Robert Rosen How Are Organisms Different

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Robert Rosen's theories of complexity and how science gets it wrong
  rosen how are organisms different ROBERT ROSEN: THE WELL POSED QUESTION AND ITS ANSWER-WHY ARE ORGANISMS DIFFERENT FROM MACHINES? Donald C. Mikulecky Department of Physiology Medical Campus of Virginia Commonwealth University BOX 980551 MCV Station Richmond, VA 23298-0551 USA Email: URL:  retd 2014 10 08 from  n.d. Abstract The question What is life? has been around for some time. There is an impressive list of great minds that tackled the question. In spite of this, it never has been answered in any definitive way. Robert Rosen, a student of Nicholas Rashevsky and a product of the Mathematical Biology program at the University of Chicago started one line of research that grappled with the question in the late 1950's. It is worth examining the progression, which lead Bob Rosen to realize that he was dealing with a poorly posed question and that when rephrased, the question had an earthshaking answer. The answer was earthshaking not so much due to its information content but more so due to the process by which it was answered. This process and its really revealing ramifications will be the subject of this review. It is no easy task to try to say these things in Bob Rosen's stead, and you will suffer from having to hear a surrogate. On the other hand, to see beyond where anyone has seen before has often necessitated standing on the shoulders of giants. What we will examine here is the entire epistemological basis for modern science. We will examine it with a view that, in itself, is a product of that very examination. And, thus, from the onset, we will be forced to stop every step of the way in order to remind ourselves that what we are doing is only effective if it is changing even as we do it.  Why so bold a goal? Because anything short of that easily and deceptively lapses back into well worn tracks even if dressed to seem new and different. What Robert Rosen discovered had that effect on him, and, as he wrote and spoke over the years, it began to have an effect on some of us. The path we are about to traverse is very difficult. It was even more difficult for Bob, for as he saw, he had to communicate what he saw. This is difficult enough with new ideas even when they nicely extend the ideas upon which they are built. It is far more difficult when the new ideas radically change that perspective.  Now we will move on to the subject at hand. The role of the machine metaphor in science goes back to Descartes.  Newton and those who followed built it into what has become modern science. The success of this world-view was so great that it became as strong as any of the other belief structures we might identify as religions. In this case, however, science was to liberate us from superstition and myth and to give us a basis for evaluating those things that were to be candidates for truth. Hence physics dealt with the fundamental laws of nature and chemistry and biology were to use these laws to deal with specific applications of the general laws physics discovered. In other words, the relation of physics to biology, in particular, is that of the general to the special. Rosen was able to see that, in fact, this was a prison for our thought and an extreme handicap to our understanding. It was a legacy of the machine metaphor. How could this be? It is so  because the world of the machine is a simple world. Its laws and inhabitants are simple machines or mechanisms. What if the objects in chemistry and biology are not that simple? Then we must reduce them to subunits that are. By this reductionist path we will learn all that there is to learn about the real world. Robert Rosen discovered that this approach was a dead end! He discovered that when the reduction is performed, something real and necessary is lost and in a way which made it unrecoverable. This profound realization turned the ontology of our world upside down! It isn't the atoms and molecules that are at the hard core of reality, it is the relations between them and the relations  between them and things called processes which are at the core of the real world! There is much to this discovery and we will only be able to have a taste of it. In that tasting we will examine the modeling relation that is the key to our own ongoing examination of what we are doing as we do it! We will examine the alternative to a mechanistic world, a world of processes and causes. A world ever changing and yet a world more rational than the sterile world of machines. Finally, we will utilize this new way of seeing to repose the question about life and answer it. 1.   Science and the issue of complexity The goal of this paper is to reveal to the reader a view of science that has the potential for changing its direction in the most profound way since the time of Descartes. The example used to convey this view is the issue of life:  Life itself , to steal the title of Robert Rosen's book on this subject. This potential change has an historical timeliness since it is happening during a time when much else calls for it. There clearly will not be an opportunity to pursue that digression here, due to space limitations, but it needs to be pursued. In order to have any hope of achieving so  bold a goal, it will be necessary to present a skeleton with the hope that meat can be added to the bones by those interested enough to go on with the thoughts. In this case, even a skeletal presentation requires that the reader be willing to suspend certain ideas about science which are usually taken as fundamental . The whole notion of what is fundamental is open to examination here. That, in fact, is how to begin. 1.1 Science, perception and measurement: The role of the modeling relation In order to be able to deal with some very confusing issues, it is necessary to formulate just what it is we think we are doing when we carry out this function called science . In a very real sense what we mean by science is the ultimate version of what humans do quite regularly, namely the perception of their world. The perception of the  world is merely the way humans turn sensory information into awareness. What is that all about? Here's one idea that will serve the purpose for this discussion (Fischler and Firschein, 1987, 233) No finite organism can completely model the infinite universe, but even more to the point, the  senses can only provide a subset of the needed information; the organism must correct the measured values and guess at the needed missing ones. ... Indeed, even the best guesses can only be an approximation to reality - perception is a creative process. This simple observation is fraught with meaning. So much meaning that it is worth examining its implication in some detail. 