Modeling complexity / by Siobhán Cronin

When I trace culture and technology along an axis of certainty I see that we have a problem. We have not effectively examined how the constraints of our biology (tools of perception), psychology (cognition, including our over-dependence on linguistically-mediated thought), and cultural valuation of change restrict our ability to conceive, operationalize, carry out, and interpret data from research on complex systems.  

Meanwhile, we see scientific communities calling for a change, heralding the promise of the intersections of computational science and "classic" disciplines. Biology unfolds to computational biology, including new thinking emerging from systems biology and quantum biology. Neuroscience finds deeper rooting in computational neuroscience. Network theory in energy infrastructure births new mappings for efficiency . 

Complexity science has pressed onto the scene over the past decades as a valiant organizer of this conversation, urging us to address the central question, "How will the construction of our minds, and how they behave in linguistic, psychological, biological, and cultural realities, limit our ability (or perhaps willingness) to engage with complexity?" And calling us to dream, "How might we build new tools and models to correct for our inherited bias towards reductionism?"

My optimism has been stoked, and I'm ready to dive in.