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Published on Question Everything on August 8, 2014
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An Example from Biology
A living system is the basic example of an economy. For example within a single cell the metabolic machinery is a production factory to produce more biomass, either growth of the cell to a mature size, or through cell division production of new individuals. There is a third product that some cells, those in multicellular organisms, make and that is simply replacement of degraded biomass, what we call a steady-state economy.
Figure 1 shows a simplified and abstract representation of cell metabolism, at least as far as things like protein synthesis and uses are concerned. The major work processes are the construction of enzymes (and enzymatic systems) and the machinery construction. Various processes, such as those shown, are actually complex molecular machines that require enzymes and energy to do their work. For example the ribosomes, the major protein synthesizer machine has to be constructed out of RNA molecules and proteins. All of the cellular organelle are constructed or self-organize based on their inherent chemistries.
The cell is basically an “exchange” economy where various machines produce products needed by other machines. Most often the trades go through several steps. In the background all of the machines tend to degrade and break down. Their molecules have to be either recycled or expelled. Many cells actually produce molecular products that are used by other cells, so the exchange model extends to whole multicellular systems as well.
Figure 1. Metabolism in a living cell is an example of an economic system.
Every cell captures materials and energy from its environment. Photosynthesizing cells (plants) have an energy capture and conversion machine, the chloroplast, that manufactures energy packets, like adenosine tri-phosphate (ATP) from sunlight input. Animal and fungal cells take in molecules that are both energy carriers and raw materials. They first need to digest organic materials (from plants) and then machines called mitochondria convert the carbohydrates into ATP. ATP is like a floating battery that circulates everywhere within the cell conveying convenient energy to all of the other machines. Every machine in the cell (organelles) use the energy stored in ATP to do their work. All of them employ proteins and membranes. The former can be either structural components or functional (enzymes). The latter, bi-layered lipoproteins, encapsulate the functions of the machines. Those boundary conditions regulate the flows of molecules so that rates of work are controlled.
Every machine, or metabolic processor, operates under feedback control. Certain molecules “sense” the products and provide either direct feedback to the machine (e.g. down modulating the production of certain proteins at the ribosomes) or escort the products off to the recycling center if they are not needed. Some escorts test the quality of the output, for example determine when a protein has not folded into its tertiary structure properly, and acting as quality control monitors send the deformed product off for digestion and recycling.
Living economies operate under fairly rigid rules (principles) with respect to the conservation of material and energy. For example the rule of “if you don’t use it, you lose it” is followed rigidly. Cells don’t keep useless organelles or molecules around if they are not actively contributing to the whole system. Such “excesses” are degraded and digested, recycled or expelled. And their production machinery will be down-modulated. No more energy will be expended on producing what isn’t needed.
Another rule is: “If there is a greater need to produce product X, then up-modulate the machinery to make it.” When cells are placed under conditions that are unfavorable, where some critical factor like pH is near or beyond the limits of tolerance the cell responds by up regulating machinery that produces mechanisms to thwart or compensate it.
These rules reflect the laws of supply and demand.
The depiction in figure 1 represents the kind of organization and processes that take place in the cytoplasm outside of the nucleus. The basic controls regulating metabolism are operational controls (as covered in the last post). Everything is tightly coupled through feedback loops and under “nominal” conditions the market of exchanges and valuation based on energy consumption works cooperatively without a great deal of intervention. But nominal conditions hardly prevail for long. Every cell sits in an environment where fluctuation in critical factors constantly impose stresses that must be responded to, as described above. One of life’s earliest accomplishments was the invention of homeostasis. This is the basic feedback control loop for maintaining critical factors within a nominal range by reacting to external changes. A homeostatic mechanism can either do something actively to influence the external conditions, or respond by activating a movement of the organism away from the situation (where movement is possible) or call upon internal reserve mechanisms to counter the external influence, for example by sequestering molecules when their concentrations are driven too high. Homeostasis is the first level of tactical management, coordination with the external world in order to maintain function. It also demonstrates the tight link between operational control and tactical control. Figure 2 depicts the components of a homeostatic system.
Figure 2. Homeostasis.
