Essay About Life Itself
Review of: "Essays on Life Itself" by Robert Rosen, Columbia University Press, (estimated date of publication, November 1999).
Donald C. Mikulecky
Professor of Physiology
Medical College of Virginia Commonwealth University
Box 980551 MCV Station
Richmond, VA 23298-0551
Robert Rosen died in December of 1998 after a long bout with diabetes and its complications. He left a significant quantity of unpublished notes and had this book in the publication process. His last "writings" were hand done on paper with great effort due to extensive peripheral neuropathy. It was a mixed blessing to be among the first to read his last works both this manuscript and the next, unfinished one. I am saddened by our loss even as I feel his presence through his writings.
Bob was an eloquent speaker and reading this set of essays is almost as good as hearing him in person. The essays were written to be published in a number of places, usually as invited talks, yet they may as well have been set down to be a book from the start. There is a thread of continuity that makes this the case. In addition, even though I had read many of the essays as they appeared earlier, their juxtaposition in this volume proves that "the whole is more than the sum of its parts"!
The book is 344 pages. The parts come as five, each containing chapters within (the individual essays). They are:
PART I: On Biology and physics
PART II: On Biology and the mind
PART III: On genericity
PART IV: Similarity and dissimilarity in biology.
PART V: On biology and technology.
His stated purpose of this collection is to, in a sense, "flesh out" arguments in Life Itself (LI) that had to be short or even omitted for what might be called "logistic" reasons. In my opinion they essays do that at least. In LI he began with a caveat with which I am totally sympathetic. He warned the reader that he was weaving a very intricate cloth with a single linear thread and therefore much was being laid upon the reader's shoulders. My own experience is that it took numerous readings to begin to see how the weave was manifest. Once there, things fell into place more and more quickly, yet still a lot more was required because the design is so highly interconnected and rich in levels of meaning. I hope this book of essays will spare others that struggle. It will never be my place to evaluate that possibility since I can never go back.
For some years I have maintained a pair of web sites mainly devoted to these ideas. They are at http://views.vcu.edu/complex/ and the site listed in the heading. In addition, I ran a discussion group from the complexity site and participated in two others, the Principia Cybernetica Project (PCP) and the newer New England Complex Systems Institute (NECSI) both of which are linked from the complexity site. There is no way I can relate how much my present state of mind and my understanding of Rosen's work has been influenced by exchanges on these boards. We are truly in a new age when such things are possible.
In addition, since Bob Rosen was to have participated in the 43rd annual International Society for the Study of Systems meeting in 1999, I was asked to come to summarize his work in his absence. That review appears on my web site as well as on theirs and in the proceedings. So far those giving feedback have found it helpful. For that reason I will refer to it rather than rewrite a lot of background material here.
The first part deals with the relationship of biology and physics within science, which can sound like an innocent enough topic until one understands that it is a revolutionary view.
It is revolutionary because of the depth to which Rosen delves to get at the root of a number of matters (and already we have to cope with the intertwined threads of thought).
Underlying it all is the common notion that physics is the source of all scientific laws and that chemistry and biology somehow must utilize physics to be scientific. Rosen rejects this notion and thereby opens a Pandora's Box. He uses the now fifty-five-year-old essay by Schrödinger, What is Life? as a springboard to the revealing argument about biology's more generic character in comparison to physics. As he does this he develops his notion of complexity as a description of this more generic view promoted by biology in contrast to the kind of "simple systems" which are the subject matter of physics. None of this should sound new to anyone who has read his earlier work, especially Life itself, except for the new connections and new depths to which the arguments are taken. The result is a more solid whole than ever before.
I will mention a few lines of argument that particularly impressed me to try to entice everyone to read the whole thing. The first essay is entitled "The Schrödinger Question, What is Life?" and deals with what Rosen considers the basic question of biology. His introduction to this part of the book is worth having here to get a flavor for where he is going: "I claim that Gödelian noncomputability results are a symptom, arising within mathematics itself, indicating that we are trying to solve problems in too limited a universe of discourse." This is a nice capsule version of Rosen's message. If nothing else comes from his writings, this alone should change everyone who understands the message.
Much of the book is devoted to explaining why this is so. This chapter looks into Schrödinger's essay to find clues to the relation of the answer to the question to the demonstration that the methods offered by physics are too non-generic to answer the question.
A line of reasoning running through all his writings is the ease with which things that seem to be the domain of physics and physics alone can be recast into biological terms. One set of concepts that gets used this way is the relation of genotype to phenotype. The careful examination of this relationship weaves into the basic failure of reductionism to supply the whole from its parts. This, of course, is just another way of saying that the simple systems of physics fail to describe the complexity of the real world.
