of Why, this podcast delves into the fascinating world of causal reasoning, counterfactuals, and the science of asking ‘why.’ Each episode breaks down complex concepts into accessible and thought-provoking insights. Perfect for researchers, students, and curious minds, this podcast offers a fresh take on decision-making and discovery.
Decoding Causality
Claim This Podcastby Amir Rafe
5.0(1 reviews)
11 episodes
Updated Daily
Accepts GuestsHas Sponsors
44
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality49
Social0
YouTube66
Engagement32
Podcast Overview
Welcome to Decoding Causality, where conversations unravel the mysteries of cause and effect. Inspired by the ideas explored in The Book of Why, this podcast delves into the fascinating world of causal reasoning, counterfactuals, and the science of asking ‘why.’ Each episode breaks down complex concepts into accessible and thought-provoking insights. Perfect for researchers, students, and curious minds, this podcast offers a fresh take on decision-making and discovery.
Language
🇺🇲
Publishing Since
2/21/2025
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44
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality49
Social0
YouTube66
Engagement32
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Recent Episodes
April 21, 2026
Closing the Loop: What We Learned About Causality
<p><strong>Season 1 - Extra: Wrap-up of The Book of Why</strong></p><p>Welcome back to the <strong>Decoding Causality</strong> podcast after a long hiatus! As Season 1 comes to a close, we are wrapping up our journey by summarizing the entirety of The Book of Why.</p><p>In this episode, we explore the convergence of big data, artificial intelligence, and the age-old question of “why.” While machines have become astonishingly good at pattern recognition, they still struggle with the essence of human understanding: causal reasoning. We reflect on how the Causal Revolution challenged traditional statistics and ask whether AI can ever truly emulate human curiosity and imagination.</p><p>What does it take for machines to not only predict outcomes but explain them? Can we teach future robots to use causal theories to learn just like humans? Join us for a thought-provoking finale as we relate these concepts to real-world scenarios, from medicine and public policy to transportation engineering and AI, and examine the future of causal thinking in a world increasingly driven by data and algorithms.</p><p>Stay tuned, because we will be back with Season 2 soon!🔍 <strong>Stay Connected</strong></p><p>📧 Email: <a href="">amir.rafe@txstate.edu</a></p><p>🌐 Website: <a href="https://pozapas.github.io/">https://pozapas.github.io/</a></p><p>🔗 LinkedIn: <a href="https://www.linkedin.com/in/amir-rafe-08770854/">https://www.linkedin.com/in/amir-rafe-08770854/</a></p><p>🐦 X: <a href="https://x.com/rafeamir">https://x.com/rafeamir</a></p>
April 21, 2025
S1E10. Can AI Ask Why? The Final Frontier of Causal Reasoning
<p><strong>Season 1: The Book of Why</strong></p><p>As Season 1 comes to a close, we explore the convergence of big data, artificial intelligence, and the age-old question of “why.” While machines have become astonishingly good at pattern recognition, they still struggle with the essence of human understanding: causal reasoning. In this episode, we reflect on how the Causal Revolution challenged traditional statistics and ask whether AI can ever truly emulate human curiosity and imagination.</p><p>What does it take for machines to not only predict outcomes but explain them? Can we teach AI to distinguish correlation from causation—or even reason about counterfactuals? Join us for a thought-provoking finale as we examine the future of causal thinking in a world increasingly driven by data and algorithms.</p><p>🔍 <strong>Stay Connected</strong></p><p>📧 Email: <a href="" target="_blank" rel="ugc noopener noreferrer">amir.rafe@usu.edu</a></p><p>🌐 Website: <a href="https://pozapas.github.io/" target="_blank" rel="ugc noopener noreferrer">https://pozapas.github.io/</a></p><p>🔗 LinkedIn: <a href="https://www.linkedin.com/in/amir-rafe-08770854/" target="_blank" rel="ugc noopener noreferrer">https://www.linkedin.com/in/amir-rafe-08770854/</a></p><p>🐦 X: <a href="https://x.com/rafeamir" target="_blank" rel="ugc noopener noreferrer">https://x.com/rafeamir</a></p>
April 8, 2025
S1E09. Tracing the Invisible: How Causes Travel Through the World
<p><strong>Season 1: The Book of Why</strong></p><p>What lies between cause and effect? In this episode, we delve into the concept of <strong>mediation</strong>, the hidden pathways that connect actions to outcomes. From James Lind’s battle with scurvy to groundbreaking diagrams in intelligence research, we explore how scientists uncover the mechanisms that explain how and why effects occur. When we ask, “Does Drug B prevent heart attacks?”, we’re really asking: “Through what chain of events?” Understanding these chains can mean the difference between truth and tragic error.</p><p>We also reflect on the legacy of Barbara Burks—a pioneering woman in science who challenged the norms of her time by visualizing the complex threads of nature and nurture through path diagrams, decades ahead of her field. Why do some causes work directly while others weave through mediators? And how can this knowledge transform scientific policy, medicine, and artificial intelligence?</p><p>Join us as we climb deeper into the Ladder of Causation and learn to trace the steps between action and consequence.</p><p>🔍 <strong>Stay Connected</strong></p><p>📧 Email: <a href="">amir.rafe@usu.edu</a></p><p>🌐 Website: <a href="https://pozapas.github.io/">https://pozapas.github.io/</a></p><p>🔗 LinkedIn: <a href="https://www.linkedin.com/in/amir-rafe-08770854/">https://www.linkedin.com/in/amir-rafe-08770854/</a></p><p>🐦 X: <a href="https://x.com/rafeamir">https://x.com/rafeamir</a></p>
11 total episodes available
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Frequently asked questions
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- What is Decoding Causality?
- How often does this podcast release new episodes?
This podcast updates daily.
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This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
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No, this podcast does not typically feature guests.
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