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Life Itself

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Robert Rosen asks the question: what is life?, and answers the question precisely after 10 chapters. His method of answering the question is ground breaking. In trying to answer the question of, What is Life? he first must explore what life is not. In that process of trying to answer the question about life, he had discovered something *very* important about science and mathematics: there are some unnecessary limitations placed them, currently.

Robert Rosen *precisely* shows the reader the logical limitations of current scientific thinking in the form of modern physics and the machine metaphor. This is not your typical rant on reductionism. Everybody has hear the reframe against reductionism, "the whole is more than the sum of the parts," but Rosen shows in precise terms, much more: there is a limitation of modes of entailment (inference). The book is not easy reading, not because it is poorly written, for Rosen is a great writer, but because it examines the foundations of science, mathematics, and computer science (essentially anything having to to logical investigation). By trying to answer the question: what is life?, Robert Rosen shows us that the Newtonian paradigm (including all of modern physics, such as string theory, quantum loop gravity, and relativity) cannot and will not be sufficient to answer the important questions that not being ask in physics. Their modes of entailment are limited unnecessarily using the machine metaphor (e.g. differential equations and recursion, such as the Schrödinger's wave equation or Einstein's field equations). One of his results is to show precisely why physics (including molecular biology) has little to say about life (and non-life). He proves that Alonzo Church's thesis cannot be true, and demonstrates a revolutionary methodology (akin to precise analogy -- category theory) can help answer questions not asked by reductionistic science. Rosen examines physics, mathematics, biology, computer science with great insight and points the way to the future of science, in the use of precise mathematical metaphor; that is, by reasoning about function (as opposed to structure) by doing a primitive form of comparative complexity.

Life Itself is the best introduction into Robert Rosen's revolutionary work: any scientist not completely blinded by the machine metaphor or lacking in enough background, should be able to "get it" with some work and concentration. Don't be fooled and bogged down by the first three chapters; this is, the ground breaking book: on par with Newton's Principia and Darwin's Origin of Species. However, don't expect to get everything on the first (or tenth) reading.

A guide to the book: getting through Preface, Note to Reader, Praeludium, Chaps 1-3, Chapter 4 is crucial, this is where he sets up the problem and deconstructs Newton's technique (dynamics) and shows its weakness. Chapter 5 shows that there is another way. (Life Itself is not the standard (and vague) rant against reductionism - he shows an alternative.) In Chapters 6-9 he deconstructs simulation and the machine metaphor and shows it is equivalent to the Newton paradigm. Chapter 10 and 11 give you a good understanding why he went to so much trouble. What he doesn't say explicitly in this book, for his interest is in biology, is that his methodology is applicable to ALL of Science and mathematics, not just biology.

His Anticipatory Systems book (his previous book) is just as good, but the book Life Itself is crucial to read to understand the importance of his ideas, and is the best introduction. Unfortunately, Anticipatory Systems is out of print. Its going to take awhile for science, mathematics, and computer science to catch up. His last book, published after his death, Essays on Life Itself, is icing on the cake.

In his short story, "The Wall Of Darkness", Arthur C. Clarke (cf. Tales From Planet Earth), described Trilorne, a world in which all exploration was forced to end by a wall that appeared to extend to the very heavens. In this brilliant and thought provoking book, a summing up of over 30 years of careful analysis, the late Dr. Rosen argues forcefully for the presence of just such a wall between what he called "simple systems" (roughly, systems that are algorithmic), and "complex systems" (everything else). His main thesis is that biological systems were complex and as such, beyond the ken of algorithmic approaches. The book also outlines rudiments of an alternative approach, the "closed causal loop" model of complex systems. The book explores the concept of a model and the act of modeling, state-based models (a particularly brilliant discussion), analytic and synthetic categories, the Turing machine and it's relation to simple systems, and the relevance of Aristotelian causality for biology. Causality is unfashionable at the moment (in particular Aristotle's view of it); Rosen's gift for finding gold in strange mines is nowhere more evident than his use of causality to build his alternative approach.

Dr. Rosen was one of those unfortunate scientists who worked on problems, that to the rest of his community were non-existent. This decade has been a little kinder to his work. The increasingly evident general intractability of problems in disparate areas such as artificial intelligence (consciousness,intelligence) linguistics (symbolic reference), artificial life (speciation), computer vision (pattern recognition), and algorithmics (e.g. protein folding problem) led credance to Rosen's claims.