Another approach to this distinction between simple and complex comes from a comparison of inertial and gravitational forces and the resulting issue of the difference between response to a forceand the generation of a force. He then looks at the gene as a molecule argument from this perspective and reminds us that when such an identification is made it shifts the object from a "gravitational" role to an "inertial" role! This is but one example of his ability to use analogy and generalization to weave the picture. As it emerges, we see the connection between a sparseness of meaning in physics, the need to go outside physics (in this case to biology) to augment the formalism, and the epistemological ramifications of looking beyond the usual limited usage of these words. He then turns around the popular and familiar idea that the discovery that the gene can be a molecule was what matters most. He asserts that this obscures the more important question: "When can a molecule be a gene?" Finally, he weaves in another line of reasoning which further illuminates the point being made. He discusses certain structures with a grammatical analog. He compares "life" as a noun with "living" as an adjective and generalizes that comparison to graphical patterns of causality, which are central parts of his treatment. This essay is well placed as it serves as a good preview and enticement for what is coming.
The second essay in this part, "Biological Challenges to Contemporary Paradigms of Physics and Mimetics" are aimed at two problems, first the role of physics in dealing with the properties of living systems, and second, the role of mimetic approaches (prefixed by "artificial"). In this essay he tackles reduction of biology to physics head on. Here he weaves in another thread, the ontology of the "something" that makes the whole more than the mere sum of its parts (and, generally, different from its parts). Here is n essence that has to be appreciated if one is to appreciate Rosen at all. There is actually something here which gets lost when the system is fragmented. It is non-fragmentable. How do we "see" such things? We observe what the system does. We see that disappear when the fragmentation is performed. These things are defined by their context. They are context dependent! This idea now takes on a life of its own feeding on the other threads in the weave much as what it is telling us about. He then contrasts this with the strong desire to obtain objectivity through context independence in physics. He weaves back in the non-generic character of such things. He then shows the inability of mimesis to cope with these issues and weaves back in the thought that complex systems are not simulable.
In the third chapter, "What is biology?" he goes further in his comparison of Mendelian genes, phenotypes and DNA. He considers three possibilities, based on the fact that simple systems posses a "largest model" while complex system do not.
The first recognizes that DNA and Mendelian factors are not readily matched but asks that somehow there is a way of getting from one to the other. The second says that the first is not possible, but that a largest model can be used to obtain them independent of that. Finally, we must consider that there is no largest model and that the system is complex.
The next part deals with the biology of the mind. In the introduction he states that the chapters in this part deal with "objectivity". He asserts "As a whole, they argue that attempts to identify objectivity with algorithms and their execution has been a profound mistake.
The first chapter of this section, chapter 4, "The Church-Pythagorous Thesis" reviews some 2000 years of mathematical history to trace Church's Thesis to Pythagorous. It culminates in the recent failed attempts to reduce mathematics to algorithms. In so doing he makes his refutation to the claim that all effective processes are computable. The section on Pythagorous is delightful. It weaves together the issue of genericity with the issues surrounding measurement and the limited use of algorithms to do even basic mathematics. It also raises the issue of commensurability and its devastating effect on the formalist's efforts. The role of mimesis can be summed up by the conclusion that mimesis is not science, it merely mimics science.
Chapter 5, "Drawing the Boundary between Subject and Object: Comments on the Mind-Brain problem", is a paper published in the Journal of Theoretical Medicine. This paper is an example of its own subject and therefore exemplary of the notion of self-referential loops and impredicativities. This of course is a further example of the context dependence of complex systems in contrast to simple systems. In this chapter he reviews the use of mathematics in the study of mind and sets the record straight about the history of neural network theory that actually started with the early work of Rashevsky. This is his first explicit attempt to talk about the mind-brain problem and it immediately is related to the "measurement problem" in physics and the whole basis for the concept of "objectivity". He says in the introduction to this part of the book: "Hence, by extension, a reductionist excursion into the mind-brain problem in the name of objectivity merely exposes the limitations of the reductionist approach itself."
Chapter 6, "Mind as Phenotype" weaves the mind-brain problem into the existing cloth by using a generalization of the arguments already presented in earlier chapters. It is a sequel to the previous chapter, developing a new angle. Here, another important thread is woven in, the Aristotelian causalities. The genome is identified as formal cause and related to phenotype in this manner. The question of the legitimacy of this approach is examined. The inadequate roles of reductionist fractionation and mimesis are dealt with as the examination proceeds. The following admonition is worth noting: "An essential feature of this discussion is the necessity of learning about a material system, not only by taking it apart into subsystems, but also by putting it into larger systems with which it can interact. This is still another set of threads based on Gödel and leading to the notion that complexity demands going outside the system for answers.