The basic physiological process depicted could be any of the producing machines described above. It needs and input of some critical factor to do its job. But the critical factor is influenced by something in the environment that can drive that factor above or below its necessary level. The control system monitors the input generating a feed forward error signal, eff, which is used by the sub-process I’ve called the ‘control model’ to generate a control signal, cr that activates the response mechanism. That mechanism is capable of doing something that counteracts the environmental influence. This diagram shows an arrow from the response to the environmental factor, but the mechanism might act internally, for example to actively sequester or neutralize unwanted molecules.
The control model might be a complex one. I’ve included the basic feedback control loop for the physiological process product output. The comparator generates an error signal, efb, that can be used by the model to send a control signal, cp to the process to take internal corrective action. The model, thus, represents a close cooperation between an operational control (feedback) and a simple tactical control (feed forward).
Also shown in the figure is a depiction of a higher-order mechanism that embodies the two principles mentioned above. The response mechanism needs to be maintained at some level of readiness that is just necessary for the ordinary sorts of responses it has to make. The ‘response constructor’ is responsible for this maintenance. Imagine its “responsiveness” as represented by the size of the oval. It can’t be too big because its maintenance would be prohibitive in terms of energy and material required. At the same time it cannot be too small because if the external influence were to drive the critical factor out of range too fast it would result in some kind of damage to the organism that could be fatal. How to determine what the right size would be?
The response constructor uses some kind of molecular memory device that keeps, essentially, a time averaged trace of the history of external influences (supplied by the control model). If the memory value is high then it means the influence has been strong and frequent over some past time window. Thus the response constructor “knows” to build up and keep strong the response mechanism. It will invest more material and energy into the response mechanism because it “expects” there will be an on-going need for fast and strong responses in the future.
The details of the constructor and its memory are not important right now. I will just say that this basic kind of machinery is active in all biological systems where some anticipation of future demands for a function is needed to prevent damage or take advantage of an opportunity. In a more elaborate and multi-time domain form, this is the basis for what neurons do when they encode memory traces in their synapses. Hence the term memory is not abused here.
You may recognize the above figure as it is basically the same as figure 6 in the prior post in this series. Here I have added the response constructor to expand the example as an exchange economic model.
In the metabolic economy there is a true ‘currency.’ That currency is the packets of energy called ATP. Energy is involved in all transactions and, by the second law of thermodynamics, degrades in capacity to drive work as it flows through the economy. It is given off as waste heat and new high grade energy must always be supplied.
The messages depicted in these figures are conveyed by chemical signaling. Small weight molecules are released by one sub-process and diffuse through the cytosol to be ‘received’ by another, target, sub-process that will then act on that message. Cells have receptor sites on the outsides of their membranes that are specialize to couple with these diffusing molecules. When that happens it generally sets off a cascade of so-called second messengers that eventually affect an internal control mechanism that then does its work (having access to ubiquitous ATP) and responds to the signal the cell received. That is what is actually going on in figure 2 with all of the signal arrows representing various molecules that activate the machinery, such as the response mechanism. Chemical signaling was the earliest form of communications in living systems, both internal and external to the cell membrane.
But the point is that the cellular metabolic economy is regulated by the same hierarchical control system covered in the last post. When we include the role of the genes, along with their network of expression controls and epigenetic mechanisms, we will find that it all fits the model shown in figure 8 in that post.
There is one more aspect to the biological model of economy governance that should be brought out. Cells do not grow bigger and bigger forever. There are constraints on how large a cell of a particular type can get to be. Some constraints may be imposed by external factors, others, like effectiveness of heat dissipation, may be imposed by internal factors. Newly created cells, however, are smaller than the optimal size and so they follow the mandate to convert materials and energy in to new biomass within their membrane. Once they reach the optimal size however they have the potential to replicate by cellular division, thus making two small cells that then, each, continue to grow biomass. They do this as long as there are no external constraints, such as lack of a vital material or energy, to cause them to stop growing and simply maintain.
In the case of multicellular organisms the same pattern can be seen but with an interesting twist. External factors, that is external to the multi-celled tissue that is growing, can trigger internal signaling within the tissue to stop the reproduction of more cells. This is what happens, for example, in the development of organ tissues in embryos and fetuses. Cells receive signals that not only tell them what to differentiate into, but also when to cease growth activity or at least modulate it to fit with the overall organism growth pattern. No one tissue can exceed its natural size. Figure 3 depicts this form of restraint on growth.
Figure 3. The biological mandate dictates that more biomass be produced until some forms of constraint trigger restraint.
