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Complexity: The Emerging Science at the Edge of Order and Chaos
A look at the rebellious thinkers who are challenging old ideas with their insights into the ways countless elements of complex systems interact to produce spontaneous order out of confusion
380 pages, Hardcover
First published January 15, 1992
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July 20, 2015
I cannot recall the last time I enjoyed a book of any kind this much.
There is a stark difference between the way a book like this was written in 1990 and the way such books are written just 25 years later. The author, then, had two assumptions: His reader did not know very much, and his reader was very intelligent. M. Mitchell Waldrop, subsequently, explains with brevity and sophistication every idea.
Today's equivalent, a catastrophe like The Upright Thinkers, assumes the opposite: Today's reader knows everything, because of Google, and today's reader is a moron with a chipmunk's attention span. Therefore, stay in the first-person and make it glib!
Anyway, here are some examples from the wonderful Complexity:
It's essentially meaningless to talk about a complex adaptive system being in equilibrium: the system can never get there. It is always unfolding, always in transition. In fact, if the system ever does reach equilibrium, it isn't just stable. It's dead. And by the same token, there's no point in imagining that the agents in the system can ever "optimize" their fitness, or their utility, or whatever. The space of possibilities is too vast; they have no practical way of finding the optimum. The most they can do is change and improve themselves relative to what the other agents are doing. In short, complex adaptive systems are characterized by perpetual novelty. (p. 147)
and
Holland, however, saw such top-down conflict resolution as precisely the wrong way to go. Is the world such a simple and predictable place that you always know the best rule in advance? Hardly. And if the system has been told what to do in advance, then it's a fraud to call the thing artificial intelligence: the intelligence isn't in the program but in the programmer. No, Holland wanted control to be learned. He wanted to see it emerging from the bottom up, just as it did from the neural substrate of the brain. (p. 185)
and
It's a lot like the difference between solids, where the atoms are locked into place, and fluids, where the atoms tumble over one another at random. But right in between the two extremes, he says, at a kind of abstract phase transition called "the edge of chaos," you also find complexity: a class of behaviors in which the components of the system never quite lock into place, yet never quite dissolve into turbulence, either. These are the systems that are both stable enough to store information, and yet evanescent enough to transmit it. These are the systems that can be organized to perform complex computations, to react to the world, to be spontaneous, adaptive, and alive. (p. 293)
This book is an intellectual experience that delights.
There is a stark difference between the way a book like this was written in 1990 and the way such books are written just 25 years later. The author, then, had two assumptions: His reader did not know very much, and his reader was very intelligent. M. Mitchell Waldrop, subsequently, explains with brevity and sophistication every idea.
Today's equivalent, a catastrophe like The Upright Thinkers, assumes the opposite: Today's reader knows everything, because of Google, and today's reader is a moron with a chipmunk's attention span. Therefore, stay in the first-person and make it glib!
Anyway, here are some examples from the wonderful Complexity:
It's essentially meaningless to talk about a complex adaptive system being in equilibrium: the system can never get there. It is always unfolding, always in transition. In fact, if the system ever does reach equilibrium, it isn't just stable. It's dead. And by the same token, there's no point in imagining that the agents in the system can ever "optimize" their fitness, or their utility, or whatever. The space of possibilities is too vast; they have no practical way of finding the optimum. The most they can do is change and improve themselves relative to what the other agents are doing. In short, complex adaptive systems are characterized by perpetual novelty. (p. 147)
and
Holland, however, saw such top-down conflict resolution as precisely the wrong way to go. Is the world such a simple and predictable place that you always know the best rule in advance? Hardly. And if the system has been told what to do in advance, then it's a fraud to call the thing artificial intelligence: the intelligence isn't in the program but in the programmer. No, Holland wanted control to be learned. He wanted to see it emerging from the bottom up, just as it did from the neural substrate of the brain. (p. 185)
and
It's a lot like the difference between solids, where the atoms are locked into place, and fluids, where the atoms tumble over one another at random. But right in between the two extremes, he says, at a kind of abstract phase transition called "the edge of chaos," you also find complexity: a class of behaviors in which the components of the system never quite lock into place, yet never quite dissolve into turbulence, either. These are the systems that are both stable enough to store information, and yet evanescent enough to transmit it. These are the systems that can be organized to perform complex computations, to react to the world, to be spontaneous, adaptive, and alive. (p. 293)
This book is an intellectual experience that delights.
January 19, 2009
What can I say about this book? Complexity is one of my favorite topics - the world is made of individual agents reacting to limited local factors, and their interaction produces sophisticated emergent systems. Awesome.
And this book manages to make it seem like a boring administrative task.
Maybe I'm coming to this book too late. I've been seeing the world through complexity-colored glasses for years, so this book seemed plodding. Dull. No matter the discipline, Waldrop barely manages to capture the basics of complex systems. Maybe they were a difficult, new topic when this book was written in 1992. Maybe the ideas of the Santa Fe institute (WTF? Who cares?) have already managed to permeate all of academia enough to make it seem stupid. But I doubt it. More likely, this guy was trying to make a story out of an understanding that most scientific disciplines already have.
This book is not an exploration of ideas: it's a history of academia - of one institute that apparently lays claim to the idea of emergence, and the old White guys who think they're revolutionary by thinking about it.
Ugh, a pet peeve - Waldrop seems to think that the order of complex systems is somehow antithetical to evolution. Where did you come up with this nonsense? It's a huge revelation for him when someone comes close to reconciling them. The awesome thing about emergent systems is that the complexity comes about through evolution at the individual level! Have you even been listening?
Anyway. Search Google for emergence, emergent systems, complex adaptive systems, flocking or schooling behavior, evolutionary algorithms, cellular automata, neural networks, self-organizing systems, or PRETTY MUCH ANYTHING ELSE REALLY COOL, and you'll get a better idea of complexity than this book would give you.
And this book manages to make it seem like a boring administrative task.
Maybe I'm coming to this book too late. I've been seeing the world through complexity-colored glasses for years, so this book seemed plodding. Dull. No matter the discipline, Waldrop barely manages to capture the basics of complex systems. Maybe they were a difficult, new topic when this book was written in 1992. Maybe the ideas of the Santa Fe institute (WTF? Who cares?) have already managed to permeate all of academia enough to make it seem stupid. But I doubt it. More likely, this guy was trying to make a story out of an understanding that most scientific disciplines already have.