This may be a good place to interject a few thoughts from outside the system that Rosen has created. One is the overlap between Rosen's concept of organism and Maturana and Varela's autopoiesis. Another is the use of the modeling relation and semiotics. These are two areas where what Rosen and others are saying may interact in a very constructive way.
Rosen's answer to this is the relational approach that is quite compatible with impredicativites and reaching outside the system for additional system definition due to its context dependence.
Chapter 7, " On Psychomimesis" is a further discussion on mimesis and, in particular, the Turing test. The contrast between mimesis and science is a contrast between synthetic and analytical approaches to the same end. If analysis and synthesis, as used in this context, were simple inverses they would be reconcilable. In complex systems they are not. In short, the mimicry uses a different set of causal relation than exist in the system being imitated in order to obtain a certain form of behavior. The syntactic methods used are unable to deal with the causal relations in the system being examined and thereby circumvent the entire issue. Imitation substitutes for understanding.
Chapter 8, "The Mind-Brain Problem and the Physics of Reductionism" is a direct assault on reductionism and its failure to address the issues it has been used to address. This is because of the absence of algorithms and/or lists of properties which somehow go together to make the whole system.
In this chapter, the essence of what is lacking in the traditional approach to science is summed up very nicely in the critique of the study of the mind: "On the other hand, experience has shown that the resultant lists or algorithms either turn out to be infinitely long, which is unacceptable, or else must turn back on themselves, which is also unacceptable. The latter essentially constitutes impredicativity - Bertrand Russell's viscous circle. Such impredicativities cause semantic referents within them, in this case self-referents that depend entirely on the context created by the circle itself. Attempts to eliminate such circles by purely syntactic(context-independent) means, to express them as a finite list, even in a bigger syntactic system, simply destroy these properties."
Part III of the book is about Genericity. It expands on chapter 2 of Life Itself which dealt with what is general and what is special. He uses Rene Thom's work on Structural Stability and morphogenesis as an example. He then generalizes the concepts by talking about comparing things with their nearby neighbors with respect to some property. If the nearby neighbors also posses the property it is called generic.
Chapter 9, "Genericity as Information", was an essay he contributed to a Festschrift for Rene Thom and it will appear there as a French translation. It harks back to the "What is Life" question and goes further into what can be learned from the interchange of noun and adjective. This thread has much to offer. For example, the words turbulent and turbulence, illustrate the issue very well. As an adjective describing water, air, or oil we find the usual usage that science is comfortable with. It describes a property of real substances. Turn it around and talk about water turbulence, oil turbulence, and air turbulence and the quality has become the object of study rather than the material. The same is true with life and living. Once life becomes a thing, an object of study, science looses its ability to prescribe an approach. We have no process that can separate the noun and adjective aspects of such qualities, they are outside the paradigm. This raises the issue of surrogacy, a thread that intertwines with the modeling relation and other ideas. Catabolic and anabolic modes are clearly aspects of the organism. They are an essential part of the M-R systems and their role in defining life. Reductionism reduces life to a "pile of rubble" and asks that this be a surrogate for the whole, losing any trace of these and other essential properties. Had the issue of genericity been understood, such a poor surrogate would have never been considered.
Chapter 10, "Syntactics and Semantics in Languages, deals with a central thread of the complexity theme. The duality between syntax and semantics is the key to the impossibility of ever bringing reality into a simple system mode of description without the loss of most, if not all, of the meaning. Rosen uses mathematics, a particular language, as a surrogate for languages in general to make his point. He reviews the failure of formalization and its roots in Gödel's work. Church's Thesis is again rejected and the role of inferential structure through entailments is studied. Many of the threads introduced earlier are thereby given further credibility. The modeling relation is reviewed as a means of illustrating how these ideas come together. The recent work of Dress strengthens this tie very well . It puts semiotics into the form of the modeling relation and weaves that together. The "well posed problem" is discussed. The idea that this means stripping off semantics and reducing the problem to syntax suggests that the well posed problem discussion itself is not well posed. Church's Thesis is given more attention using the newly developed threads along with those already woven. It is held up as an antithesis to the well-posed problem. The reliance of complex systems on external referents and closed loops internally makes a strong bond between language and the rest of the world, the external referents of language.