Biological systems evolved these self-restraint in the face of external constraints in order to preserve life. Any overrun by any one biological entity threatens the life of all other organisms and therefore mechanisms for suspending the biological mandate were needed to achieve balance in the whole ecosystem. The regulation mechanisms are many in form but you will find them at all levels of living systems. And you can see the effects when they fail to work. This is what cancer is, a breakdown in the growth-regulating system releases the suspension on the mandate and the cells resume growth and reproductions indiscriminately. I’ll return to this idea later.
The Biophysical Economy
The human economic system is effectively the same model as the cellular metabolic economy. The roles of materials and energy are the same. The work processes needed to construct products needed by other processes are basically the same. Even the purpose of the whole system is the biological mandate of growing more human biomass.
In figure 4 I have drawn yet another view of the biophysical economy, abstracting all of the basic functions into just a few representative sub-processes. Fundamentally the economy is designed to extract natural resources from the Ecos as well as capture sources of energy to then produce all of the goods and services that ultimately go to consumers through a distribution subsystem. If you trace through the flows and processes you will see that this schema is similar to what was shown in figure 1. Unlike the cell example the human economy has a much smaller recycling capability (so it is not shown).
Figure 4. The biophysical economy is shown in a very abstracted form.
Since I have written a considerable amount about the biophysical economy (and biophysical economics) I won’t go into details here (look for more in the Biophysical Economics section of the blog). Rather I want to call attention to the signal arrows in this figure, the thin black and green arrows. These are the cooperation signals the provide supply and demand messages between processes. In the past I have claimed that money is really just a form of signal, information about the amount of usable (free) energy that can be controlled in the sense of directing which work is to be done (see figure 5 below). Unfortunately in a debt-based situation such as we have today money is a very distorted message conveyance. That is one reason that our current economic system, world wide, is not working very well. The governance model (essentially free markets with light regulations on selected processes) relies too heavily on cooperation and that depends on the fidelity of inter-process signals. As already argued, when any system gets too complex it is necessary to introduce coordination (logistical management) between processes in order to facilitate the functions in figure 4.
Figure 5. Money is used to convey information regarding the flows of goods and services. Individual agents decide how much money (the intensity of the message!) to send. The receiver interprets the message to determine how much work to do and thus how much energy to expend.
What this really means is that a workable governance model must be based on effective communications and realistic logistics rules. The governance we have was born from a very nebulous set of ideas about the interactions between government, political process, and the economy, hence the name political economy. The system is a result of an evolutionary process but with a kind of built-in bias toward the idea of progress. Unlike all previous forms of social evolution (e.g. emergence of eukaryotic cells from bacterial cells, emergence of multicellularity, etc.) the evolution of the political economy has been nudged along by the reflective agents who have tried to shape what it would be. It was as if certain genes in the genome ‘thought’ about what they wanted and mutated themselves accordingly. The whole system is impacted by ideology-based decisions, and generally not for the better. Overlay the complexification of society due to technological development and you have the evolution not of a sustainable system, but an aggregate of many dysfunctional processes.
Economic Governance
Consider the history of economic systems that have come into existence since the advent of agriculture. The original governance of agriculture-based societies was based on the need to reliably produce food stuffs for the society. Governance began with the specialization of those who could see the larger picture, not just how to plant seeds, but when and where to plant. The early Egyptians, for example, organized around the management of water from the Nile river and the land immediately nearby. A coordination function emerged quite early in the form of early kings (probably derived from “headmen” in nomadic tribes) in neighboring territories who took on the role by managing the administration of things like granaries and the emergent functions of ‘surveyors’ who specialized in measuring out the land areas after the annual Nile floods had receded. After the invention of the plow and the domestication of animals, along with the increasing capabilities to work with metals and clay, specialist trades developed rapidly. The production of products of these specialists needed to be organized and coordinated since any one specialist might be losing track of what the others were doing. Someone had to rise above the whole operation and help make sure what needed to be done was done.
The model of governance that emerged in Egypt and five other similar civilization centers was based on a hierarchy of command and control. The kings became Pharaohs, god-kings, who had absolute authority. They presumed their knowledge was absolute. As the complexity of the kingdom rose layers of administrators were rapidly added. The Pharaoh became more distant from the workers in the fields. A class system based on the tendency in human psychology to establish some kind of pecking order was amplified by the nature of the hierarchy. This would establish a pattern that would be with us for the rest of our experience. A human bureaucracy superposed over the natural management hierarchy carried all of the flaws of human psyche, especially the lack of adequate sapience to counteract the limbic system’s tendency to drive the need for establishing power relations. It has never been a particularly happy combination.
