The Collective Dynamics of Social Transformation


”Why should social science confine itself to passively studying social phenomena when it can be used to actively change the state of affairs?”         George Soros


"The world we have created is a product of our thinking; it cannot be changed without changing our thinking."        Albert Einstein

These pages are dedicated

to the memory of Dana Meadows,

and to Jay Forrester and Phil Agre


Starlings on Ot Moor

Watch this! Simple and elegant emergent collective patterns of behavior in a living system.





”Why should social science confine itself to passively studying social phenomena when it can be used to actively change the state of affairs?”

George Soros


"Philosophy is written in this grand book - I mean the Universe - which stands continually open to our gaze. But the book cannot be understood unless one first learns to comprehend the language and read the letters in which it is composed. It is written in the language of mathematics... Its characters are triangles, circles and other geometrical figures, without which it is humanly impossible to understand a single word of it; without these one is wandering about in a dark labyrinth."

Galileo, ll Saggiatore


“A scientific explanation is a description mapped to a tautology”

Gregory Bateson


"The major problems in the world are the result of the difference between how nature works and the way people think"


”These new concepts appearing in dynamics will extend the conceptual power of our civilization”

Ralph Abraham


"Designing" social systems or corporations may seem mechanistic or authoritarian. But all governmental laws and regulations, all corporate policies that are established, all computer systems that are installed, and all organization charts that are drawn up constitute partial designs of social systems.

Jay Forrester


“Systems thinking can lead us to the edge of what analysis can do and then point beyond - to what can and must be done by the human spirit.” 

Dana Meadows


We need to know four things:
what there is,
what to do about what there is,
that there is a difference between knowing what there is, and knowing what to do about what there is, and what that difference is.


Adherents of the mythological world-view tend to regard the statements of their creeds as indistinguishable from empirical "fact," even though such statements were generally formulated long before the notion of objective reality emerged. Those who, by contrast, accept the scientific perspective - who assume that it is, or might become, complete - forget that an impassable gulf currently divides what is from what should be.

Jordan Peterson


“It will often be to no purpose to tell of the superior advantages the subjects of a well-governed state enjoy; that they are better lodged, better clothed, better fed. These considerations will commonly make no great impression. You will be more likely to persuade, if you describe the great system of public policy which procures these advantages;

if you explain the connexions and dependencies of its several parts, their mutual subordination to one another, and their general subserviency to the happiness of society; if you show how this system might be introduced…, what it is that hinders it from taking place at present, how those obstructions might be removed, and all the several wheels of the machine of government be made to move with more harmony and smoothness, without grating upon one another, or mutually retarding one another’s motions.

It is scarce possible that a man should listen to a discourse of this kind, and not feel himself animated to some degree of public spirit. He will, at least for the moment, feel some desire to remove those obstructions and to put into motion so beautiful and so orderly a machine.”

Adam Smith


"We must create positive visions of the future"

John Lennon


"My dear Kepler, what would you say of the learned here, who, replete with the pertinacity of the asp, have steadfastly refused to cast a glance through the telescope? What shall we make of this?  Shall we laugh, or shall we cry?"

Letter from Galileo to Kepler





Introduction to the Course


Motivation


The motivation for this course is to provide a set of ideas about the nature of reality and the way we think about it, to use these ideas to understand how human social systems change and evolve, and in turn to learn how to design action plans for creating transformations of social systems from dysfunctional to sustainable behavior. We shall find as we go that the necessary, and perhaps sufficient requirement for a sustainable society is that it be an open society. A society that can learn from it’s error’s, and adapt to a changing reality. The premise is that the roots of dysfunction in human society lie in fundamental errors in our understanding of the complex world that surrounds and includes us - errors in epistemology.

The lectures will discuss the observation that we are in the midst of a cognitive revolution - a revolution in epistemology - of the magnitude of that earlier revolution triggered by the views of Galileo and brought to fruition by Isaac Newton. We will consider the implications of the current revolution for the governance of human societies. This new revolution extends that of Galileo, Kepler, Newton, and their contemporaries. This new revolution is also rooted in mathematics, a new mathematics empowered by the emergence of fast computation.


Mathematics


The first thread of development of this new mathematics began with the work of Henri Poincare on the three-body problem, the first chaotic attractor, analyzing the behavior of three bodies interacting through their mutual gravitational attraction. He looked at the gravitational interaction of the Earth, Moon and Sun. The mathematics he applied was Newton’s calculus - basically the study of change.


This discovery of a chaotic attractor did not have the impact it might have, because without fast computation, examples of the behavior of chaotic attractors systems were inaccessible. The discovery and exploration of the behavior of the Lorenz attractor in 1968, using a digital computer, revealed the impact that chaotic attractors have for scientific explanation.


Chaotic attractors appear in what are called dynamical systems. These are sets of coupled differential equations, implemented as difference equations, that, given the state of a system at a given point in time, defines the state of the system after a small time step to a new point in time. Repetitive iterations trace out the path of the system through the space of it’s variables through time. It extends the Calculus of Newton and Leibniz, heretofore strongly constrained by the necessity for analytical solutions, into a vast new mathematical space of nonlinear equations accessible to what are called numerical methods made feasible by fast computation.

