Can science learn to read “pattern language”…?

This post is a section of my report titled “Approaching 30 days from the 40th Anniversary” on attending the quite exciting 2012 40th Anniversary meeting on the Meadows and Randers authored Club of Rome “Limits to Growth” study.   The excerpt is on the deep reasons why the science, as solid as it still seems to be, isn’t widely accepted.    Science is still struggling to find a comfortable way to discuss natural systems whose innovative systems are housed internally, and so largely hidden from view.


I think the real reason the public as well as most of the scientific community is largely ignoring the rather well established hard limits to growth, is that it presents the scientific community a new problem it hasn’t yet learn how to deal with.   It has yet to find a good way to make sense of self-designing and self-managing systems, like weather systems, cultures and economies, that have working designs that are  hidden internally, displaying organization much too complex and localized to be determined by external forces.

Science is built around identifying how one thing controls another,
not how to study the  patterns of uncontrolled systems and how they became designed to work by themselves.

So science is naturally somewhat lost in discussing how they work, having no model for what are better described as “opportunistic” than “deterministic” systems.   Though both climate and economies display highly inventive systems, they do still necessarily operate within what traditional science can define as their natural bounds.     Climate is still fundamentally a complex pressure-temperature behavior, of unchanging deterministic processes following fixed laws of science.

Economies though, are able to be far more creative, and move the boundaries of what is possible by innovative design, much further than the push and pull forces of the weather can.   It has given traditional science very little to anchor reliable theory on, except as in the Limits to Growth study, fixing boundary conditions and experimenting with multiple options.  Still, because economies do display deeply creative behavior, constantly inventing new ways to use energy as a normal rule, that natural science still lacks a widely accepted way to study them as natural systems, adds uncertainty for others to what anyone might say about them.

Constantly inventing new organization is just what natural systems ‘do’.   It lets economies as well as ecologies create new kinds of organization and uses for their energy resources, making formerly useless things highly profitable often enough.   Using the profits as returns on energy investment to grow by building more innovations.   It’s complicated by not being a ‘numeric’ process, though we can see it through our measures.   It’s an “organizational process”, of fitting complementary parts together, more amenable to study as a “pattern language” of “design elements” than equations.

The rigid limits of any mode of productivity still do exist, of course, but as limits of the organizational processes science has yet to find a way to study.   Those limits are still determined by the earth and the organization of the internal and external systems that any innovation depends on, but with each new innovation there are new unknown limits.  It leaves a stubborn problem for traditional scientific prediction.   What seems to work better is a language of observing such systems to see when their own organization is being stretched.

Natural systems generally link individual units of organization in an open rather than deterministic environment, each with its own internal organization that emerged during its own development, creating a serious mis-match between the natural design and the information an observer could collect, and with the kinds of behaviors that can be emulated by equations.

That big problem for science also makes a big and very fascinating subject of study, that science has quite generally not realized is there, having avoided the study of self-designing and managing systems in general.    Self-designing ans managing systems not only seem to develop by themselves, but to have their “works” hidden internally within the boundaries of their design, as an individual system maintaining internal organization for responding to external systems, like we see in living systems as a special case in point.  

So their behaviors are not really determined externally, as if by the information outside observers can collect the way deterministic systems can be modeled.    They have to be studied as negotiating their own behaviors between independently organized internal and external systems, quite an unusual posture for traditional science.   I means outside observers normally have no information on their critically important internal designs a behaviors.   How that becomes a fascinating subject of study is recognizing their natural boundaries define enormous holes in our information about how things work, a true gold mine for new science.

How to begin studying the thermodynamics of energy crossing boundaries of self-organization is a very basic but important step, and the subject of my longer research paper last year,  System Energy Assessment (SEA).   By aggregating the data not by our arbitrary categories for how we collect it, but by how the system’s parts are connected to work together, produces a profoundly meaningful new result, the ability to study such systems as individual wholes.

There are many ways to identify the natural boundaries of self-managed systems,  as closely interconnected parts distinct from an otherwise passive environment, for example.   When a concentration of energy uses is notably more complex than the external forces on it, you identify the system by its distinctive “miss-match in variety”.   You can confirm such identifications with tracing how they developed, always displaying “S” curves of accumulative design over time, with recognizable processes for generating an energy surplus to be invested in expanding the system producing it.   Those identifiers locate the heart of the working system, and how it is organized to work as a whole.   You then understand what you are looking at, as you see them:

  • responding to environmental conditions in uniquely original ways,
  • using low complexity inputs and producing low outputs,
  • working by highly complex and organized internal means,
  • that remain largely hidden from view.

You see that form of organization in societies, ecologies, as local, regional and global energy economies of nature, as well as in the local, regional and global energy economies of people, identified by the same method.   Being internally organized, like how a family lives in their own home, means you may see something of the deliveries that arrive and wastes discarded, but generally nothing about what’s done with them internally, making the family unit work.   It’s logically obvious once you think about it, but part of how an internally managed system must work is to collect more resources than needed.  Surplus resources can be used for anything, so parts can help each other out, or doing new and purely enjoyable things.   That’s called “net-energy” and is a major key to how self-managing systems work independent of their surroundings internally, hidden from outside view.

Maybe the most important insight to come from it, at least at first, is an appreciation of what large gaps in our information on how things work by the designs of natural systems being so hidden from view.  For traditional science it messes up everything.    Traditional science has been a highly productive way of using information to identify predictable patterns, so our use of them can be determined from our equations for them.   For subjects that science has little or no information about leave gaps in our understanding too.     What science needs is a way to define useful questions about the self-managed and self-designed systems of our world, a “pattern language” for the study of natural systems, a way to ask better questions about the distinct gaps in our information that natural systems create.     I think not having that yet is why these very serious subjects are not treated seriously.

The term “pattern language” in its widest usage refers to useful building blocks of design, a concept originated by Christopher Alexander (RNS links), today gaining major interest from “object oriented” software design, with quite similar usage for the study of the building blocks of internally organized  individual natural systems, as has been the focus of my work since the 70’s.



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