Complex Systems Summer School 2016-Panel Questions

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Complex Systems Summer School 2016

Please post questions you might have for our panel. Panel includes Simon DeDeo, Josh Grochow, Elly Power, Jessica Flack

  1. Compared with machine learning or data mining, we may feel that complex systems have less practical applications in enterprise development. How to better adopt the theories and profits of complexity into practical production and make this field better as a demand-driven research, as well as research guided production?
  2. Systems like social activities and economic activities are quite complex. The trends of agent-based modelling usually simplifies or ignores many mechanisms and conditions, which are far away from real situations. Can we use these "toy models" to solve real world financial crisis, fight against terrorist organizations or protect civil rights?
  3. How do you distinguish between research you'd consider to be complexity science or not?
  4. Is it true that doing interdisciplinary research makes it harder to find an academic position? What advice do you have looking for academic jobs when you sit between disciplines (besides, of course, getting a position at SFI).
  5. A paraphrasis of an Einstein's quote was used in one of our lectures: “Make things as simple as possible, but not simpler.” When is a toy model too simple? When is a data analysis too simple?
  6. The movement of the planets looked pretty complex until Newton showed up. How do you identify a successful theory coming out of complexity research, and how do you satisfy yourself that a phenomenon can't be explained with simple dynamics yet to be uncovered? Is positing a "complex theory" a cop-out?
  7. Complexity science has roots in the physics. In applying its tools and methods in social science, what kinds of change of perspectives are needed? Can you show some examples?
  8. Echoing to the previous question, I argue that complexity paradigms were simultaneously discovered and used in the social sciences (e.g. in theoretical and quantitative geography). What surely came from physics are methods and tools, but not all paradigms shifts observed in social sciences, and many thinkers of complexity have a background in humanities (e.g. Edgar Morin, Paul Bourgine). My question is therefore, do you think it is possible (and desirable) to avoid the over-quantification trap that would consist in applying blindly physics methods to social science subjects, and forget all qualitative and theoretical background ? In other words, what are the conditions of equalitarian and fruitful interdisciplinary collaborations between humanities and hard sciences ? Could Complex System Science become a "third way", transcending the misleading opposition between quantitative and qualitative ?