A second thread of development was initiated by Conway's Game of Life, which best understood by studying the examples in the links (like now). The Game of Life is a cellular automata, a two-dimensional grid of individual entities - pixels. Each pixel is connected to it’s four nearest neighbors. The connection is a communication pathway. Each pixel “sees” the current state of it’s neighbors (on or off), and it’s rules use this information to determine it’s own next state.


The Game of Life is a cellular automata, and can be considered a reduced or rudimentary example of a Collective Dynamical System (CDS), a collection of coupled entities which communicate and act, based on internal rules and information derived from this communication. In a CDS, the state of the entities at any time is typically represented more the one variable, with multiple bits of information. The rules which incorporate this information are differential equations of Isaac Newton. Actually, in practice, during computation, these equations become difference equations, with time passing in finite small time steps, with the value of each variable.


With the appearance of faster computation, the memory devoted to each individual has expanded to kilobits or even megabits and gigabits. This evolution of this approach empowers the study of collective dynamical systems, collections of individual entities which are connected by a network of communication pathways. Each individual, or class of individuals, can be defined as a dynamical system, sets of coupled equations which are the rules determining the behavior of the individuals. The independent variables of the equations are the information obtained by individuals from the communication network. The rules are differential equations, or rather, difference equations. The rules specify how information coming to the entity from other entities, through the network, influences the future behavior of the entity. This coupling of these entities leads to the possibility of coherent behavior, the emergence of collective q, patterns of behavior, at the next higher hierarchical level of the system.

These new mathematics teach us a new language - of feedback loops, attractors, bifurcations (tipping points), and emergence. These are new mathematical analogs of the triangles and circles and other geometrical figures of Galileo. The geometric objects of Galileo along with the differentials and integrals of Newton revolutionized our understanding of the physical world, by providing possibilities for new scientific explanations for change. The attractors, bifurcations and emergent events of collective dynamical systems are mirrored in the real world of repeated patterns of behavior in what are called complex systems. Social systems, perhaps the most intractable complex systems, we here seek to understand and explain using this new language.

Thus, the course will examine this thesis that the impotence of human institutions to create and put in motion appropriate evolutionary changes stems from using inadequate models of reality; inadequate scientific explanations of social system behavior.


Epistemology


Starting with a discussion of the nature of scientific explanation, we proceed to explore these new mathematics, to see the correspondence between the patterns of behavior of these mathematical systems and the patterns of behavior we see around us in the real world of collective human behaviors - the behaviors of social systems. We learn to "read the book" of social behaviors, as written in this new mathematical language, and to consider the design of actions that can create evolutionary changes which enhance the survival and sustainability of our social systems, and lead us out of our dark labyrinth.

The goal is to bring the meaningful use of these mathematical terms, and the insights they bring with them, into the everyday language of the social sciences. Obviously a lofty goal, but one worth pursuing.

It seems relevant at this point to quote the words of the thermodynamicist Truesdell, in his paper "The Tragicomedy of Classical Thermodynamics":

"Thermodynamics adopted and continues a style in which the thermodynamicist applies what mathematics he happens to know. If that mathematics does not suffice, he cuts down the problem to its size."

Underlying this course is the notion that the new mathematics of fast computation has opened a vast new territory for scientific explanation, and this cognitive revolution gives us the power of new insights into old intractable problems in the organization of human society. By analogy, one could characterize the current state of the field of Economics by, somewhat arrogantly I admit, paraphrasing this statement of Truesdell:


"Economics adopted and continues a style in which the economist applies what mathematics he happens to know. If that mathematics does not suffice, he cuts down the problem to its size."

The problem is that of using the wrong models for thinking about the behavior of social systems. The scientific approach to social systems has been rooted in the success of the mathematics of physical science. The mathematics which enabled the explanation of physical phenomena are not appropriate for complex systems. Without the insights provided by the mathematics of fast computation, and what is called the science of complexity which accompanied its emergence, maladaptive behaviors of social systems seem beyond our capacity to change. This course is a search for new ways to understand and create selected adaptive changes in human society, based on an understanding of this new mathematics.


Social Action


The notion of creating changes in a social system almost inevitably encounters pessimism. While awareness of serious dysfunction in our social systems is almost universal, there is also a sense of hopelessness, a sense that change is unlikely if not impossible. The course explores an approach to overcoming this situation.

The first term of the course begins with epistemology and mathematics. These subjects are not presented in the style of philosophers or mathematicians, but rather are explicitly oriented towards the acquisition of a language for description and thus a framework for scientific explanation. Next we examine some emerging ideas which apply complex systems thinking to social systems, and relate them to these underlying mathematical roots. In subsequent lectures we use these tools to attempt to facilitate this way of thinking about change and evolution in social systems and global human society.

In the research projects of the second term we learn together how to effect positive change in social systems using this point of view. We will select a small set of systems and organize groups to focus on these systems. They propose a series of steps for thinking about creating positive changes in these system.

There is a problem here - how can we know what positive change is? Are we ready to take on the role of God?


