I’m giving a short 30-minute talk at a workshop on Biological and Bio-Inspired Information Theory at the Banff International Research Institute. I’ll say more about the workshop later, but here’s my talk: * Biodiversity, entropy and thermodynamics. Most of the people at this workshop study neurobiology and cell signalling, not evolutionary game theory or…
I’m having a great time at a workshop on Biological and Bio-Inspired Information Theory in Banff, Canada. You can see videos of the talks online. There have been lots of good talks so far, but this one really blew my mind: * Naftali Tishby, Sensing and acting under information constraints—a principled approach to biology and…
John Harte is an ecologist who uses maximum entropy methods to predict the distribution, abundance and energy usage of species. Marc Harper uses information theory in bioinformatics and evolutionary game theory. Harper, Harte and I are organizing a workshop on entropy and information in biological systems, and I’m really excited about it!
John Harte, Marc Harper and I are running a workshop! Now you can apply here to attend: * Information and entropy in biological systems, National Institute for Mathematical and Biological Synthesis, Knoxville Tennesee, Wednesday-Friday, 8-10 April 2015. Click the link, read the stuff and scroll down to “CLICK HERE” to apply.
There will be a 5-day workshop on Biological and Bio-Inspired Information Theory at BIRS from Sunday the 26th to Friday the 31st of October, 2014. It’s being organized by * Toby Berger (University of Virginia) * Andrew Eckford (York University) * Peter Thomas (Case Western Reserve University) BIRS is the Banff International Research Station,…
How does it feel to (co-)write a book and hold the finished product in your hands? About like this: Many, many thanks to my excellent co-authors, Tadashi Nakano and Tokuko Haraguchi, for their hard work; thanks to Cambridge for accepting this project and managing it well; and thanks to Satoshi Hiyama for writing a nice blurb.
You may have seen our PLOS ONE paper about tabletop molecular communication, which received loads of media coverage. One of the goals of this paper was to show that anyone can do experiments in molecular communication, without any wet labs or expensive apparatus.
[My comments posted to the original Facebook post follow below.]
I’m coming to this post a bit late as I’m playing a bit of catch up, but agree with it wholeheartedly.
In particular, applications to molecular biology and medicine are really beginning to come to a heavy boil in just the past five years. This particular year is the progenitor of what appears to be the biggest renaissance for the application of information theory to the area of biology since Hubert Yockey, Henry Quastler, and Robert L. Platzman’s “Symposium on Information Theory in Biology at Gatlinburg, Tennessee” in 1956.
Upcoming/recent conferences/workshops on information theory in biology include:
I’ll note in passing, for those interested, that Claude Shannon’s infamous master’s thesis at MIT (in which he applied Boolean Algebra to electric circuits allowing the digital revolution to occur) and his subsequent “The Theory of Mathematical Communication” were so revolutionary, nearly everyone forgets his MIT Ph.D. Thesis “An Algebra for Theoretical Genetics” which presaged the areas of cybernetics and the current applications of information theory to microbiology and are probably as seminal as Sir R.A Fisher’s applications of statistics to science in general and biology in particular.
For those commenting on the post who were interested in a layman’s introduction to information theory, I recommend John Robinson Pierce’s An Introduction to Information Theory: Symbols, Signals and Noise (Dover has a very inexpensive edition.) After this, one should take a look at Claude Shannon’s original paper. (The MIT Press printing includes some excellent overview by Warren Weaver along with the paper itself.) The mathematics in the paper really aren’t too technical, and most of it should be comprehensible by most advanced high school students.
For those that don’t understand the concept of entropy, I HIGHLY recommend Arieh Ben-Naim’s book Entropy Demystified The Second Law Reduced to Plain Common Sense with Seven Simulated Games. He really does tear the concept down into its most basic form in a way I haven’t seen others come remotely close to and which even my mother can comprehend (with no mathematics at all). (I recommend this presentation to even those with Ph.D.’s in physics because it is so truly fundamental.)
For the more advanced mathematicians, physicists, and engineers Arieh Ben-Naim does a truly spectacular job of extending ET Jaynes’ work on information theory and statistical mechanics and comes up with a more coherent mathematical theory to conjoin the entropy of physics/statistical mechanics with that of Shannon’s information theory in A Farewell to Entropy: Statistical Thermodynamics Based on Information.
In recent years, ideas such as “life is information processing” or “information holds the key to understanding life” have become more common. However, how can information, or more formally Information Theory, increase our understanding of life, or life-like systems?
Information Theory not only has a profound mathematical basis, but also typically provides an intuitive understanding of processes, such as learning, behavior and evolution terms of information processing.