Chapter 11, "How Universal is a Universal Unfolding?" is a more technical, mathematical chapter. In it, Rosen weaves in the argument that involves the exactness of differential forms and the absence of state descriptions of complex systems. Having included an appendix about Carotheodry's proof of the Second Law of Thermodynamics using the integrability of differential forms in my own book, I find this argument a very stimulating one. It has a distinct non-mechanistic, thermodynamic flavor. Here Rosen also weaves the thread further with the distinction between anabolic and catabolic processes and the fact that they are not inverses. This thread delves deeply into the nature of the organism vs. machine distinction along the lines of what is called "path dependence" in the categorization of work and heat as something other than state functions in thermodynamics. What Rosen shows us is that the work and heat type variable is more generic than the state function! The thread about catabolism and anabolism is developed further with the recognition that failure modes, such as the breaking of the beam, are not the reverse of manufacture or synthesis.
Chapter 12, "System Closure and Dynamical Degeneracy" follows up along the lines of the previous chapter. It begins with the dissociation of degeneracy from genericity. Degeneracies are generally not generic. This might seem trite until we recognize how much of what we pay attention to in science is a degeneracy. Even the numbers we use most often are degenaracies among numbers. The discussion turns to the openness of living systems and the degeneracy of closed systems. Alternative views of senescence are couched in this language giving the phenomenon a very fresh meaning.
Chapter 13, "Some Random Thoughts about Chaos and Some Chaotic Thoughts About "Randomness" is a chapter which helped inaugurate the Journal of Biological Systems. I was so impressed by this essay that I used it as a basis of my own essay, " A Close Look at a New Science: Chaos as Science or Science in Chaos" In this essay, the genericity of strange attractors and notions like "life at the edge of chaos" are put into a perspective commensurate with the rest of Rosen's thinking. He is careful to avoid getting into specific arguments about the application of chaotics to science saying it is much too early to tell how much it might eventually contribute. It is clear that he sees a potential for hype and fad to cloud the real nature of what chaos is. In its most clear form it is merely a class of solutions to equations of motion within non-linear dynamics. He also reminds us that as a model for real systems, it has been kept in a "hot house" without environmental or other interactions. There are also discrete forms and continuous forms of equations exhibiting chaotic solutions. Meanwhile, the role of randomness as a model for those parts of systems that we do not intend to specify in detail seems to still have a lot of merit.
In Part IV that deals with similarity and dissimilarity in biology, Rosen covers a number of topics including biological form and morphogenesis. Chapter 14, "Optimality in Biology and Medicine" was originally a tribute to Richard Bellman who was the creator of dynamic programming, a powerful optimization technique.. Rosen has written his own book on optimality in biology. One of the most striking threads is woven in here. He shows that by the use of Hamilton's principle of least action and the analogy from its application in optics, it should have been possible to develop the Schrödinger equation for wave mechanics much earlier. This is a kind of object lesson that the strict adherence to mechanistic thinking in the Newtonian Paradigm can actually keep us from insights gained by other, parallel thought patterns, such as the one being developed in this volume.
Chapter 15, "Morphogenesis in Networks", is Rosen's own version of what is now generally called "Artificial Life". My phrasing it this way is deliberately meant to be provocative because he never thought any of the large body of work called that should have ever been so named. In spite of that, the chapter itself views these objects in a fresh way and makes use of the other ideas in this volume to give the work a different perspective from those who claim too much for a mimetic approach. This chapter would be a good one to look at if one were looking for a thesis topic. It would be even more suggestive if the notion of causal entailment networks in his unpublished work were more readily available.
Chapter 16, "Order and Disorder in Biological Control Systems", is motivated by the problem of senescence. This also is an area where Rosen saw new horizons, yet never was able to complete the journey. He began the ideas in a few papers and in the book Anticipatory systems. His unpublished work carries it a bit further, especially along the lines begun in the earlier works that deal with the whole notion of time. He speaks in terms of the links to the future in the way causal relations are set up in networks. He then introduces the concept of a general system failure as a holistic view of what mechanistic reasoning has failed to explain in spite of much effort and expense. Finally, another important thread is woven in. The existence of side effects in a system captures in still another way the essence of what complexity is all about and why the machine metaphor is inadequate.
Chapter 17, "What Does it Take to Make an Organism?", is an extremely provocative chapter. In it Rosen reviews the development of his concept of organism as distinct from machine using the causal entailment network. He then goes further than ever before toward revealing some things he discussed in a taped interview in July of 1977. In that interview he discussed the moral implications of revealing what he knew about the possibility of fabricating organisms. He was reluctant to do so, yet also felt a pressure to do so. I am not aware of whether or not more information exists on this topic, but I will say that this chapter has to be read by anyone even remotely concerned with the issue.
