Alternate Vision

Scientific reductionism has formed the basis of modern science where macroscopic properties are explained in terms of their microscopic elements (complex system is nothing but the sum of its parts). But often when explaining complex, dynamic systems that evolve over time - nature is a great example - reductionist thinking fails to capture the patterns emerging out of a multiplicity of simple interactions (the whole is more than the sum of its parts). And with this, comes the need to subscribe to a more holistic view of complex systems, that recognizes the probabilistic interactions of the constituent parts as integral to the rise of emergent orders. Brad Allenby, as always, provides some invaluable gyan on this topic .

"Observation and experiment are no longer the foundations of much cutting edge science and technology. The complex systems characteristic of the anthropogenic Earth -- such as climate change, the tension between environmental protection and development, food versus biofuels, emergent technology systems in the information and communication technology, nanotechnology, biotechnology, robotics and cognitive science domains, and water systems in globalized market structures -- cannot be understood merely by studying more and more about smaller and smaller subsystems, for it is precisely the emergent behavior of these systems qua systems that is the issue.

In short, while many scientific questions remain approachable through observation and experimentation, such simple methods are inapplicable to the complex systems which increasingly are our major challenges, and the tools we must use in such instances -- computer techniques and modeling -- raise far different validation and completeness issues than contemplated by the current scientific culture.

Environmentalism, sustainability, and science itself are increasingly trapped in a dysfunctional time warp, vesting the certainty of reductionist scientific method in new tools and frameworks that cannot justify such confidence. The problem is not inherent in the models, nor can we wish away complexity. Rather, the problem is with ourselves, in that we fail to recognize the growing mismatch between the putative authority we grant our tools, and their inevitable partiality and contingency given the complexity of the systems we attempt to parse." - Brad Allenby on Science and the 'Routes to Truth'