Complex Systems Summer School 2015-Panel Questions: Difference between revisions
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Please post questions you might have for our panel on June 19th. Panel includes Simon DeDeo, Mirta Galesic, Laurent Hébert-Dufresne, Christa Brelsford, and others to be announced shortly. | Please post questions you might have for our panel on June 19th. Panel includes Simon DeDeo, Mirta Galesic, Laurent Hébert-Dufresne, Christa Brelsford, and others to be announced shortly. | ||
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<ol> | |||
<li> Are there any universal principles that govern the generation of power-law distributions? </li> | |||
<li> Is complex systems science a discipline, toolset, mindset, or something else? How do you define complex systems science? </li> | |||
<li> What evidence do we have that understanding complex systems is a task the human mind is capable of? What if we reached the point where it's fundamentally beyond our comprehension?</li> | |||
<li> Interdisciplinary knowledge is valuable, but perhaps you need to be specialized to be useful to interdisciplinary work. Do you have thoughts on balancing these? </li> | |||
<li> Is the idea of a "generative social science" approach embedded in the use of complexity tools and framework for social phenomena? How can we make this idea useful, in particular when dealing with economics, which usually aims to generate predictions? </li> | |||
<li> "I believe there is a fourth law of thermodynamics, or some cousin of it, concerning self-constructing nonequilibrium systems, such as biospheres, in the cosmos, but cannot prove it" - Stuart Kauffman, former external professor at SFI. Where do you stand on this statement? </li> | |||
<li> Can complexity radically change the way we think about and manage socio-environmental systems? </li> | |||
<li> Shall qualitative data be always quantified? We have learned at CSSS that there is basically no real randomness, and that systems are sort of in need of noise anyway. So, if we not always have to quantify qualitative data, what other ways of approaching qualitative data there can be and for what problems in particular? </li> | |||
<li> Can you imagine a research project in Complexity Science, which would be based on qualitative data that was not quantified, but still approached systemically and stepwise? </li> | |||
<li> To an extent, complex systems science seems to be the search of complex systems "universals". In the lectures by Alfred Hübler, he talked about physical intelligence: the idea that physical complex systems "seek out" the optimal dissipation of energy sources (and self-organize by consuming). This leads to all sorts of thoughts about Life being there because it dissipates energy quicker than random systems do (and hence reintroducing a kind of teleology in nature, see for instance: [http://www.ler.esalq.usp.br/aulas/lce1302/life_as_a_manifestation.pdf Schneider and Kay (1994)]. Are there, or is there evidence for, such "universal" principles of non-equilibrium thermodynamics, or should these kind of ideas be taken with a grain of salt?</li> | |||
</ol> | |||
Revision as of 06:24, 19 June 2015
| Complex Systems Summer School 2015 |
Please post questions you might have for our panel on June 19th. Panel includes Simon DeDeo, Mirta Galesic, Laurent Hébert-Dufresne, Christa Brelsford, and others to be announced shortly.
- Are there any universal principles that govern the generation of power-law distributions?
- Is complex systems science a discipline, toolset, mindset, or something else? How do you define complex systems science?
- What evidence do we have that understanding complex systems is a task the human mind is capable of? What if we reached the point where it's fundamentally beyond our comprehension?
- Interdisciplinary knowledge is valuable, but perhaps you need to be specialized to be useful to interdisciplinary work. Do you have thoughts on balancing these?
- Is the idea of a "generative social science" approach embedded in the use of complexity tools and framework for social phenomena? How can we make this idea useful, in particular when dealing with economics, which usually aims to generate predictions?
- "I believe there is a fourth law of thermodynamics, or some cousin of it, concerning self-constructing nonequilibrium systems, such as biospheres, in the cosmos, but cannot prove it" - Stuart Kauffman, former external professor at SFI. Where do you stand on this statement?
- Can complexity radically change the way we think about and manage socio-environmental systems?
- Shall qualitative data be always quantified? We have learned at CSSS that there is basically no real randomness, and that systems are sort of in need of noise anyway. So, if we not always have to quantify qualitative data, what other ways of approaching qualitative data there can be and for what problems in particular?
- Can you imagine a research project in Complexity Science, which would be based on qualitative data that was not quantified, but still approached systemically and stepwise?
- To an extent, complex systems science seems to be the search of complex systems "universals". In the lectures by Alfred Hübler, he talked about physical intelligence: the idea that physical complex systems "seek out" the optimal dissipation of energy sources (and self-organize by consuming). This leads to all sorts of thoughts about Life being there because it dissipates energy quicker than random systems do (and hence reintroducing a kind of teleology in nature, see for instance: Schneider and Kay (1994). Are there, or is there evidence for, such "universal" principles of non-equilibrium thermodynamics, or should these kind of ideas be taken with a grain of salt?