The final part of the book, Part V, on biology and technology is a treat in its own right. Once again if one wants ideas for future work, this is a rich source. The focus is on what biology has to teach us about other disciplines. Rosen believed that biology was a means for learning to approach complex problems, especially those in human society. The quickness with which complexity science has been applied to human organizations and institutions says that he was on the mark this time too. These matters were reluctantly omitted from life itself for logistic reasons. He says: "The common relational models that bridge biology and the technologies allow us, in principle, to separate the fruits of selection without needing to emulate its methods. They provide a Rosetta stone that allows us to utilize the billions of years of biological experience contained in Nature's encyclopedia, and to realize them in our own ways, applied to our own problems." What a challenge to those who are looking to the future and have realized the latent power of biotechnology!
In this section the metaphor of chimera is introduced as a new thread and woven in with the rest. It connotes a single organism with more than the usual number of parents. Its cells arise from genetically diverse sources. He then makes the analogy with social structures and institutions. He takes the analogy in the other direction to speak about activated complexes in biology. He says " One of the deepest lessons of biology is that such cooperation [between function in chimeras] is selected for; indeed, that life would be impossible with it; and hence that complex organizational problems can be solved via cooperation and not by power and competition."
Chapter 18, "Some lessons of Biology", begins with the biggest lesson to be learned from biology, namely that there are lessons to be learned from biology! The discussion revolves around the hermit crab that becomes an immediate symbol for the cloth woven so far in many ways. The special chimerical nature of this crab in a shell with an anemone attached is full of meaning that he exploits in a delightful way. He concludes that life is too rich a process to rely on programs for its source. Therein is one big clue to the fabrication question.
Chapter 19, "Bionics Revisited" might somehow use the word "cybernetics" to advantage, but doesnt. beginning with some historical remarks, Rosen develops a strategy for biotechnology worth considering seriously. Using the bird wing as a talking point he once more shows us the futility of holding too tightly to the machine metaphor. He then weaves to a conclusion his ideas about complexity, pointing the way to the future and what might be done.
Chapter 20, "On the Philosophy of Craft", is a delightful excursion into the world of reality where "magic bullets (treatments without side effects) do not exist. He then proceeds to tell us what can be expected in such a world. He says:"We are now free to envision strategies involving controllers that are themselves complex .in fact for complex systems in general, complex controllers are the only reasonable hope."
Chapter 21, "Cooperation and Chimera" and Chapter 22, "Are Our modeling Paradigms Nongeneric?" deal with an approach to complex systems based on dynamics. These are in some way the main thrust of the volume. Let me end this summary with a quote from the introduction of this section: " the fabrication of something(e.g., an organism is a vastly different thing than the simulation of its behaviors. In conclusion, any material realization of the (M<R) system [model for an organism] must have noncomputable models ..Thus we have part of the answer to the question with which we started---What does it take to build an organism? It takes a lot more than we presently have. That is why the problem is so hard, but also why it is so instructive."
In conclusion, this book of essays is unique in its scope and content. The scientific world is beginning to discover Robert Rosen, not so much because it wants to or because it likes what he teaches, but because there may be no other way to proceed.
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From the Publisher
Compiling twenty articles on the nature of life and on the objective of the natural sciences, this remarkable book complements Robert Rosen´s groundbreaking Life Itself -a work that influenced a wide range of philosophers, biologists, linguists, and social scientists. Breaking free from the constraints of reductionist reasoning, which maintains that simple, empirical mechanisms are the basis of all life, the renowned biophysicist tackles a remarkable range of subjects that will stimulate similarly far-reaching audiences.
In Essays on Life Itself, Rosen takes to task the central objective of the natural sciences, calling into question the attempt to create objectivity in a subjective world. The book opens with an exploration of the interaction between biology and physics, unpacking Schrödinger´s famous text What Is Life? and revealing the shortcomings of the notion that artificial “intelligence” can truly replicate life. Rosen also challenges the paradox of the brain as organism and the receptacle of scientific reasoning. Elegantly rounding out his argument, the author reflects on the quandary of side effects, moments when science confronts unpredicted outgrowths of a process thought to be reduced to a system.
An intriguing enigma links all of the essays: How can science explain the unpredictable? As a century defined by extraordinary scientific progress draws to a close, Essays on Life Itself is a critical work that asks readers to reconsider what we have learned and where science can lead us in the years to come.
About the Author
Robert Rosen was professor emeritus of biophysics at Dalhousie University and the author of books including Life Itself (Columbia 1991), Principles of Mathematical Biology, and Principles of Measurement.
From the Preface
“This volume is a collection of essays, intended primarily to enlarge upon a number of points that were touched upon in Life Itself. I believe they are of independent interest and importance, but I felt the ideas could not be pursued in that place, since they would detract from the main line of the argument to which Life Itself was devoted.
