Episode 18, feat. Alexander Siegenfeld

Epistik

TIMESTAMPS

• 2:35 Natural Scientists vs. Social Scientists in Complexity Science
• 8:29 Alex’ paper about elections
• 27:00 Professor Friston’s work in relation to Complexity Science
• 36:13 Can data be to weak to be useful?
• 40:35 Complexity Science in relation to philosophy and empiricism vs. rationality
• 46:29 What is the hardest thing in your work?
• 55:38 Successful people in academia
• 1:02:00 Circles & Loops
• 1:05:00 Measuring success
• 1:10:30 Are religions circular?
• 1:17:09 Language compression and emotion transfer devices
• 1:21:00 Meta-talk
• 1:24:29 Why is it hard to talk about ”deep things”?
• 1:28:22 The nature of learning
• 1:31:30 Memory
• 1:36:50 A subagent in our embodied cognition that is ”higher” than us?
• 1:49:11 What advice do you have for younger students?

Intrested in CS? Award-winning intro to Complexity Science by Alex: https://www.hindawi.com/journals/complexity/2020/6105872/

Mentioned resources:

• https://en.wikipedia.org/wiki/The_Structure_of_Scientific_Revolutions (Note from Alex: It seems less original now than at the time it was written)
• The Master and His Emmissary by Iain McGilchrist
• Another book recommended by Alex: I and Thou by Martin Buber (he recommends the translation by Smith)
• The review article in Nature Physics: https://arxiv.org/abs/1810.11489

Regarding proxies to internal goals, I’d recommend the following Medium article: https://adamahm.medium.com/data-linkage-visualization-for-assisting-policy-makers-d4ba40715693x

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