This book is not an exploration of ideas: it's a history of academia - of one institute that apparently lays claim to the idea of emergence, and the old White guys who think they're revolutionary by thinking about it.
Ugh, a pet peeve - Waldrop seems to think that the order of complex systems is somehow antithetical to evolution. Where did you come up with this nonsense? It's a huge revelation for him when someone comes close to reconciling them. The awesome thing about emergent systems is that the complexity comes about through evolution at the individual level! Have you even been listening?
Anyway. Search Google for emergence, emergent systems, complex adaptive systems, flocking or schooling behavior, evolutionary algorithms, cellular automata, neural networks, self-organizing systems, or PRETTY MUCH ANYTHING ELSE REALLY COOL, and you'll get a better idea of complexity than this book would give you.
April 16, 2020
The Santa Fe Institute is an influential interdisciplinary research institute. Since its inception in 1984, it has managed to bring together brilliant physicists, biologists, computer scientists, and economists under the novel banner of complexity (or complex adaptive systems) research. Intended for a popular mid-brow audience, Waldrop's book is a gossipy narration of the brief history of that institute, the people behind it, and the wild ideas it has nurtured. It wisely focuses on the brilliant and eccentric minds behind the institute - and there is no shortage of them at SFI!
The cast is full of oddball luminaries, from the Nobel-prize winning physicist Murray Gell-Mann to the renegade evolutionary biologist Stuart Kauffman and the influential duo of heterodox economists, John Holland and W. Brian Arthur. The proverbial "camera and mic" are constantly pointed at one or more of the central characters. Helpfully, the chapters are structured around their life stories, ideas, and passions. The upside is that the reader gets an intimate journalistic account of their life stories. This makes the story flow smoothly and the book is quite a page turner. The downside of the journalistic narration is that the science is presented as a function of their passions and mostly taken as gospel. The author manages to explain the basic ideas of complexity science quite well but he lacks a certain amount of critical distance that belongs to popular science. While I am fully on board with complexity, this book makes it all sound a bit too evangelical.
As someone who is actively working on the science of complexity, this book is ridiculously useful. But most people are not working in this field, so what can they expect to get out of it? I think that for anyone who is interested in scientific breakthroughs it is a unique and wonderful document that lifts up the curtain to how the academic sausage is made. And it offers some psychological insights into the driving passions of ambitious scientists. On the other hand, the fact that it focuses mostly on the sociology and administration of running an academic institute undoubtedly makes it disappointing to many readers. And since it uncritically hypes up the underlying science and even commits occasional scientific errors and misunderstandings (especially in the realms of economics and evolutionary theory), it is only middling as a scientific introduction to the ideas of complexity. But overall it deserves high praise for the groove of its prose, the excitement of its tone, the importance of its subject matter, and its unique level of access to world class thinkers.
I hope that the book inspires people to see the importance of the work done at SFI. It is my fervent hope that developing better models of self-organization and complex adaptive systems can be used to develop a new language of a unified 21st century science. But this can only happen if people are able to connect strands of cutting edge research across disciplinary boundaries. This is why we need institutes like SFI - to cross those boundaries, to bridge those disciplines, and to remind people of their place in the cosmos as emergent phenomena between the quarks and the stars.
The cast is full of oddball luminaries, from the Nobel-prize winning physicist Murray Gell-Mann to the renegade evolutionary biologist Stuart Kauffman and the influential duo of heterodox economists, John Holland and W. Brian Arthur. The proverbial "camera and mic" are constantly pointed at one or more of the central characters. Helpfully, the chapters are structured around their life stories, ideas, and passions. The upside is that the reader gets an intimate journalistic account of their life stories. This makes the story flow smoothly and the book is quite a page turner. The downside of the journalistic narration is that the science is presented as a function of their passions and mostly taken as gospel. The author manages to explain the basic ideas of complexity science quite well but he lacks a certain amount of critical distance that belongs to popular science. While I am fully on board with complexity, this book makes it all sound a bit too evangelical.
As someone who is actively working on the science of complexity, this book is ridiculously useful. But most people are not working in this field, so what can they expect to get out of it? I think that for anyone who is interested in scientific breakthroughs it is a unique and wonderful document that lifts up the curtain to how the academic sausage is made. And it offers some psychological insights into the driving passions of ambitious scientists. On the other hand, the fact that it focuses mostly on the sociology and administration of running an academic institute undoubtedly makes it disappointing to many readers. And since it uncritically hypes up the underlying science and even commits occasional scientific errors and misunderstandings (especially in the realms of economics and evolutionary theory), it is only middling as a scientific introduction to the ideas of complexity. But overall it deserves high praise for the groove of its prose, the excitement of its tone, the importance of its subject matter, and its unique level of access to world class thinkers.
I hope that the book inspires people to see the importance of the work done at SFI. It is my fervent hope that developing better models of self-organization and complex adaptive systems can be used to develop a new language of a unified 21st century science. But this can only happen if people are able to connect strands of cutting edge research across disciplinary boundaries. This is why we need institutes like SFI - to cross those boundaries, to bridge those disciplines, and to remind people of their place in the cosmos as emergent phenomena between the quarks and the stars.
August 9, 2021
This book firggin’ ROCKS!
Its fun fun fun from cover to frickin’ cover.
It’s a group biography of the founders of complexity theory, and what eventually became the Santa Fe Institue.
If you’ve ever had a dream.
Or a cool idea.
And then had some tool take a poop on it.
And walked away feeling completely discouraged.
Then you will ONEHUNDREDPERCENT relate to the people in this book.
The BEST part about it is.
These guys and gals didn’t give up.
And they ended up coming together and inventing something totally new and exciting and important.
If this doesn’t sound hype as fuck.
Than I suck at reviews.
Because it TOTALLY is hype as fuck.
And you will just have to take my word for it.
The book covers a bunch of cool ideas including: increasing returns in economics, artificial life, infinite games, self organizing systems, autocatalytic sets, phase shifts and emergence.