In this special issue, we are interested in both:
the information-theoretic formalization and quantification of different aspects of life, such as driving forces of learning and behavior generation, information flows between neurons, swarm members and social agents, and information theoretic aspects of evolution and adaptation, and
the simulation and creation of life-like systems with previously identified principles and incentives.
Topics with relation to artificial and natural systems:
information theoretic intrinsic motivations
information theoretic quantification of behavior
information theoretic guidance of artificial evolution
information theoretic guidance of self-organization
information theoretic driving forces behind learning
information theoretic driving forces behind behavior
information theory in swarms
information theory in social behavior
information theory in evolution
information theory in the brain
information theory in system-environment distinction
information theory in the perception action loop
information theoretic definitions of life
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed Open Access monthly journal published by MDPI.
Deadline for manuscript submissions: 28 February 2015
Special Issue Editors
Guest Editor Dr. Christoph Salge
Adaptive Systems Research Group,University of Hertfordshire, College Lane, AL10 9AB Hatfield, UK
Phone: +44 1707 28 4490 Interests: Intrinsic Motivation (Empowerment); Self-Organization; Guided Self-Organization; Information-Theoretic Incentives for Social Interaction; Information-Theoretic Incentives for Swarms; Information Theory and Computer Game AI
Guest Editor Dr. Georg Martius
Cognition and Neurosciences, Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig, Germany
Phone: +49 341 9959 545 Interests: Autonomous Robots; Self-Organization; Guided Self-Organization; Information Theory; Dynamical Systems; Machine Learning; Neuroscience of Learning; Optimal Control
Guest Editor Dr. Keyan Ghazi-Zahedi
Information Theory of Cognitive Systems, Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig, Germany
Phone: +49 341 9959 535 Interests: Embodied Artificial Intelligence; Information Theory of the Sensorimotor Loop; Dynamical Systems; Cybernetics; Self-organisation; Synaptic plasticity; Evolutionary Robotics
Guest Editor Dr. Daniel Polani
Department of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK
E-Mail: firstname.lastname@example.org Interests: artificial intelligence; artificial life; information theory for intelligent information processing; sensor Evolution; collective and multiagent systems
Click the link, read the stuff and scroll down to “CLICK HERE” to apply. The deadline is 12 November 2014.
Financial support for travel, meals, and lodging is available for workshop attendees who need it. We will choose among the applicants and invite 10-15 of them.
Information theory and entropy methods are becoming powerful tools in biology, from the level of individual cells, to whole ecosystems, to experimental design, model-building, and the measurement of biodiversity. The aim of this investigative workshop is to synthesize different ways of applying these concepts to help systematize and unify work in biological systems. Early attempts at “grand syntheses” often misfired, but applications of information theory and entropy to specific highly focused topics in biology have been increasingly successful. In ecology, entropy maximization methods have proven successful in predicting the distribution and abundance of species. Entropy is also widely used as a measure of biodiversity. Work on the role of information in game theory has shed new light on evolution. As a population evolves, it can be seen as gaining information about its environment. The principle of maximum entropy production has emerged as a fascinating yet controversial approach to predicting the behavior of biological systems, from individual organisms to whole ecosystems. This investigative workshop will bring together top researchers from these diverse fields to share insights and methods and address some long-standing conceptual problems.
So, here are the goals of our workshop:
To study the validity of the principle of Maximum Entropy Production (MEP), which states that biological systems – and indeed all open, non-equilibrium systems – act to produce entropy at the maximum rate.
To familiarize all the participants with applications to ecology of the MaxEnt method: choosing the probabilistic hypothesis with the highest entropy subject to the constraints of our data. We will compare MaxEnt with competing approaches and examine whether MaxEnt provides a sufficient justification for the principle of MEP.
To clarify relations between known characterizations of entropy, the use of entropy as a measure of biodiversity, and the use of MaxEnt methods in ecology.
To develop the concept of evolutionary games as “learning” processes in which information is gained over time.
To study the interplay between information theory and the thermodynamics of individual cells and organelles.
Artificial Life aims to understand the basic and generic principles of life, and demonstrate this understanding by producing life-like systems based on those principles. In recent years, with the advent of the information age, and the widespread acceptance of information technology, our view of life has changed. Ideas such as “life is information processing” or “information holds the key to understanding life” have become more common. But what can information, or more formally Information Theory, offer to Artificial Life?