Among the duties of the ruling class, by virtue of their nominal positions, was the protection of land holdings — the territory of the kingdom. A separate specialization developed early on, that of the warrior and the armed forces necessary to protect the kingdom from marauders. At first their jobs were probably mainly defensive but as time went on and kingdoms experienced bad harvest from time to time, the idea of invading another territory probably followed very naturally. Of course it might not have taken a hard time to promote the notion of aggression. Humans are already individually aggressive and greedy (again a lack of sapience thing). So the temptation to invade another kingdom for booty or outright takeover was probably not a hard hurdle to jump.
The basic form of hierarchical governance with class and power overlays has been with us ever since. Even the American and European experiments in some forms of democracy have not been able to rid us entirely of this structure. For example the American presidency, which George Washington explicitly demanded not be like a king, has evolved to a king-like status. We even have a modern form of dynasty in families like the Roosevelts, the Bushes, and the Clintons. The British, of course, never got rid of their royalty, going back to feudal days.
What is wrong with governance is the humans who implement it. A human being is a selfish, self-centered, limited-perspective agent who is placed in the untenable position of making cybernetic decisions with weak knowledge and distorted senses. No mere mortal man (or woman) can be the president of the United States, or leader of any state on the planet. The philosopher kings are rare these days.
Human Agents
Recall figure 4 in the prior post, reproduced here so you don’t have to go back to that. We human beings are, ourselves hierarchical cybernetic systems. Our brains are designed to process operational level, coordination level and strategic level information. We make decisions at all of these levels. But, and this is a huge caveat, we are driven by the biological mandate and our sapience capacity is still very immature. In figure 6 I’ve added the limbic system that drives much of human decision making. In higher sapience the feedback from the strategic level of decision making acts to down modulate the emotional and purely biological drives that influence our thinking and reactions. In ordinary sapience (i.e. the average brain) this feedback is weak and the influences from the limbic system will ultimately dominate decision. This is the basic reason that economic agents are selfish and mostly irrational.
Figure 6. The irrational and selfish agent is motivated by limbic drives and desires.
Human beings are the worst agents for a hierarchical cybernetic system since the inject their own desires into the decision process. Moreover they are largely plagued by incomplete or even wrong knowledge about how the world works. Libertarians are the worst. They completely deny the need for a regulation system. But I have to admit that their instincts might be right given that it is human agents that are doing the regulation. A political economy needs a hierarchical cybernetic framework. What it does not need is human decision makers who are so lacking in sapience.
But suppose that the agents in a hierarchical cybernetic system could be more sapient. In effect it would mean an expanded strategic thinking ability along with expanded systems and higher-order judgment ability. Such an agent would not have lost their limbic drives; evolution doesn’t work that way. Instead what the expansion of the prefrontal cortex associated with increased sapience would mean is a stronger ability to down-modulate the activities of the limbic system that might have driven poor, selfish decisions. Such individuals would have stronger cooperativity motivation and more empathetic capacity; they would be hyper-social creatures. In short, they would be wise. Figure 7 depicts such an agent. I call such an agent an “adaptive, evolvable agent” because their expanded abilities include being able to deal with uncertainty, ambiguity, and especially an ability to modify their own concepts (beliefs) in light of new evidence. Their thinking is capable of evolving with changing conditions.
Figure 7. An adaptive, evolvable agent is one with greater sapience than we currently see in most people. Greater sapience would include expanding on strategic thinking in each agent, but would also mean the agent would be hyper-social, quite ready and motivated to cooperate with fellow agents.
In my next post in this series I will attempt to construct a hierarchical cybernetic system for a human economy that would be long-term stable (dare I say sustainable?) Note that I said ‘a’ human economy. Given the situation with energy source depletion it cannot be the current economy. I’ll base the design on the above concepts of a biophysical economy embedded within the Ecos framework and in balance with it. We can then ask, what governance might look like for such a system. We have to use my adaptive, evolvable agents as the decision makers in this structure, and I will offer the argument as to why this is so.
Granted that this is something like a Platonic ideal — we don’t have a surfeit of highly sapient people to work with — but in order to understand where our real system is it might be useful to gauge against what the ideal might look like.