All of these ideas are discussed via interlinking biography’s of the fascinating and gritty people who somehow found each other, after toiling in obscurity and isolation, and went on a journey together, from the margins of science and academia, to the center of an exciting new paradigm.
Author Mitchel Waldrop made this story ridiculously relatable, and he made these crazy interesting but kinda’ obscure ideas crack wide open.
This book is so good it will ruin the next one.
⭐️⭐️⭐️⭐️⭐️
Its fun fun fun from cover to frickin’ cover.
It’s a group biography of the founders of complexity theory, and what eventually became the Santa Fe Institue.
If you’ve ever had a dream.
Or a cool idea.
And then had some tool take a poop on it.
And walked away feeling completely discouraged.
Then you will ONEHUNDREDPERCENT relate to the people in this book.
The BEST part about it is.
These guys and gals didn’t give up.
And they ended up coming together and inventing something totally new and exciting and important.
If this doesn’t sound hype as fuck.
Than I suck at reviews.
Because it TOTALLY is hype as fuck.
And you will just have to take my word for it.
The book covers a bunch of cool ideas including: increasing returns in economics, artificial life, infinite games, self organizing systems, autocatalytic sets, phase shifts and emergence.
All of these ideas are discussed via interlinking biography’s of the fascinating and gritty people who somehow found each other, after toiling in obscurity and isolation, and went on a journey together, from the margins of science and academia, to the center of an exciting new paradigm.
Author Mitchel Waldrop made this story ridiculously relatable, and he made these crazy interesting but kinda’ obscure ideas crack wide open.
This book is so good it will ruin the next one.
⭐️⭐️⭐️⭐️⭐️
October 25, 2007
This book tells the story of the people, places and events involved in the creation of the science of complexity. The story is told well and I found it difficult to put down. This is the only book that, upon finishing it, I have decided to re-read immediately... note: I am a geek quite enamored with fractals, chaos, and all things complex.
June 27, 2008
Skims over the science in favor of messianic praise for the rogue theorists who began the Santa Fe institute.
Reads like an article from Sports Illustrated or Rolling Stone. Skimmed through the second half, and decided not to finish it.
Not much substance, but an interesting story if you are interested in the history behind the Santa Fe Institute.
Reads like an article from Sports Illustrated or Rolling Stone. Skimmed through the second half, and decided not to finish it.
Not much substance, but an interesting story if you are interested in the history behind the Santa Fe Institute.
August 10, 2023
I found this book a dangerously simplistic and naïve approach for understanding the actual world I live in.
If I had read this book in 1992, I would have thought it was brilliant, today it shows a bunch of smart people grasping at imaginary windmills while the world has ignored them and moved forward by synthesizing the web of science while not always striving for the perfect metaphor as the players in this book seemed to vainly strive for.
It’s so clear the featured players in this story were in search of solutions before the problem was understood, and their approaches were fun to think about while mostly only adding color without form, as Kant says “theory without experience is mere intellectual play,” and the players featured in this book are playing when they would have been bettered served experiencing before theorizing.
If I had read this book in 1992, I would have thought it was brilliant, today it shows a bunch of smart people grasping at imaginary windmills while the world has ignored them and moved forward by synthesizing the web of science while not always striving for the perfect metaphor as the players in this book seemed to vainly strive for.
It’s so clear the featured players in this story were in search of solutions before the problem was understood, and their approaches were fun to think about while mostly only adding color without form, as Kant says “theory without experience is mere intellectual play,” and the players featured in this book are playing when they would have been bettered served experiencing before theorizing.
May 7, 2021
What a wonderful read!! Heavily recommend it to anyone interested in chaotic dynamic systems.
As a computer scientist who has formal training in neural networks and language models, I was curious to stop a bit and investigate some of the foundations from a different perspective. This is not a technical book, but it does an amazing job at explaining not just the concept but the intuition behind complexity in a very straitforward and captivating way. I learned a lot even though I'm not exactly a lay person because the book explores so many different areas, and there were many connections I hadn't seen before. For example, it prompted me to learn more about agent-based models.
The book goes through topics in Complexity Theory as it narrates the inception of the field and its bleeding into other areas like economics through mini-biographies and tales of the founding of the Santa Fe research institute. Sometimes I thought this was overdone and a bit distracting and unnecessary. But it also added some personal tones that make it enjoyable. I wish the mini biographies interwoven in the text talked about more people than a bunch of white dudes but that didn't really tick me off. They are still quite interesting characters and felt like outcasts in some way? Everyone in this book sounds like they have ADHD, which is quite funny, or maybe that's just me projecting this everywhere recently. Either way, I found it amusing.
I really appreciated the discussion of the conflict between Complexity Theory and US economics. If there is a firm belief in free market and that full individual freedom would always bring the best results, that goes in direct confrontation with a scientific theory that says that it is just not possible to optmize for some ideal equilibrium and that the collection of individual choices will occasionally make non-optimal and catastrophic events emerge. The book was clear about the fact that there was an ideological problem in researching in this area, since the philosopher that really laid down a perspective to investigate systems in constant change that are very sensitive to initial conditions was Marx. Researchers in the US really wanted to stay away from praising him because, you know, all of the communist stuff. I really wish the book went into more detail about dialectical materialism and its connection with chaos theory. It didn't and I had to look for more writings about this outside of this book. I felt that in a way the book committed the same behavior it accused the reserachers of avoiding Marx because of political implications. It's almost as if the book wants us to believe that it is a mere coincidence that Marx wanted to analyse the world as a system in constant transformation and just happenend to be a communist. To me, those two things are very well connected. The very concept that the class in which one is born will be heavily defining in how much suffering a person will go through life is exactly the sensitivity to initial conditions of a chaotic system applied to social sciences. To me, the book failed by not going deeper in this connection.
The book could also have brought more reflections on autonomy. It mentioned autonomy through pointing out that the implications of accepting chaos theory is that we can let go of newtonian determinism and understand that each of all the little interactions we have could change everything. While I loved what was laid out, I wanted more. I wanted to see some critical theory and Paulo Freire in here. I wanted to see a better exploration of people as agents of their own world. It was the perfect moment to bring that in and go deeper in this connection as well, and then it just moved on.