Thus this volume should be considered a supplement to the original volume. It is not the projected second volume, which deals with ontogenetics rather than with epistemology, although some chapters herein touch on ideas to be developed therein.”
Part I: On Biology and Physics
“To me, the basic question in biology, to which all others are subsidiary or collateral, is the one put most succinctly by the physicist Erwin Shrödinger: What is life?
Any question becomes unanswerable if we do not permit ourselves a universe large enough to deal with the question. Ax = B is generally unsolvable in a universe of positive integers. Likewise, generic angles become untrisectable, cubes unduplicatable, and so on, in a universe limited by rulers and compasses.
I claim that the Gödelian noncomputability results are a symptom, arising within mathematics itself, indicating that we are trying to solve problems in too limited a universe of discourse. The limits in question are imposed in mathematics by an excess of “rigor”, and in science by cognate limitations of “objectivity” and “context independence”. In both cases, our universes are limited, not by the demands of problems that need to be solved but by extraneous standards of rigor, The result, in both cases, is a mind-set of reductionism, of looking only downward toward subsystems, and never upward and outward.”
Chapter 1: The Shrödinger Question, What is Life? Fifty-five Years Later
“Open systems thus constitute in themselves a profound and breathtaking generalization of old physics, based as it is on excessively restrictive closure conditions, conservation laws, and similar nongeneric presumptions that simply do not hold for living things. Seen in this light, then, is it really biology that is, in Monod’s words, “marginal,” “a tiny and very special part of the universe,” or is it rather the old physics? In 1944, Shrödinger suggested that it was the latter that might be the case. Today, fifty-five years later, that possibility continues to beckon and indeed, with ever-increasing urgency.”
Chapter 2: Biological Challenges of Contemporary Paradigms of Physics and Mimetics
“The following remarks are intended to address two problems: (a) the role of contemporary physics in dealing with nature and properties of living systems, and (b) the role of mimetic approaches (usually prefaced by the adjective artificial) in dealing with these same matters.”
Chapter 3: What is Biology?
“In this chapter, I had intended to consider only the legitimacy of identifying two very differently defined things: a “Mendelian gene,” defined in indirect functional terms via its manifestations in larger systems (phenotypes), and an intrinsic structural feature (sequence or primary structure) of a polymeric molecule. As it turned out, this question could not be readily separated from its own, deeper context, one that goes to the very heart of reductionism itself.”
Part II: On Biology and the Mind
“The mind-brain problem is somewhat apart from my direct line of inquiry, but it is an important collateral illustration of the circle of ideas I have developed to deal with the life-organism problem. I do not deny the importance of the mind-brain problem; it was simply less interesting to me personally, if for no other reason than that one has to be alive before being sentient. Life comes before mind, and anything I could say about mind and brain would be a corollary of what I had to say about life. That is indeed the way it has turned out.”
Chapter 4: The Church-Pythagoras Thesis
“It is my contention that mathematics took a disastrous wrong turn some time in the sixth century B.C. This wrong turn can be expressed as an ongoing attempt, since then, to identify effectiveness with computability. …. “The impact of that wrong turn, made so long ago, has spread far beyond mathematics. It has entangled itself into our most basic notions of what science is. …. From this common concern with measurement, concepts pertaining to mathematics have seeped into epistemology, becoming so basic a part of the adjective scientific that most people are quite unaware they are even there.”
Chapter 5: Drawing the Boundary Between Subject and Object: Comments on the Mind-Brain Problem
“The identification of objectivity with what is independent of or invariant to (these are not the same) perceivers, or cognizers, or observers, is what has led to the current infatuation with the machine as simulacrum of life and mind. Roughly speaking, if a machine can “do” something, that is prima facie evidence of its objectivity, and of its admissibility into science. Hence the conflation of mechanism with what is objective, and the relegation of anything nonmechanistic to the realm of the subjective, the ad hoc, the vitalistic, the anthropomorphic: in short, beyond the pale of science.
I shall argue, to the contrary, that mechanism in any sense is an inadequate criterion for objectivity; that something can be objective (and hence a candidate for scientific scrutiny) without being in any sense a mechanism. That is, the perceived dichotomy between mechanism and vitalism (i.e., denial of the former means affirmation of the latter) is a false one.”
Chapter 6: Mind as Phenotype
“An essential feature of this discussion is the necessity of learning about a material system, not only by taking it apart into subsystems, but also by putting it into larger systems with which it can interact. …. In biology, these two ways of viewing a given material system are already radically different, and highly inequivalent. But as we have noted, the invocation of specific larger contexts creates impredicativities that contemporary physics does not like to admit; that is precisely why there is a measurement problem in physics, and a life-organism problem in biology, and a mind-brain problem. Such problems ultimately force us into some deeply ingrained habits of thought, which it is entirely possible are bad habits.”
