Episode 18, feat. Alexander Siegenfeld

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 Give Epistik a follow and fill the following form: https://forms.gle/MSZwUEFm1kzMTuia6