I loved the insight of letting go of optmizing algorithms for specific parameters when problems are just not well defined, but I was already conviced of that before reading the book. The thing is that then it goes to discuss things like what are usually considered "pure" sciences, what is the value of understanding things that can't be predicted, and the concequences of all of this mess for policy making. The fact that everything is messy and prediction is hard doesn't mean that problems aren't workable under a complex systems perspective or that it would result in "second best" solutions. The innacuracy of reductionism is already not bringing us optimal solutions anyway.
The part that I found most interesting in this book, was the discussion of what constitutes life. From a complexity perspective, when something is perfectly stable, it is in fact dead. And then in goes to explore just how much chaos and how much order are the perfect conditions for the emergence of life. And what characteristics could be taken as thresholds for recognizing something as a living organism. As I was reading through, I got the vibe that some sections of the scientific community are slowly coming to the realization that the Earth is alive. Later, I got to the part of the book where they say exactly that but the way they say it sounds derogatory. As if scientists are very scared of sounding "new age" when exploring these thresholds of life. But honestly, I find this very silly, it's very old stuff, in fact. Indigenous groups have been telling us exactly this for hundreds of years already. Reading Ailton Krenak will give a great short insight on this topic. The book does mention eastern philosophy, and makes it look like some west x east thing, meanwhile there are communities in american soil shouting about this stuff to anyone who wants to hear but no one listens... Either way, what was going in the head of the scientistis when they decided to investigate what constitutes life? Did they really expect to investigate this in a completely secular way and not stumble into other cultures and theology at all? Or was it fear of pissing off the wrong people and not getting research funding?
Anyway, I loved the book. Even when it didn't explore what I wanted it to explore, it explored enough to instigate my curiosity and elicit many questions that I hadn't asked before.
As someone who was not sure about continuing my education into PhD not just because of mental health concerns but also because of lack of interest in specialization, it's very refreshing to learn about domains that work towards expansion and integration rather than reductionism. I honestly didn't know paths like this existed in academia? I have to admit I just didn't look for it. So maybe it's more common knowledge than I assumed. But yes, I really loved this idea of an unified science, which is almost medieval in a way, like an age of new polymaths.
5/5
As a computer scientist who has formal training in neural networks and language models, I was curious to stop a bit and investigate some of the foundations from a different perspective. This is not a technical book, but it does an amazing job at explaining not just the concept but the intuition behind complexity in a very straitforward and captivating way. I learned a lot even though I'm not exactly a lay person because the book explores so many different areas, and there were many connections I hadn't seen before. For example, it prompted me to learn more about agent-based models.
The book goes through topics in Complexity Theory as it narrates the inception of the field and its bleeding into other areas like economics through mini-biographies and tales of the founding of the Santa Fe research institute. Sometimes I thought this was overdone and a bit distracting and unnecessary. But it also added some personal tones that make it enjoyable. I wish the mini biographies interwoven in the text talked about more people than a bunch of white dudes but that didn't really tick me off. They are still quite interesting characters and felt like outcasts in some way? Everyone in this book sounds like they have ADHD, which is quite funny, or maybe that's just me projecting this everywhere recently. Either way, I found it amusing.
I really appreciated the discussion of the conflict between Complexity Theory and US economics. If there is a firm belief in free market and that full individual freedom would always bring the best results, that goes in direct confrontation with a scientific theory that says that it is just not possible to optmize for some ideal equilibrium and that the collection of individual choices will occasionally make non-optimal and catastrophic events emerge. The book was clear about the fact that there was an ideological problem in researching in this area, since the philosopher that really laid down a perspective to investigate systems in constant change that are very sensitive to initial conditions was Marx. Researchers in the US really wanted to stay away from praising him because, you know, all of the communist stuff. I really wish the book went into more detail about dialectical materialism and its connection with chaos theory. It didn't and I had to look for more writings about this outside of this book. I felt that in a way the book committed the same behavior it accused the reserachers of avoiding Marx because of political implications. It's almost as if the book wants us to believe that it is a mere coincidence that Marx wanted to analyse the world as a system in constant transformation and just happenend to be a communist. To me, those two things are very well connected. The very concept that the class in which one is born will be heavily defining in how much suffering a person will go through life is exactly the sensitivity to initial conditions of a chaotic system applied to social sciences. To me, the book failed by not going deeper in this connection.
The book could also have brought more reflections on autonomy. It mentioned autonomy through pointing out that the implications of accepting chaos theory is that we can let go of newtonian determinism and understand that each of all the little interactions we have could change everything. While I loved what was laid out, I wanted more. I wanted to see some critical theory and Paulo Freire in here. I wanted to see a better exploration of people as agents of their own world. It was the perfect moment to bring that in and go deeper in this connection as well, and then it just moved on.
I loved the insight of letting go of optmizing algorithms for specific parameters when problems are just not well defined, but I was already conviced of that before reading the book. The thing is that then it goes to discuss things like what are usually considered "pure" sciences, what is the value of understanding things that can't be predicted, and the concequences of all of this mess for policy making. The fact that everything is messy and prediction is hard doesn't mean that problems aren't workable under a complex systems perspective or that it would result in "second best" solutions. The innacuracy of reductionism is already not bringing us optimal solutions anyway.
The part that I found most interesting in this book, was the discussion of what constitutes life. From a complexity perspective, when something is perfectly stable, it is in fact dead. And then in goes to explore just how much chaos and how much order are the perfect conditions for the emergence of life. And what characteristics could be taken as thresholds for recognizing something as a living organism. As I was reading through, I got the vibe that some sections of the scientific community are slowly coming to the realization that the Earth is alive. Later, I got to the part of the book where they say exactly that but the way they say it sounds derogatory. As if scientists are very scared of sounding "new age" when exploring these thresholds of life. But honestly, I find this very silly, it's very old stuff, in fact. Indigenous groups have been telling us exactly this for hundreds of years already. Reading Ailton Krenak will give a great short insight on this topic. The book does mention eastern philosophy, and makes it look like some west x east thing, meanwhile there are communities in american soil shouting about this stuff to anyone who wants to hear but no one listens... Either way, what was going in the head of the scientistis when they decided to investigate what constitutes life? Did they really expect to investigate this in a completely secular way and not stumble into other cultures and theology at all? Or was it fear of pissing off the wrong people and not getting research funding?
