The future we deserve blogathon – reflections on “A systemic revolution, or, the need for a post-scientific approach”

By admin, on August 19th, 2010

This post is a response to Vinay Gupta’s call to blog on submissions to The future we deserve.

The following is the contribution from Andy Novocin, my reflections upon it are below:

A systemic revolution, or, the need for a post-scientific approach

I remember learning about the scientific method through an example in a textbook. The example was that of spontaneous generation in which someone tested the statement that rotting meat generates flies. They did this by placing rotting meat in a sealed jar and directly observing that flies never emerged from the meat. From this example we were supposed to learn about attacking a problem through the process of observing, questioning, isolating out a testable hypothesis, experimenting, and finally concluding the validity of the hypothesis. The aspect that I want to focus on in this piece is the separation of aspects of a problem. I believe that the scientific approach of analyzing a problem by breaking it down into manageable chunks is very pervasive in our world, and exists in many aspects of our culture. I see ripples of this divide and conquer approach in many facets of industrialized modern life: in the production world via the separation of labor, in the academic world with the near-infinite specialization of fields, the artistic realm in which the separation of elements in a viewing experience are abstracted into various components (think the chain from impressionists through cubists through object-less art into formless art and beyond), we analyze food in terms of it’s constituent nutrients, and we educate students in specific and separated subject matters from a young age right on through to post-graduate work. This cultural shift formed a type of revolution, in the sense that a new mode of seeing the world emerged to challenge the old and then traditional modality of knowledge. This new scientific modality allowed better predictive models which could be generated, tested, and improved. A working predictive model leads to confidence in the approach that generated the model and this helps to fuel these generational changes and slowly replace the old models.

In the future that we deserve I envision a dethroning of the divide-and-conquer approach by a more systemic mode of thought. We are witnessing real-time worldwide inter-connectedness and its impacts. I suspect that this connectedness will be echoed in a new language and paradigm for combining previously separate parts of scientific models for problem solving. The systemic approach to problem solving will be to see and model the inter-relationships of aspects that science/abstraction/industry has separated. We are discovering just how connected and complex things really are, and new models must be formed in light of this. Such new models will require more synthesis as opposed to separation. Just walk into the mathematics section of any university library and see hundreds of books which are only readable by a handful of experts in a highly specific field, I suspect the same is true in many core sciences. We are producing specialists who are becoming increasingly marginalized, what we don’t have are people to glue together the disparate parts.

Many important and interesting problems are not attackable by a divide-and-conquer approach. For instance the growing gap between the rich and the poor, the over-usage of our planet’s non-renewable resources, inter-nation and inter-cultural conflicts, or appropriate and adaptive education. We are just now beginning to develop the language infrastructure to even describe the extent of these problems largely as a matter of necessity. As we address more complex problems via synthesis and system thinking we will form the way for new approaches and paradigms by which inter-connectedness is understood, modeled, and more accurate predictions are made. Such models could bring confidence and such confidence could fuel the new modality by which future generations see knowledge. This modality would of course be echoed in many aspects of life and culture in unforeseeable ways, leading to better insights and thus wider or more refined approaches and the positive feedback loop of new ideas would carry the process. Think from the top-down and bottom-up about how to see and describe interconnected aspects of problems and you’ll be working towards solving the systematic problems we face and unlocking new insights into the world that the old approach is unequipped for.

I can relate very closely to the phenomenon of compartmentalisation that Andy describes. Indeed, I am one of those to whom he refers, one of the multitude trained in great depth in a tiny subsection of a subsection of science. I have always been fascinated by the concept of the true polymath, the person able to stand astride the many disciplines of science and the humanities, understanding all. The depth and wealth of human knowledge precludes such status from modern thinkers, but I think that it is alo true that the habits of science and scientific enquiry introduce a needless barrier between the layman and comprehension in most scientific fields. I say this not only as one who has experience of penning journal papers obscure to all but a few dozen readers, but as one who considers himself relatively well versed across many fields, and who often wades into specialisms taht are not my own trying to understand and advance in them.

Andy has captured some of the difficulties presented by this compartmentalised approach to thought, but I think could have even more firmly expressed the potential gap between this compartmental understanding and a return to systemic thinking. The language of combining models invokes the development of behemothic combinations of arcane knowledge, the computerised association of the sub-disciplines that have grown so esoteric. There is a risk that even as one tries to move beyond analysis at a level of detail beyond the capacity of the non-expert to understand, one internalises the mysteries you seek to overcome. Economic models of the world, growing with more and more modules and details, are an excellent example of this – it is too easy for the workings of a systemic model to become mysterious both to the generalist doing the modelling, who does not understand the detail, and to the specialist in the field, who does not understand how her data is applied.

This is not the approach to modelling that, I think, Andy intends for us to imagine. His version, I think, puts human ingenuity and intuition back at the centre of the enterprise – it demands a school of scientific publishing in which references to past work are included to elucidate rather than disguise meaning, in which we reignite some of the 19th century’s ability to write ground-breaking science in beautiful prose. Policy makers, politicians, the decision makers at the centre of the web spun by modern data collectors, have been too often ill equipped to judge and act on it. Witness the level of denial of the existence of climate change among politicians compared to scientists. The education of the future might do well to recognise that a scientific and numerical literacy is not an alternative but a complement to a rounded ability to argue and comprehend prose.

The more the thought leaders of tomorrow are equipped not only with sophistry but with the tools to examine, question and synthesise the overwhelming streams of data available to them, the more they will be able to construct the intelligent systemic models Andy yearns for. To return full circle to the premise behind this blog, the development of these systemic models might just empower the thinker to challenge it’s own assumptions, and reach better conclusions.