The book itself is very carefully constructed; there are other obvious hints that he intended this book to reflect parts of his theory. Rosen's style, as always, is magisterial, and sometimes even poetic. Perhaps the readers most likely to benefit from this work are those who have confronted the wall at some point in their own careers.

In Clarke's short story, Trilorne's universe turned out to be a Mobius strip. The wall had no other side, and all journeys ended at the beginning. It may well be that the limitations seen in these areas are fundamental, and that *no* approach will work. Yet, the joyous abundance of life itself and this work suggests otherwise.

Although many influential scientists (Steven Weinberg, Francis Crick, and Richard Dawkins, for example) claim - and most members of general public believe - that all of reality can "in principle" can be expressed as the dynamics of its constitutive elements (atoms, genes, neurons), some have intuitively felt that this reductive tenet is wrong, that life and the human mind are more complex phenomena. Critics of reductionism have pointed to Kurt Goedel's 1931 "incompleteness theorem" (which shows that in any axiomatic formulation of, say, number theory there will be true theorems that cannot be established) as a contrary example, but this paradigm-shattering result has been largely ignored the scientific community, which has blithely persisted in its reductive beliefs.

How is one to understand this curious situation? In Kuhnian terms, it seems that reductionism persists because this old paradigm has not yet fallen out of favor. Leaders in physics have not yet taken the public stance required by Goedel's theorem and assertions in their textbooks have not changed. Why not? Perhaps because Goedel's theorem relates to mathematics rather than reality, or perhaps because recognizing its import diminishes the status of physics as the primary science.

With the publication of Robert Rosen's LIFE ITSELF, the other shoe has dropped. In a carefully constructed exposition developed over eleven reader-friendly chapters, Rosen shows how something akin to Goedel's theorem applies to the natural world, and in particular to biology. Thus Rosen shows that all dynamical systems can be divided into two broad classes: "simple systems" for which the reductive paradigm holds and "complex systems" for which it does not hold. Note, however, that by the term "complex system" Rosen means something more specific than the way that the same term is used in chaos theory. Low-dimensional dynamical systems that exhibit chaos are "simple" to Rosen, whereas the term "complex" is reserved for those systems that cannot be simulated. Thus a Turing machine is "simple" as is the weather system proposed by Edward Lorenz as a model weather system that exhibits "irregular" (i.e., chaotic) solutions and the well-known "butterfly effect." "Complex systems" - Rosen proves in the sense that mathematicians use the term "prove" - comprise natural systems that cannot be simulated.

As a physicalist whose intuition has long suggested that reductive perspectives are too narrow to encompass living organisms and human consciousness (see my STAIRWAY TO THE MIND), the discovery of this book has been an illuminating experience for me. Having just read it word for word over three increasingly exciting days, I strongly recommend LIFE ITSELF to all who would understand the limits of science as it is currently practiced and preview the ways that linguistics, biology, cognitive science, and the social sciences (psychology and cultural anthropology) can be expected to develop in the present century.

Alwyn Scott
[...]

The other reviewers have already described the contents of Rosen's work sufficiently well that I will not bother to restate it all.

Instead, I want to stress that this book and his "Essays on Life Itself" are so profound and intelligently argued that anyone interested in any of the physical sciences, not just theoretical biology, will gain a great deal of insight and appreciation for the limitations of the current state of physics, upon which so much science is now based, as well as offering insights into ways of enriching physics, and the sciences in general.

The use of category theory and similar math should not deter any astute layperson, for although the math supports the arguments brilliantly, the arguments are well-described. What will be more difficult, in fact, is successfully grasping the results of the arguments in their full profundity.

This book rightfully deserves to have as widespread paradigm-shattering impact on physical science as Godel's "On Formally Undecidable Propositions of Principia Mathematica and Related Systems" had on mathematics.

Rosen showed that, in fact, biology is not merely a trivial subcategory of physics; but instead that biology displays physical systems that are beyond the limited scope of current physics. And that enriching physics to encompass biological systems would enhance all of physics in very profound ways.

Sadly, I can only assume that it was (and still is) the ideological view of biology as a mere curiosity of physics that has allowed so many in science to fail to read Rosen's work.