Anyway, I loved the book. Even when it didn't explore what I wanted it to explore, it explored enough to instigate my curiosity and elicit many questions that I hadn't asked before.
As someone who was not sure about continuing my education into PhD not just because of mental health concerns but also because of lack of interest in specialization, it's very refreshing to learn about domains that work towards expansion and integration rather than reductionism. I honestly didn't know paths like this existed in academia? I have to admit I just didn't look for it. So maybe it's more common knowledge than I assumed. But yes, I really loved this idea of an unified science, which is almost medieval in a way, like an age of new polymaths.
5/5
June 1, 2015
One of those books that kicked a door open into a whole other realm of a science that I have been looking for my whole life. Emergence, Complex Adaptive Systems, Ecology, Chaos Theory, Simplicity, Neural Networks, Embryology, Cell growth, Evolution, Computer Programming, Immunology, Artificial Intelligence, Human Intelligence, Mathematics, Economies, Earthquakes, Power Laws, Statistics, Physics, Stocks, (and several other subjects I am leaving out due to not wanting to overdo the review) are touched upon with great insight. What is most striking about this book is how well it is told and the great clarity in which it unfolds. Scientists are painted as fully fleshed out human beings and the science is perfectly translated to be understandable to the layman. For me this book is a life changer in the sense that I plan on studying this interesting science very thoroughly. By page 256 I knew I had to order my own copy. I know that this will be a book that I will continue to go back to as a reference. I feel that it plays an important role as the cornerstone for the building and expansion of my mental library as well as my physical library on the supremely interesting subject of Complexity.
November 30, 2017
This is the story of the creation of the Santa Fe Institute and the personalities and thinking of the scientists who came together to explore disciplines that just might relate to their own. So we have mathematicians, physicists, biologists, computer programmers and analysts, chemists, astronomers, and many more giving workshops and lectures to one another to explore what lies between order and chaos. (A car key is simple. A car is complicated. A car in traffic is complex.) This book is about complexity.
Author Waldrop tells stories and explores the personalities of the men and women who made the Santa Fe Institute happen, thereby creating a tale that enlightens the reader on many intellectual levels. This book was written in 1992, but it is timeless.
Author Waldrop tells stories and explores the personalities of the men and women who made the Santa Fe Institute happen, thereby creating a tale that enlightens the reader on many intellectual levels. This book was written in 1992, but it is timeless.
October 2, 2022
Reading this book three decades after its publication is not as illuminating as its author planned. The work hailed as revolutionary appears inevitable as humanity began developing the use cases of exponentially growing computational abilities. In fact, the pioneers and their pioneering work were small first steps in the long journey to where data analytics and its impact on all sciences are a few short years ahead. This reviewer had a handful of other takeaways, even though none were intended in the story.
It is fashionable to assume, as oft-repeated in the book, that most giants of various fields of the previous eras truly believed in linear, polynomial equations comprehensively providing answers about whatever they were investigating. The doyens worked with pens and papers, log tables and limited precise information; they were simply providing some logic or structure they could, based on the capacities of the tools at their disposal. The celebrated scientists and philosophers were not as stupid as often made out to be because of the theories they championed that appear highly simplistic (or worse) in our era.
Until the arrival of digital computers, it was impossible to explore the fields of recursive, iterative, circular equations involving a small number of simple linear equations. Digital computers not only made it possible to do calculations using higher power polynomial equations but afforded the luxury of having equations feeding into each other and measuring their impact after thousands of iterations (of course, the abilities are far higher now).
Santa Fe pioneers - as described in the book - were one of the first to witness the results of some such interplays. Should they be credited as the first to come up with ideas like "markets do not have an equilibrium"? I feel the author goes too far in such assertions.
The other problem is the importance assigned to armchair work without theoretical rigor or genuine practical links. If there is a set of all mathematical equations, linear equations - a highly specific case - will be an infinitesimally small part. Any claims that almost all rule-based life equations are nonlinear are stating an obvious and not necessarily radical. And this has been true from time immemorial. Most thinkers of the past sought refuge in linearity out of necessity, as explained above, and not dumbness.
It is easy to comprehend how those who first harnessed the powers of early computers to play around with hypothetical recursive, iterative equations were surprised by what they ended up with over time. With modern computing power and visualization tools, a neophyte learns how a seemingly homogenous cloud could be converted into lumpy clusters with a tiny perturbation and simple recursive mathematical steps that favor clustering. The pioneers of the book were the first ones to generate some of it, but their work is not as radical as claimed despite big words like the title in the book. Similar simulations were going on at countless places in those years with the new-fangled machines. It is almost given that many others had obtained the same results in those years with their hypothetical equation sets. It would have been different if the academics discussed in the book had come up with some precise, universal laws before anyone else. That certain types of equation interplay can suddenly turn chaotic from orderly or vice versa is not novel enough now and was perhaps not even then.
The holy grail in any field - scientific, economic, or any other walk of life - is to find the equations that work (to explain alone would be a great enough start). Given that the book's heroes were not pursuing any pure mathematical concepts and coming out with generalized laws, their work needed applicability for validity. In the absence of these, it was certainly not an idle pursuit, but this reviewer would join the ranks of many baffled colleagues of the pioneers discussed in wondering what all the fuss is about. The author might have missed that such bafflement does not equate to disagreement with the conclusions.
All that said, the book is at its best when explaining the dominance of nonlinearity in dynamic systems we see all around.
It is fashionable to assume, as oft-repeated in the book, that most giants of various fields of the previous eras truly believed in linear, polynomial equations comprehensively providing answers about whatever they were investigating. The doyens worked with pens and papers, log tables and limited precise information; they were simply providing some logic or structure they could, based on the capacities of the tools at their disposal. The celebrated scientists and philosophers were not as stupid as often made out to be because of the theories they championed that appear highly simplistic (or worse) in our era.
Until the arrival of digital computers, it was impossible to explore the fields of recursive, iterative, circular equations involving a small number of simple linear equations. Digital computers not only made it possible to do calculations using higher power polynomial equations but afforded the luxury of having equations feeding into each other and measuring their impact after thousands of iterations (of course, the abilities are far higher now).