Chapter 7: On Psychomimesis
“This argument from a mimesis to an identity is a version of the Turing Test, designed by Turing (1950) to provide an answer to the question, Can a machine think? and thereby to provide an operational characterization of thought itself. It is precisely this kind of extrapolation that allows mimesis to encroach on science and even on mathematics, as we shall see. In fact, the real question, approached mainly in the context of machines, brains, and minds, is the extent to which mimesis is in itself science or is only a mimic of science.”
Chapter 8: The Mind-Brain Problem and the Physics of Reductionism
“Problems such as the mind-brain problem appear hard because they involve properties (e.g., life and mind) that depend on impredicativities within the systems x that manifest them. …. Just as an attempt to break open an impredicative loop in a mathematical system, and replace it by a finite syntactic list or algorithm, destroys all properties of the loop itself, so any attempts ot fractionate a material system containing closed causal loops destroys all of its properties that depend on such an internal loop. Such fractionations constitute a material version of formalization, artifactual as far as questions like the mind-brain problem are concerned.”
Part III: On Genericity
“It was a main thrust of Life Itself that what is more generic does not merely reduce to what is less so – it is more the other way around. In particular, I argued that mechanistic systems are nongeneric in several basic ways; they are simple, whereas most systems are complex. I characterized the nongenericity of simple systems in terms of their infinitely feeble entailment processes, either causal entailment in natural systems or inferential entailment in formalisms. From the standpoint of complex systems, simple ones are infinitely degenerate; they are like a high-order polynomial, most of whose roots coincide.”
Chapter 9: Genericity as Information
“Indeed, most of the truly radical aspects of Thom’s book [Structural Stability and Morphogenesis] have never been discussed at length; the book itself is largely viewed as a wrapper for the Classification Theorem. But that theorem, conspicuous as it is, is only the tip of an enormous iceberg. I will go beneath the water a bit to explore some of the architecture of that iceberg, especially concerned with the implications of genericity for science in general, for the deeper relations between biology, physics, and mathematics it reveals, and above all, the the theoretic and philosophical principles buried in it.”
Chapter 10: Syntax and Semantics in Languages
“[W]e cannot identify pure syntax with objective, and dismiss all the rest as subjective. A language fractioned from all its referents is perhaps something, but whatever it is, it is neither a language nor a model of a language. …. The main issue, however, is that, just as syntax fails to be the general, with semantics as a special case, so too do the purely predicative presuppositions underlying contemporary physics fail to be general enough to subsume biology as just a special case. This kind of attitude is widely regarded as vitalistic in this context. But it is no more so than the nonformalizability of Number Theory. Stated another way, contemporary physics does not yet provide enough to allow the problems of life to be well-posed.”
Chapter 11: How Universal is a Universal Unfolding?
“On the face of it, however, bifurcation theory should be as much a representation of system generation as of system failure. Indeed, in generating or manufacturing a mechanical structure, such as a bridge, we need the bridge itself to be a bifurcation point, under the very same similarity relation pertaining to failure modes; otherwise we simply could not even build it. The fact that we cannot in general interpret universal unfoldings in terms of generation modes as we can with failure modes raises a number of deep and interesting questions. Obviously, it implies that the universal unfolding is far from universal.”
Chapter 12: System Closure and Dynamical Degeneracy
“At issue here is the profound question of how to create a physics of open systems – specifically, a physics which will be powerful enough to encompass the material basis of organic phenomena. The prevailing approach, which has developed historically over a period of centuries, is to take the closed, isolated, conservative system as primary, and attempt by one means or another to open it up. (Nicolis and Prigogine 1977). The considerations sketched above indicate that this is at best the hard way to go about it; as we have indicated, the closed systems are so degenerate that essentially anything can happen. The alternative strategy is to acknowledge the primacy of open systems, and forget about closed systems in this context altogether.”
Chapter 13: Some Random Thoughts about Chaos and Some Chaotic Thoughts about Randomness
“By its very nature, nongeneric dynamics is inherently less robust, in the face of truly arbitrary environments. Indeed, nongeneric dynamics can look robust only if we severely restrict the genericity of the environment as a source of system fluctuations. Perhaps, indeed, the way to discriminate between “chaotics” and its alternatives lies precisely here – pushing a system into a truly arbitrary niche and seeing what happens. It is, of course, equally possible that both pictures are wrong (Rosen 1979), that dynamics itself is already too nongeneric.”