One relevant area is the motivation of behaviour for artificial agents, both virtual and real. Instead of learning to perform a specific task, informational measures can be used to define concepts such as boredom, empowerment or the ability to predict one’s own future. Intrinsic motivations derived from these concepts allow us to generate behaviour, ideally from an embodied and enactive perspective, which are based on basic but generic principles. The key questions here are: “What are the important intrinsic motivations a living agent has, and what behaviour can be produced by them?”
Related to an agent’s behaviour is also the question on how and where the necessary computation to realise this behaviour is performed. Can information be used to quantify the morphological computation of an embodied agent and to what degree are the computational limitations of an agent influencing its behaviour?
Another area of interest is the guidance of artificial evolution or adaptation. Assuming it is true that an agent wants to optimise its information processing, possibly obtain as much relevant information as possible for the cheapest computational cost, then what behaviour would naturally follow from that? Can the development of social interaction or collective phenomena be motivated by an informational gradient? Furthermore, evolution itself can be seen as a process in which an agent population obtains information from the environment, which begs the question of how this can be quantified, and how systems would adapt to maximise this information?
The common theme in those different scenarios is the identification and quantification of driving forces behind evolution, learning, behaviour and other crucial processes of life, in the hope that the implementation or optimisation of these measurements will allow us to construct life-like systems.
According to their release, the open access journal Entropywill sponsor the workshop by an open call with a special issue on the topic of the workshop. More details will be announced to emails received via email@example.com and over the alife and connectionists mailing lists.
From the publisher’s website, they provide the following synopsis:
This book discusses information theory as a means of extracting data from large amounts of biological sequences. Utilizing the Shannon theory, the book explains using the information theory principles to interpret sequences and extract vital information. It provides a detailed overview of the practical applications in bioinformatics and includes coverage of diversity in nucleotide and amino acid sequences, sing-nucleotide polymorphism (SNP) and indel sites, binding sites in promoter regions, splicing sites, and more.
If I can manage to get an early copy, I’ll provide a review shortly.
This year is the progenitor of what appears to be the biggest renaissance for the application of information theory to the area of biology since Hubert Yockey, Henry Quastler, and Robert L. Platzman’s “Symposium on Information Theory in Biology at Gatlinburg, Tennessee” in 1956. (I might argue it’s possibly even bigger than Claude Shannon’s Ph.D. thesis.) It certainly portends to create a movement that will rapidly build upon and far surpass Norbert Weiner’s concept of Cybernetics and Ludwig von Bertalanffy’s concept of General Systems Theory.
The BIRS workshop will be a bit more general in its approach while the NIMBioS workshop has a slightly tighter view specifically on maximum entropy as applied to biology.
Even more telling (and perhaps most promising) about the two workshops is the very heavy mathematical bent both intend to make their focus. I have a theory that the bounds of science are held below the high water level of mathematics (aka are “bounded by” in mathematics-speak), so there is nothing more exciting than to see groups attempting to push the mathematics and its application further. It was both the lack of mathematical rigor and the general youth of biology (and specifically genetics and microbiology) in the 1950’s which heavily hampered the early growth of cybernetics as a movement. Fortunately this is no longer the case on either count. Now we just need more researchers who are more readily conversant in the two realms simultaneously.
Complexity: A Guided Tour
Oxford University Press
May 28, 2009
This book provides an intimate, highly readable tour of the sciences of complexity, which seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. The author, a leading complex systems scientist, describes the history of ideas, current research, and future prospects in this vital scientific effort.
This is handily one of the best, most interesting, and (to me at least) the most useful popularly written science books I’ve yet to come across. Most popular science books usually bore me to tears and end up being only pedantic for their historical backgrounds, but this one is very succinct with some interesting viewpoints (some of which I agree with and some of which my intuition says are terribly wrong) on the overall structure presented.
For those interested in a general and easily readable high-level overview of some of the areas of research I’ve been interested in (information theory, thermodynamics, entropy, microbiology, evolution, genetics, along with computation, dynamics, chaos, complexity, genetic algorithms, cellular automata, etc.) for the past two decades, this is really a lovely and thought-provoking book.
At the start I was disappointed that there were almost no equations in the book to speak of – and perhaps this is why I had purchased it when it came out and it’s subsequently been sitting on my shelf for so long. The other factor that prevented me from reading it was the depth and breadth of other more technical material I’ve read which covers the majority of topics in the book. I ultimately found myself not minding so much that there weren’t any/many supporting equations aside from a few hidden in the notes at the end of the text in most part because Dr. Mitchell does a fantastic job of pointing out some great subtleties within the various subjects which comprise the broader concept of complexity which one generally would take several years to come to on one’s own and at far greater expense of their time. Here she provides a much stronger picture of the overall subjects covered and this far outweighed the lack of specificity. I honestly wished I had read the book when it was released and it may have helped me to me more specific in my own research. Fortunately she does bring up several areas I will need to delve more deeply into and raised several questions which will significantly inform my future work.