Santa Fe pioneers - as described in the book - were one of the first to witness the results of some such interplays. Should they be credited as the first to come up with ideas like "markets do not have an equilibrium"? I feel the author goes too far in such assertions.
The other problem is the importance assigned to armchair work without theoretical rigor or genuine practical links. If there is a set of all mathematical equations, linear equations - a highly specific case - will be an infinitesimally small part. Any claims that almost all rule-based life equations are nonlinear are stating an obvious and not necessarily radical. And this has been true from time immemorial. Most thinkers of the past sought refuge in linearity out of necessity, as explained above, and not dumbness.
It is easy to comprehend how those who first harnessed the powers of early computers to play around with hypothetical recursive, iterative equations were surprised by what they ended up with over time. With modern computing power and visualization tools, a neophyte learns how a seemingly homogenous cloud could be converted into lumpy clusters with a tiny perturbation and simple recursive mathematical steps that favor clustering. The pioneers of the book were the first ones to generate some of it, but their work is not as radical as claimed despite big words like the title in the book. Similar simulations were going on at countless places in those years with the new-fangled machines. It is almost given that many others had obtained the same results in those years with their hypothetical equation sets. It would have been different if the academics discussed in the book had come up with some precise, universal laws before anyone else. That certain types of equation interplay can suddenly turn chaotic from orderly or vice versa is not novel enough now and was perhaps not even then.
The holy grail in any field - scientific, economic, or any other walk of life - is to find the equations that work (to explain alone would be a great enough start). Given that the book's heroes were not pursuing any pure mathematical concepts and coming out with generalized laws, their work needed applicability for validity. In the absence of these, it was certainly not an idle pursuit, but this reviewer would join the ranks of many baffled colleagues of the pioneers discussed in wondering what all the fuss is about. The author might have missed that such bafflement does not equate to disagreement with the conclusions.
All that said, the book is at its best when explaining the dominance of nonlinearity in dynamic systems we see all around.
February 4, 2019
A soft 4 stars, maybe 3.75 stars. Against my hopes, this book was much more storytelling than actual theory. So I skimmed a fair chunk. But Waldrop does do a fine job of putting the reader into the midst of exciting breakthroughs and intense brainstorming sessions. The scholastic culture portrayed in the book is so attractive, I toyed with going to an SFI workshop (it costs a few grand nowadays to attend). I loved the way these scientists from various fields (economics, physics, CS) exchanged ideas and battled.
The book gives a pretty good intro treatment of the various theories going at SFI in the 60's-80's. The concept of cellular automata representing a "phase transition" from order to chaos was new to me, as was the whole business with autocatalytic polymers. Maybe too much ink was spilled over Brian Arthur's economic theories, which honestly still seem kinda crackpot nowadays. I'm very skeptical of how much you can learn from an ABM economy simulation without knowing what you're looking for first. But this is a book that revels in the unorthodox, so it's fitting.
The book gives a pretty good intro treatment of the various theories going at SFI in the 60's-80's. The concept of cellular automata representing a "phase transition" from order to chaos was new to me, as was the whole business with autocatalytic polymers. Maybe too much ink was spilled over Brian Arthur's economic theories, which honestly still seem kinda crackpot nowadays. I'm very skeptical of how much you can learn from an ABM economy simulation without knowing what you're looking for first. But this is a book that revels in the unorthodox, so it's fitting.
March 7, 2018
The title is somewhat misleading. I read this eons ago, but as I pack up things to give away, I may as well review those I remember or scribbled in. My reaction to pulling this one out of the box was "ugh, why didn't I give this away long ago?" What was supposed to be a general science introduction to the science of complexity is, in fact, the story of the people -- scientists and mathematicians -- who started the Sante Fe Institute. There was little science in this book. So if looking for information and education regarding complexity theory, then this is the wrong book. If you want a shiny (think People Magazine) gloss of some science stars, then you've got the book! Despite the year this was published, there were decent general audience books on chaos theory. At the time Mitchell, Strogatz and Scott Page had books out. Of course there are many these days. In fact, in wondering why I bought this one, I think I was seduced by Melanie Mitchell's blurb. I was sorely disappointed.
December 26, 2019
This book is brilliant. It braids together stories of multiple scientists, illuminating their respective areas of research one by one, into a tale of an unusual institute of Santa Fe. Despite the main topic, complexity theory, being not the simplest thing around, the author introduces it bit by bit, never boring you with too many technicalities but also never delving into too much of historical details about the particular figures.
Although it is a bit dated by now (which makes it even more of a history book as opposed to popular science one), this book is still very thought-provoking. Going to the meta-level of synergy between disciplines as different as economics and physics is just... the best kind of tingly in the brain. I believe every person who reads this book will see parallels and patterns in their own field(s) of expertise.
Although it is a bit dated by now (which makes it even more of a history book as opposed to popular science one), this book is still very thought-provoking. Going to the meta-level of synergy between disciplines as different as economics and physics is just... the best kind of tingly in the brain. I believe every person who reads this book will see parallels and patterns in their own field(s) of expertise.
April 25, 2008
I've shelved this under philosophy. May move it to a new bookshelf on complexity and emergence. It's a popular book, breezily written, made economics sexy to me, and helped me get a focus on my emerging attraction to complexity theory. It is mightily recommended.
November 10, 2020
Be warned: This book is more about the history of the Sante Fe Institute than actual principles of complexity science.
Still entertaining but not as enlightening as I had hoped.
Still entertaining but not as enlightening as I had hoped.