The answer is that we cannot know absolutely. The question is fundamentally unanswerable, but we cannot avoid making a choice. It is not possible to do nothing. Deciding to do nothing is also an act, and it can have critically important consequences. This course is intended as a guide to making these necessary choices.

To continue this line of thought, I would suggest that if we want to take on the role of God we might pay attention to what Albert Einstein called "knowing God's mind"; the search for understanding which we call science. The power of the evolutionary process in creating our world is embedded in that world, surrounding and including us. In Galileo's words, it "stands continually open to our gaze". It seems clear that our choices for design, choices which we must necessarily make, must be guided by our knowledge of evolutionary processes.

The group projects will focus on designing changes in various restricted subsystems of contemporary society. These systems we seek to change are embedded in a hierarchy of larger systems which form the context in which our proposed designs for change, for learning and evolving, must be implemented. We find as we progress that changing our local systems requires changing the context in which they function. This means confronting basic societal structures and patterns of behavior. These structures and patterns strongly resist the sort of changes we are proposing.

This leads directly and unavoidably to the necessity for change at the highest levels. This higher level change, as we shall see, is the emergence of the open society. Don’t imagine that the concept of open society is new - it is merely a renaming of what has long been called democracy, but that term has been misused so often that a new term may be useful. Furthermore, the name emphasizes the need for openness, or transparency, in public affairs. Secrecy in government is always a danger for democracy.


An open society is a system that can learn, adapt and evolve. The emergence of the open society is second-order learning in Bateson's hierarchy of learning - collectively learning how to learn. In recognizing the need for this transformation and implementing it, society must undergo a third-order learning process, learning how to learn how to learn. This sort of transition is rooted deeply in the human collective consciousness, a transition that is both intellectual and spiritual.


This collective spiritual transformation brings a new awareness of the human condition that embraces all peoples, while at the same time making a commitment to preserve individual cultures within the human community. This cultural diversity is a critical condition for our survival as is the notion of biodiversity; both are necessary for sustainability. Diversity is a fundamental source of the power of the evolutionary process, without this diversity our species cannot adapt and evolve.




Inspiration for this course has come in great part from my excellent students at Central European University over the past fifteen years. Your positive responses to my teaching gave me the courage to persevere. You are a unique collection of bright young minds, whose countries and cultures are at various stages of rapid and more or less chaotic social, political and economic changes. Indeed the whole global system is subject to chaotic events with unpredictable futures. But remember, in chaos lies the possibility to create the new.

John B. Corliss
Budapest
Jun 1, 2004
Jan 8, 2008
Jun 2, 2011

 


Preface - CDST_2014


This course and this web page are constantly under construction. At present I am teaching the course to another set of the remarkable students who come to study here at CEU. These web pages are primarily devoted to you, dear students.


The course is essentially rebuilt every time I teach it. This results not only from my own learning process, but from the explosive growth of knowledge and understanding of our world that characterizes our times.


In particular, an issue that has impacted my thinking about this course this term is my discovery last summer of a book - “On Intelligence”, by Jeff Hawkins with Sandra Blakeslee (2005).


I believe it answers the perennial question, “What is human consciousness?” Hawkins answer is that “consciousness is living with a neocortex”.


More explicitly, I believe that the top-down model of the brain proposed will lead directly to the emergence of a scientific explanation for consciousness. For “scientific explanation” I follow Gregory Bateson’s notion, extending Galileo, that “an explanation is the mapping of a description onto a tautology”.


Critical for this is the bottom-up model of the brain being built over recent years by the community of scientists mapping the patterns of connectivity of the neurons of the brain. A most recent and fascinating effort being by the Brainbow project of Jeff Lichtman at Harvard. This work will lead to the possibility for experimental simulations of the patterns of connectivity in the brain and the processes that underlie consciousness, creating this an scientific explanation for consciousness. It may be possible to create a real sort of intelligence, and put to rest the “artificial” intelligence which has characterized attempts in this field so far.


This modeling and simulation can explore, for example, the network dynamics. A key feature of the network dynamics, the role of the other components of the brains neural network that mediate between the cortex and the external inputs to the brain


The implications for this present course are manifest in our emphasis on understanding repeated patterns of behavior.  We observe repeated social patterns of behavior (1) in the dynamics of the environmental systems of the real world we study, (2) with our systems dynamics diagrams which map these patterns of behavior onto mathematical objects of dynamical systems theory (attractors, feedback loops, basins of attraction, bifurcations (tipping points), and (3) in our attempts to transform the consciousness and the unsustainable patterns of behavior of the human actor in these real world systems.


The impact of this new knowledge on the social sciences will be profound. This impact will no doubt by delayed by the intransigent nature of academic disciplines, but the ideas are too powerful, and new forms of communication of ideas will bypass this resistance.


Jack Corliss

31 Jan 2014


Note: The present state of these pages has been frozen for the last 3-5 years while the course content has evolved considerably. The basic ideas are not wrong - just dated. This will be resolved - too late for this year’s class - but for the future.

Jack Corliss

Dr. John B. Corliss

Visiting Faculty

Environmental Science and Policy

Central European University

Budapest, Hungary

jack.corliss@gmail.com

Home       Prefaces       Syllabus       Lectures       Topics