I've been working on a book about the human relationship with nature, starting from thinking about water, and gradually my research has made it seem inevitable that I would have to tackle Rosen's book. I'm an English professor, not a scientist, not a mathematician. I'm fascinated by the overturning of the Newtonian paradigm and by new understandings of causation that are unfolding in contemporary science. Rosen's mighty work is about exactly these things. Using mathematics as a rigorous way of thinking about thinking, his book (if I understand it somewhat) undertakes to demonstrate -- prove -- that the Newtonian explanation of physical reality is utterly insufficient to deal with the challenges of biology, because that explanatory paradigm does not admit enough causality into its description of the world. Rosen challenges the supremacy of physics among the natural sciences, and he argues for readmitting all four of Aristotle's types of causation (material, efficient, formal, and final) into the world of scientific inquiry. I am certain there are bold and profound implications to his argument that I was unable to appreciate because, at this point in life, I don't have time to go back to college and grad school in mathematics. Nonetheless, this is a brilliant, authoritatively written, deeply challenging book.

This is an deep and complex book. Rosen addresses what he considers to be the core theme of biology, "What is Life?" from a relational biology perspective. Although the book requires close reading and intense concentration, the journey is highly rewarding. Rosen's work is intricately constructed and addresses core foundations regarding modeling and the representation of living systems.

Written from a biological perspective with a fair amount of mathematics in the form of category theory, Rosen builds up the concepts of formalism, semantics, models and modeling relations, the concept of state, entailment, relational biology, simulations and machines. Rosen discusses the historical notion of recursive state in Newtonian science and the concept of functions entailing functions (and closed systems of entailment) in living systems.

Despite the biological perspective, this is intriguing stuff for systems researchers and systems theorists as well. Although the material relies heavily on mathematics, I'm no mathematician so there is hope for those who are merely comfortable with mathematical expression. Rosen does proceed very carefully through these topics, giving the non-mathematician a chance to keep up, although I suspect that a previous familiarity with abstract algebra, topology, set theory, or category theory would make the journy all the easier.

So, overall it is a challenging read. I have never really read anything quite like it. The exposition is tightly controlled and not a moment is wasted. My hardbound is well broken in and many a valuable nugget has been extracted on numerous successive readings of the material.

It is hard to believe this book is not better known considering the nature of its views. At least, one wonders why so few who are "experts" in the area seem unaware of it since it appears to stand unrefuted. But then again, we are talking about a book that points out the serious limitations inherent in our whole scientific framework that has become today's religion.

Rosen starts by discussing concepts of life: what is it? He then runs through the reasons why it is considered a "hard" problem with the present Newtonian-based framework. He covers the difference between syntax and semantics, Godel, causality and complexity in a very informative yet also accessible manner.

He then gets to the meat of his thesis, the discussion of the fundamental axioms inherent in our present scientific viewpoint. This section has enough of an overview that I believe most people will grasp what he is driving at. That is, the concepts of modeling and entailment that are to be formally dissected in later chapters are very well explained so that there limitations may be understood.

It is the true nature of our models and their methods of encoding the world that Rosen is primarily exposing. Rosen goes back to Taylor's Theorem and demonstrates how Newton's "Laws of Nature" built in fundamental constraints on the nature of the whole scientific enterprise. Unfortunately I suspect the math here may be beyond some people although it really is only slightly more advanced that what is typically learned in high school - this is, in fact, the way it should be taught in the first place.

After laying this groundwork Rosen returns to his discussion of why the type of entailment specified through Newton's fundamental constraints limits any applicability to the "real" world. He introduces Rashevsky's ideas and then develops excellent methods of notation in order to delve more deeply into relational biology.

Then he moves to Analytic and Synthetic models which are compared and contrasted. The uses these ideas to introduce the concept of a machine (loosely based on Turing's ideas). And finally he delves into the relational limits of machines. All this work leads to:

"The picture we have painted looks bleak indeed, if we insist on identifying science with mechanism. But we must recall that there is no basis for such an identification."

And there we have it - just what many have been saying for quite a while just without the full technical details provided by Rosen.

There probably is enough evidence to finally convince the die-hards that this view is correct now that we have the spectacular failure of the genome-mapping project (well, it isn't a failure in some ways but it is for those fanatics of Dawkins and Crick) and the even more spectacular failure of the new priests of complexity. It should be more obvious that we need a new framework, not more shaky models built on axioms that are the problems in the first place.

Let us hope more people read this book so that some of the arrogance may be dispelled...