September 4, 2020
Absolutely wonderful! Reading this made me happy! A narrative-driven overview of both science but also the relevant people's lives in the making of Santa Fe's complexity science institute - and a whole new scientific field. Warmly recommend to anyone who feels like being inspired by some very driven people <3
September 8, 2020
Less a book about complexity and more about the men who developed the science in the 1960s-1980s. This is fine, if you're interested in that, and the book does give you somewhat of a taste of academic life--papers being rejected, having to apply for funding, the balance between research and administration. But as a working post-doc scientist myself it was hard not to notice that the author heavily romanticizes his subject themselves, evidentally unaware of the insane amount of privilege these researcher had in terms of being able to afford extensive education, being able to afford to dither constantly and change their minds therein, being able to afford to sit around having grand-if-nebulous ideas while grad students do their computer programming for them, one of them even being able to afford to not finish his PhD during three years of post-doc work before finally being held accountable for the validity and applicability of his grand ideas by a thesis committee. The author treats them simply as special, brilliant people, too important to care if their wives don't want them to be up at all hours of the night programming, or to make due with the less-than-the-best astronomy program they think they deserve and need. Certainly the book deals with intelligent men who made notable contributions to an emerging field, but seems ironically unaware of the complex forces--beyond the idealized drive to understand an idea--that brought these men to the top of their field. Malcom Gladwell's book Outliers deals with this well. This book makes professional science look like a free, grand adventure for irascible dreamers in love with great ideas, who occasionally have to apply for funds or have their work criticized by others, and maybe that's what it was for these men, but that's not what it's like for most people. If there were any women or minorities with similar grand ideas working at the same time as these men, it certainly wasn't like that for them. Instead, the book provides a rosy picture of what doing science is like with a very important caveat (When You Are A White Man In The 1960s Who Has Money And Respect) complely ignored. So, unfortunately, it doesn't tell the reader much about complexity science *or* about scientific life.
May 5, 2019
I had to drop this book. It started out fine as a good story of how the Santa Fe Institute was founded and the initial players in this saga. Then, as more actors are being introduced, the book just becomes more and more monotonous. It’s all about this incredibly geeky scientists with megalomaniac ambitions to “understand the whole universe”, to unveil the secrets of the mind, the brain and life itself with their incredibly reductionistic theories. It is an old book already, so 90’s! and it shows it’s age in its style and in the ideas is trying to portray. At this point I’m not to sure if the “science” of complexity has really gotten anywhere, or if chaos theory came to have any further relevance in the new Millenium. But It doesn’t really matter, at least not to me.
August 7, 2022
I gave it five stars, which is almost unheard of for a book written in the journalistic style, because there was so much fascinating material on complexity theory and self-organizing systems. But I'd have liked it a lot better with less inside baseball about the Santa Fe Institute, and without the interesting material about complexity embedded in biographical vignettes. I could have handled the stories better if they'd just stuck to intellectual biography, without all the stuff about Langton's hang gliding accident and the like. I also wish journalists would footnote things instead of putting "bibliographic essays" at the end of the book.
November 20, 2008
This book is what introduced me to the concepts of emergence and complexity theory. It's easy to read, and follows various scientists from disparate disciplines as they discover and investigate this oddly pervasive concept of complexity. Emergence and complexity theory have changed the way I look at the world, and this book sparked my interest to learn more. If you are curious about complexity theory, this book is a nice introduction.
August 20, 2012
I read this many years ago when Chaos thoery was all the rage. The book came out in 1992, I probably read this in 1997. This lays out the case for Complexity and introduces the main players at teh Santa Fe Institute. I found this utterly fascinating.
October 25, 2022
This is a book that needed to be written precisely when it was. Otherwise this is an area of science that could have easily slipped undocumented and mostly forgotten into the annals of history.
Unlike some of the more popular books on systems thinking, which mainly covers deterministic views of systems dynamics, Waldrop traces the entire history of the domain of complexity, growing on the back of chaos theory and driven by the birth of the Sante Fe Institute.
At first, I was sceptical. The writing style is blueprint journalist, relying heavily on quoted interviews and focusing more on the people than the knowledge itself. This is usually a recipe for disaster: an underqualified and uneducated journalist taking on a domain far beyond their understanding; but, very quickly, Waldrop proved me wrong. Over the period of the book, he not only interviewed, told the story of, and explored the lives and motivations of all the most influential scholars in complexity theory, but also demonstrated how, within the chaos of these scholars' lives, complex systems theory emerged.
Waldrop is also no ignoramus. He has a PhD in particle physics and clearly understood the foundations of complexity well. Yet, while he could have told only the stories of the physicists of the early Sante Fe Institute, he instead focused on the central figures of complexity science: Brian Arthur (economist), George Cowan (chemist), Philip Anderson (Physicist), Stuart Kauffman (Biologist), Murray Gell-Mann (physicist), John Holland (computer scientist), Chris Langton (computer scientist), and Doyne Farmer (complexity researcher). And, these are stories that needed to be told. Holland, Gell-Mann, Cowan, Anderson, and Pines have all passed away since this book was written. Brian Arthur is also in his late 70s and Stuart Kaufman is in his 80s.
The story unfolds to discuss Arthur's work on increasing returns and how it relates to self-reinforcing feedback loops in dynamical systems, then shifts to talk about Kaufmann's auto-catalytic set theory and his work on the Red-Queen Effect in evolution; Holland's genetic algorithms and learning classifier systems; Robert Axelrod's Tit for Tat theory in Prisoner's Dilemma games; Arthur's later work on complexity economics; Langton's artificial life and natural selection, and "Edge of Chaos" phase transition theory, built on Wolfram's CA; Kaufmann's and Farmer's theories on the "Second Law" and coevolutionary systems; Craig Reynolds’ "Boids"; and finally Per Bak's self-organised criticality, comparing it to Langton's Edge of Chaos. As each theory smoothly collides, you get to the end of the book and suddenly realise that Waldrop has somehow mapped out the entire domain of complexity science!
It's now 2022 and the domain of complex systems theory is a mere shadow of what it once was. Although genetic algorithms are foundational in optimisation theory, their basis in complexity are long forgotten. ABMs, built on Holland's Complex Adaptive Systems theory, are now the new hottest modelling method, finally overtaking equational systems dynamics modelling and discrete event systems models; yet they're essentially siloed to operations research, and the methodology itself is a mess in terms of rigour and quality. Meanwhile, complexity theory has become "old news", and its potential for revealing the hidden emergent properties of the universe is being pushed aside for publication politics.
Still, the world still needs these stories. We need to remember who these scholars are or were, and what they contributed. We need a new generation of scholars who are driven by the potential to take today's computing power and to apply it to complexity to demonstrate how non-linear dynamics still have a very real potential in modern science. To get that, we need people who are excited by the idea of complexity! This book helps to keep that excitement alive, and I feel very fortunate to have read it!
Unlike some of the more popular books on systems thinking, which mainly covers deterministic views of systems dynamics, Waldrop traces the entire history of the domain of complexity, growing on the back of chaos theory and driven by the birth of the Sante Fe Institute.
