The Theory of Anything Episode 26: Is Universal Darwinism the Sole Source of Knowledge Creation?
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Jul 12, 2021 This episode examines whether the Universal Darwinism algorithm applies to knowledge creation in AI and machine learning. It explores examples like Gradient Descent and the Naive Bayes Classifier, questioning their relationship with variation and selection. Counter examples challenge Donald Campbell's prediction about evolutionary algorithms being the sole source of knowledge creation. The podcast also delves into the theory of critical rationalism and the value of testable explanations. Overall, it highlights the exciting epistemological problems that Machine Learning presents.
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Introduction
00:00 • 2min
Artificial Intelligence and Knowledge Creation
01:34 • 22min
The Impact of AlphaGo on Human Gameplay and Knowledge Creation
23:33 • 24min
Gradient Descent and the Universal Darwin Algorithm
48:01 • 9min
Explaining the Naive Bayes Classifier and its Applications
56:45 • 2min
Challenging Campbell's Bold Prediction
59:01 • 15min
The Theory of Critical Rationalism and the Value of Testable Explanations
01:14:12 • 2min
Embracing the Best Explanation
01:16:14 • 8min