1.1.1 The traditional view of science: the role of measurement Science is the way we have developed to avoid our perception 's being creative in the above sense. Science is a creative endeavor, but the creativity must not cloud our sensation of the world in any way. In order to accomplish this we have developed a methodology that is supposed to prevent our minds from tampering with the sensory information. We call this measurement. Often the methodology that insures this objective view of the world is called the scientific method.  It should be clear that our notion of objectivity  is intimately associated with this concept. 1.1.2 Rosen's treatment of measurement Since Rosen devoted at least an entire book to this topic (Rosen, 1978), it will be necessary to give a summary here. The process of measurement is something Rosen saw as related to a number of other important concepts that will be involved in this development. Along with measurement are recognition, discrimination, and classification.  It is impossible (even if desirable to some) to reduce the issue of measurement to something independent of these other factors as we shall see. Two propositions are axiomatic in the formalization of the role of measurement in our perception. Bear in mind that what is being developed here is a way of dealing with the traditional view of science. PROPOSITION 1: The only meaningful physical events which occur in the world are represented by the evaluation of observables  on  states . PROPOSITION 2: Every observable can be regarded as a mapping from states to real numbers. Rosen warns us that the consequences of adopting these propositions as a mode of operation are very profound. They are, however, the kind of price science is willing to pay for its claim to be able to minimize the role of the conscious mind in the perception of sensory information. It should be clear that the act of measurement is an abstraction. We will return to this point shortly. The trade off is in the belief that, by making this abstraction, the world has qualities which, when measured properly, are common to all objective observers. A quote from  Fundamentals of Measurement sums it all up very well: It is essential to realize at this point that the formalism to be developed, although we cast it initially primarily in the framework of natural systems, is in fact applicable to any situation in which a class of objects is associated with real numbers, or in fact classified or indexed by any set whatever.  It is thus applicable to any situation in which classification, or recognition, or discrimination is involved; indeed, one of the aims of our formalism is to point up the essential equivalence of the measurement problem in physics with all types of recognition or classification mechanisms based on observable properties of the objects being recognized or classified.      1.1.3 The modeling relation: how we perceive The modeling relation is based on the universally accepted belief that the world has some sort of order associated with it; it is not a hodge-podge of seemingly random happenings. It depicts the elements of assigning interpretations to events in the world . The best treatment of the modeling relation appears in the book  Anticipatory Systems (Rosen, 1985, pp 45-220). Rosen introduces the modeling relation to focus thinking on the process we carry out when we do science . In its most detailed form, it is a mathematical object, but it will be presented in a less formal way here. It should be noted that the mathematics involved is among the most sophisticated available to us. In its purest form, it is called category theory [Rosen, 1978, 1985, 1991]. Category theory is a stratified or hierarchical structure without limit, which makes it suitable for modeling the process of modeling itself. Figure 1. The modeling relation. Figure 1 represents the modeling relation in a pictorial form. The figure shows two systems, a natural system  and a  formal system  related by a set of arrows depicting processes and/or mappings. The assumption is that when we are correctly perceiving our world, we are carrying out a special set of processes that this diagram represents. The natural system is something that we wish to understand. In particular, arrow 1 depicts causality in the natural world. This idea will need some additional explanation further on. On the right is some creation of our mind or something our mind uses in order to try to deal with observations or experiences we have . The arrow 3 is called implication and represents some way in which we manipulate the formal system to try to mimic causal events observed or hypothesized in the natural system on the left. The arrow 2, is some way we have devised to encode  the natural system or, more likely select aspects of it (having performed a measurement as described above), into the formal system. Finally, the arrow 4 is a way we have devised to decode the result of the implication event in the formal system to see if it represents the causal event's result in the natural system. Clearly, this is a delicate process and has many potential points of failure. When we are fortunate to have avoided these failures, we actually have succeeded in having the following relationship be true: 1 = 2 + 3 + 4. When this is true, we say that the diagram commutes  and that we have produced a model   of our world. Please note that the encoding and decoding mappings are independent   of the formal and/or natural systems. In other words, there is no way to arrive at them from within the formal system or natural system. This makes modeling as much an art   as it is a part of science. Unfortunately, this is probably one of the least well appreciated aspects of the manner in which science is actually practiced and, therefore, one which is often actively denied. It is this fact,
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