At first, I was sceptical. The writing style is blueprint journalist, relying heavily on quoted interviews and focusing more on the people than the knowledge itself. This is usually a recipe for disaster: an underqualified and uneducated journalist taking on a domain far beyond their understanding; but, very quickly, Waldrop proved me wrong. Over the period of the book, he not only interviewed, told the story of, and explored the lives and motivations of all the most influential scholars in complexity theory, but also demonstrated how, within the chaos of these scholars' lives, complex systems theory emerged.
Waldrop is also no ignoramus. He has a PhD in particle physics and clearly understood the foundations of complexity well. Yet, while he could have told only the stories of the physicists of the early Sante Fe Institute, he instead focused on the central figures of complexity science: Brian Arthur (economist), George Cowan (chemist), Philip Anderson (Physicist), Stuart Kauffman (Biologist), Murray Gell-Mann (physicist), John Holland (computer scientist), Chris Langton (computer scientist), and Doyne Farmer (complexity researcher). And, these are stories that needed to be told. Holland, Gell-Mann, Cowan, Anderson, and Pines have all passed away since this book was written. Brian Arthur is also in his late 70s and Stuart Kaufman is in his 80s.
The story unfolds to discuss Arthur's work on increasing returns and how it relates to self-reinforcing feedback loops in dynamical systems, then shifts to talk about Kaufmann's auto-catalytic set theory and his work on the Red-Queen Effect in evolution; Holland's genetic algorithms and learning classifier systems; Robert Axelrod's Tit for Tat theory in Prisoner's Dilemma games; Arthur's later work on complexity economics; Langton's artificial life and natural selection, and "Edge of Chaos" phase transition theory, built on Wolfram's CA; Kaufmann's and Farmer's theories on the "Second Law" and coevolutionary systems; Craig Reynolds’ "Boids"; and finally Per Bak's self-organised criticality, comparing it to Langton's Edge of Chaos. As each theory smoothly collides, you get to the end of the book and suddenly realise that Waldrop has somehow mapped out the entire domain of complexity science!
It's now 2022 and the domain of complex systems theory is a mere shadow of what it once was. Although genetic algorithms are foundational in optimisation theory, their basis in complexity are long forgotten. ABMs, built on Holland's Complex Adaptive Systems theory, are now the new hottest modelling method, finally overtaking equational systems dynamics modelling and discrete event systems models; yet they're essentially siloed to operations research, and the methodology itself is a mess in terms of rigour and quality. Meanwhile, complexity theory has become "old news", and its potential for revealing the hidden emergent properties of the universe is being pushed aside for publication politics.
Still, the world still needs these stories. We need to remember who these scholars are or were, and what they contributed. We need a new generation of scholars who are driven by the potential to take today's computing power and to apply it to complexity to demonstrate how non-linear dynamics still have a very real potential in modern science. To get that, we need people who are excited by the idea of complexity! This book helps to keep that excitement alive, and I feel very fortunate to have read it!
September 13, 2020
Complexity is a great combination of storytelling and science. It offers an overview of some of the key elements of complexity science, as well as the story of how the Santa Fe Institute came to be.
While the narrative can drag on at times, the passion and excitement from the people that cobbled the institute together is palpable, and added some entrepreneurial energy to the book.
A strength of this book is how it builds up the science over time: a description of one scientist's work followed by how someone else came across it at a workshop and then how they built on it to explain one more element of complexity. Rather than just explaining complexity head on, it brings you through the whole process of discovery, which allows you to see the connections and how different facets build upon each other. It felt like a much deeper exploration.
While the narrative can drag on at times, the passion and excitement from the people that cobbled the institute together is palpable, and added some entrepreneurial energy to the book.
A strength of this book is how it builds up the science over time: a description of one scientist's work followed by how someone else came across it at a workshop and then how they built on it to explain one more element of complexity. Rather than just explaining complexity head on, it brings you through the whole process of discovery, which allows you to see the connections and how different facets build upon each other. It felt like a much deeper exploration.
April 7, 2020
I read this book mostly to see how a group of scientists could manage to bootstrap something completely novel, or even alien, to the mainstream community. Our era for science has been very different from the old science world. In the old times, aristocrats are scientists, while in our times, science is mostly supported by application induced benefits form corporations and the government. It is not very clear to me how basic research is done in this system. This book gives a fair good description of the process.
One scientific aspects that might be overlooked by most people is that the development of the ideas says a lot about the idea than the technical monograph. The current reviewing process forces the authors to conceal the development and the limitation of ideas. Such processes are revealed somehow in such biography, or stories.
The book also show show Sante Fe Institute works, which is not obvious by reading their website.
One scientific aspects that might be overlooked by most people is that the development of the ideas says a lot about the idea than the technical monograph. The current reviewing process forces the authors to conceal the development and the limitation of ideas. Such processes are revealed somehow in such biography, or stories.
The book also show show Sante Fe Institute works, which is not obvious by reading their website.
February 10, 2020
For me this is a creative way to make science more interesting: by writing the story about the scientists and their endeavors to define a new kind of science, disrupting the status quo while they're at it. I got into this book interested in the issue of economic complexities (e.g. stock market crash) and was deeply engrossed reading about all the same analogies in all branches of science. From its sister branches in social sciences, its cousins in natural sciences, even in the (relatively) fledgling computer science. It appears that all of the phenomenons in life, when stripped to the bare, share the same philosophical essence. It never ceases to amaze me what the great minds in science could come up with. How the hell did they think of that? You could also get insights into the intricacies of academic life.
Want to read
April 24, 2012I really could not continue this book further, or know if I will ever return to it. Like 'Chaos', it is more interested in telling the story of the people who worked for Complexity Theory rather than make any useful description of what that theory actually entails. Perhaps my next attempt, if it should occur, would soften such a stance, but I would have to discern a great amount of improvement in substance to feel satisfied.
August 16, 2009
A wonderful book that describes the founding of the Santa Fe Institute and the origins of complexity science. After reading it, my response was, "this is what I want to do."
February 19, 2013
this was my first introduction to Complexity Theory. good general overview but probably outdated by now. i read it in college....
September 19, 2023
One of my new absolute favorites.
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