Part IV: Similarity and Dissimilarity in Biology
“The chapters in this part cover a variety of more special topics and applications, especially to biological form and to morphogenesis.”
Chapter 14: Optimality in Biology and Medicine
“One explicit way of excluding telos from physics is by postulating that present change never depends on future states (or future forces). To us, this still seems reasonable enough; it is easy to accept that such a dependence on the future is incompatible with traditional views of determinism. On the other hand, it was early recognized that the variational principles of physics, which we reviewed above, seem already to violate this maxim; we need both a present and a future configuration to determine a path. Thus, the Principle of Least Action, say, which is at the very heart of theoretical mechanics, looks more telic than mechanics itself allows. This has always bothered people, and many have taken the trouble to rationalize it away on various grounds, which we need not pause to review here. But these facts point to perhaps a deep relationship between the nature of optimality principles in general and the things we do not understand about organic phenomena.”
Chapter 15: Morphogenesis in Networks
“One of the most ancient, and at the same time the most current, fields of theoretical biology is that concerned with morphogenesis – the generation of pattern and form in biological systems. This chapter is devoted to the development of an integrated framework for treating morphogenetic problems, not only because they are of the greatest interest and importance in their own right but also because they tell us some important things about theoretical biology in general, and they help us articulate the position of biology vis-à-vis other scientific disciplines.”
Chapter 16: Order and Disorder in Biological Control Systems
“As we have seen, the concept of entropy loses all significance once we depart from the choice of closed, isolated systems as standards. We can retain the term for open systems, but only at the cost of inventing an increasingly unwieldy formalism of “entropy fluxes,” which are attempts to create new Lyapunov functions for the open system dynamics. If the system is open enough, this whole approach fails; the problems associated with open systems are dynamical problems and not thermodynamic ones.”
Chapter 17: What Does It Take to Make an Organism?
“To attach synthetic significance to analytic fragments and, still more, to believe that analytic knowledge (i.e., a knowledge of how something works, its physiology) can tell us something about it’s creation, its ontogenesis, is an article of faith inherited from the machine metaphor…. It is a most unfortunate legacy; in too many ways, it leads us in exactly the wrong direction. It identifies analysis with synthesis, replacing the latter with the former. What we must do, rather, is to separate them again. The process of doing this, however, takes us immediately outside the machine metaphor itself and everything it rests on.”
Part V: On Biology and Technology
“I have long believed, and argued, that biology provides us with a vast encyclopedia about how to solve complex problems, and also about how not to solve them. Indeed, biological evolution is nothing if not this, but its method of solution (natural selection) is, by human standards, profligate, wasteful, and cruel. Nevertheless, the solutions themselves are of the greatest elegance and beauty, utterly opposed to the discordances and mortal conflicts that created them. We cannot use Nature’s methods, but we can (and, I believe, we must) use Nature’s solutions.”
Chapter 18: Some Lessons of Biology
“Perhaps the first lesson to be learned from biology is that there are lessons to be learned from biology.”
Chapter 19: Bionics Revisited
“We shall not, in the following, be directly concerned with such questions [re the impact of bionics], but rather with another that illuminates them, and that can be phrased roughly as Where (if anywhere) does machine end and organism begin? Machine and organism are essentially different in kind, and, as a consequence, the concept of machine does not exhaust the dimensions of technology.”
Chapter 20: On the Philosophy of Craft
“Indeed, the entire concept of craft changes completely when dealing with complex systems. For we cannot generically approach them exclusively by simple means. There is a sense in which complex systems are infinitely open; just as with any infinite thing, we cannot exhaust their interactive capacities by attempting to control their parameters one at a time. In particular, the simple control cascades previously mentioned will generally not break off; hence, magic bullets of this character will generally not exist.”
Chapter 21: Cooperation and Chimera
“Here I shall take a look at the evolutionary correlates of chimera formation, and particularly at chimera in the sense of an adaptive response, based on modes of cooperative behavior in a diverse population of otherwise independent individuals competing with each other as such. If we take chimera seriously, in the sense of being a new individual with an identity (genome) and behaviors (phenotype) of its own, we can raise some deep epistemological and system-theoretic questions. These range from the efficacy of reduction of a chimera to constituent parts, all the way to sociobiology (i.e., what is phenotype anyway?), and beyond.”
Chapter 22: Are Our Modeling Paradigms Nongeneric?
“I shall proceed with a discussion of the concept of genericity, culminating in an argument that simple systems are nongeneric (rare). I will then discuss the related concept of stability, and the testing for stability by applying generic perturbations. I will conclude by showing that dynamical systems, systems of differential equations, become complex when generically perturbed, and I will briefly discuss what this means for the scientific enterprise.”