#373 Melanie Mitchell: AI, Complex Systems, Human Cognition, and Algorithms

Oct 2, 2020

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Dr. Melanie Mitchell is the Davis Professor of Complexity at the Santa Fe Institute, and Professor of Computer Science at Portland State University. Her current research focuses on conceptual abstraction, analogy-making, and visual recognition in artificial intelligence systems. Dr. Mitchell is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her book Complexity: A Guided Tour (Oxford University Press) won the 2010 Phi Beta Kappa Science Book Award and was named by Amazon.com as one of the ten best science books of 2009. Her latest book is Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux).

In this episode, we talk about AI. First, we ask if we are close to human-level AI, and also if the Turing test is really that relevant. Dr. Mitchell explains deep learning and neural networks, evolutionary computation, complex systems, and genetic algorithms. Then we get into conceptual abstraction, analogy-making, and visual recognition. We also discuss if AI systems should have built-in features (innate features). Finally, we talk about the impact that AI already has on our lives.

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