A very good book indeed. Rosen's depth of understanding of a very wide range of issues pertaining to a aspects of science, philosophy, especially epistimology, is remarkable. It is obvious Rosen has thought long and hard about the problems he addresses in this book. A reminder however that this book is not for laymen, it is quite technical requiring I would say up to 3rd year undergraduate pure mathematics: set theory, group theory, lattice theory, graph theory and category theory. None of these are trivial or straightforward, although amazingly Rosen shows just how transparent these theories can be if explained in a way that has direct meaning rather than the dry, symbolic way they are taught in the usual pure maths courses. Rosen uses these mathematical constructions to configure a very solid basis of the modelling procedure used in science whether physics or biology. Through the idea of maps and constructing the so-called modelling relation" he investigates very thoroughly the way to both analyse and synthesise models of the natural world. He first takes one on a short discourse on the philosophy required such as the perceiver and the observer and how the world is related and seen by them. He looks closely at the standard approaches people have used throughout the centuries of the development of science. Aristotle whose work was discredited through a lack of understanding of it in the last 4 centuries is revived especially his ideas of causation: efficient, material, formal and also final cause which is the problem area of normal science today where no final cause could possibly be acceptable since in the usual interpretation it refers to the backward causation in time from effects to causes. Rosen touches on many areas of contention and one does not expect most scientists to accept his views.

Rosen then, through his very general relational approach, constructs the ideas of mechanism and machines as they are conceived of today. He shows very clearly that natural phenomena, especially living organisms, cannot possibly be machines or that physics, the science which is supposed to be more basic than biology, cannot encompass biology either given its mechanistic approach. He shows that organisms are entailed within themselves in a simple way and goes on to say that physics has much to learn from this approach. The comments of Bohm come to mind when he mentioned that the sea of electrons almost appears to be alive. Rosen doesn't waffle, he doesn't talk in round about ways or use approaches which have no relation to already existing ideas. He uses very simply well understood mathematics to construct a theory of the natural world which surpasses the normal mechanistic paradigm, very easily and completely so that one wonders why anyone was ever so captivated by it in the first place or why thinking is so confined by it. Rosen is always clear and his reasoning is sound.

All in all a remarkable book. I felt that this was just the start of his whole endeavour and that there is much that he hasn't said or written down. Too bad this and the book of essays was his last work.

There are a couple of criticisms, there are quite a few spelling mistakes and typing errors and he doesn't allow that set theory isn't the be all and end all, this is still his basis and stays that way. The possibility that there are other ways to approach reality than set theory and maps his never considered but then that would have been an incredible achievement. Who knows what gems he never mentioned.

Life Itself is somewhat a seminal work of modern complexity research. The author makes a convincing case that life itself is quite complex. So complex, in fact, that it would be hard to ever understand it by using only the narrow lenses that "hard sciences" like physics and chemistry provide.

While still relevant, it is nice that you can purchase used copies of the book that are in great condition for a fraction of the $90 price of a new copy.

I have first heard about this book in an international meeting dealing with origin-of-life. The conference itself had a good representation of computer scientists and some of them talked with esteem about this work. I am involved in research on origin-of-life so I was very eager to read it as it gives premise to be dealing with the many problems we face in this field.

I cannot, however, share the enthusiasm of other reviewers. A chemist or biologist have nothing to look for here.

I cannot say whether I agree or disagree with the views and arguments put by the author as there were completely unintelligible to me. It might be my fault as I might be simply not bright enough to understand Rosen's horizon of mind. But I might answer that if someone wish to disseminate his opinions he should write even about the most difficult subject with as much clarity as it is possible. Rosen fails to achieve this. Having a graduate degree in any of the natural sciences seems not enough to grasp Rosen's thought. It appears to me that a mathematician is the only possible recipient of this book.

This perhaps can explain to other reviewers why this book is so little known among general public or even in general scientific community. It is not even clear to me whether this book deals with life itself or maybe physics itself or maybe both. I definitely learn nothing about neither by reading this work.

This said the book has few other shortcomings. Rosen's writing style is very bothersome. Reader is constantly referred to few chapters back or few chapters forward. This alone is very irritating but is even amplified by often references to other Rosen's work. Thus the reader if left thinking: "Do I don't understate the arguments because I haven read chapter 4 carefully enough or because I haven't reached chapter 8 yet? Or maybe because I haven't read Anticipatory Systems or something else before?". Or maybe it is just badly written?

Add to this we have the "shalling". "We shall see...", "we shall demonstrate in chapter 7..", "we shall do that and then we shall proceed". If Guinness book of records will start a category of the biggest percentage of shalls in a text, this work shall for sure be nominated.

We also have the laudatory references to Nicolas Rashevsky. Rosen fails however to mention that he himself was a Rashevsky's student. Therefore his remarks are not just those of a fellow scientist who deplores that Rashevsky's great achievements are not recognized but are those of a fellow traveller.