Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI

Melanie Mitchell is a professor of computer science at Portland
State University and an external professor at Santa Fe Institute.
She has worked on and written about artificial intelligence from
fascinating perspectives including adaptive complex systems,
genetic algorithms, and the Copycat cognitive architecture which
places the process of analogy making at the core of human
cognition. From her doctoral work with her advisors Douglas
Hofstadter and John Holland to today, she has contributed a lot
of important ideas to the field of AI, including her recent book,
simply called Artificial Intelligence: A Guide for Thinking
Humans.


This conversation is part of the Artificial Intelligence
podcast. If you would like to get more information
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Episode Links:
AI: A Guide for Thinking Humans (book)


Here’s the outline of the episode. On some podcast players you
should be able to click the timestamp to jump to that time.


00:00 – Introduction
02:33 – The term “artificial intelligence”
06:30 – Line between weak and strong AI
12:46 – Why have people dreamed of creating AI?
15:24 – Complex systems and intelligence
18:38 – Why are we bad at predicting the future with regard to
AI?
22:05 – Are fundamental breakthroughs in AI needed?
25:13 – Different AI communities
31:28 – Copycat cognitive architecture
36:51 – Concepts and analogies
55:33 – Deep learning and the formation of concepts
1:09:07 – Autonomous vehicles
1:20:21 – Embodied AI and emotion
1:25:01 – Fear of superintelligent AI
1:36:14 – Good test for intelligence
1:38:09 – What is complexity?
1:43:09 – Santa Fe Institute
1:47:34 – Douglas Hofstadter
1:49:42 – Proudest moment