In general, I wish there were more references I hadn’t read or been aware of yet, but towards the end there were a handful of topics relating to fractals, chaos, computer science, and cellular automata which I have been either ignorant of or which are further down my reading lists and may need to move closer to the top. I look forward to delving into many of these shortly. As a simple example, I’ve seen Zipf’s law separately from the perspectives of information theory, linguistics, and even evolution, but this is the first time I’ve seen it related to power laws and fractals.
I definitely appreciated the fact that Dr. Mitchell took the time to point out her own personal feelings on several topics and more so that she explicitly pointed them out as her own gut instincts instead of mentioning them passingly as if they were provable science which is what far too many other authors would have likely done. There are many viewpoints she takes which I certainly don’t agree with, but I suspect that it’s because I’m coming at things from the viewpoint of an electrical engineer with a stronger background in information theory and microbiology while hers is closer to that of computer science. She does mention that her undergraduate background was in mathematics, but I’m curious what areas she specifically studied to have a better understanding of her specific viewpoints.
Her final chapter looking at some of the pros and cons of the topic(s) was very welcome, particularly in light of previous philosophic attempts like cybernetics and general systems theory which I (also) think failed because of their lack of specificity. These caveats certainly help to place the scientific philosophy of complexity into a much larger context. I will generally heartily agree with her viewpoint (and that of others) that there needs to be a more rigorous mathematical theory underpinning the overall effort. I’m sure we’re all wondering “Where is our Newton?” or to use her clever aphorism that we’re “waiting for Carnot.” (Sounds like it should be a Tom Stoppard play title, doesn’t it?)
I might question her brief inclusion of her own Ph.D. thesis work in the text, but it did actually provide a nice specific and self-contained example within the broader context and also helped to tie several of the chapters together.
My one slight criticism of the work would be the lack of better footnoting within the text. Though many feel that footnote numbers within the text or inclusion at the bottom of the pages detracts from the “flow” of the work, I found myself wishing that she had done so here, particularly as I’m one of the few who actually cares about the footnotes and wants to know the specific references as I read. I hope that Oxford eventually publishes an e-book version that includes cross-linked footnotes in the future for the benefit of others.
I can heartily recommend this book to any fan of science, but I would specifically recommend it to any undergraduate science or engineering major who is unsure of what they’d specifically like to study and might need some interesting areas to take a look at. I will mention that one of the tough parts of the concept of complexity is that it is so broad and general that it encompasses over a dozen other fields of study each of which one could get a Ph.D. in without completely knowing the full depth of just one of them much less the full depth of all of them. The book is so well written that I’d even recommend it to senior researchers in any of the above mentioned fields as it is certainly sure to provide not only some excellent overview history of each, but it is sure to bring up questions and thoughts that they’ll want to include in their future researches in their own specific sub-areas of expertise.
Gregory Chaitin’s book Proving Darwin: Making Biology Mathematical combining biology, microbiology, mathematics, evolution and even information theory is directly in my wheelhouse. I had delayed reading it following a few initial poor reviews, and sadly I must confirm that I’m ultimately disappointed in the direct effort shown here, though there is some very significant value buried within. Unfortunately the full value is buried so deeply that very few, if any, will actually make the concerted effort to find it.
This effort does seem to make a more high-minded and noble attempt than what I would call the “Brian Greene method” in which an academic seemingly gives up on serious science to publish multiple texts on a popular topic to cash in on public interest in that topic through sales of books. In this respect Chaitin is closer to Neil deGrasse Tyson in his effort to expound an interesting theory to the broader public and improve the public discourse, though I would admit he’s probably a bit more (self-) interested in pushing his own theory and selling books (or giving him the benefit of the doubt, perhaps the publisher has pushed him to this).
Though there is a reasonable stab at providing some philosophical background to fit the topic into the broader fabric of science and theory in the later chapters, most of it is rather poorly motivated and is covered far better in other non-technical works. While it is nice to have some semblance of Chaitin’s philosophy and feelings, the inclusion of this type of material only tends to soften the blow of his theoretical work and makes the text read more like pseudo-science or simple base philosophy without any actual rigorous underpinning.
I’m assuming that his purpose in writing the book is to make the theories he’s come up with in his primary paper on the topic more accessible to the broader community of science as well as the public itself. It’s easy for a groundbreaking piece of work to be hidden in the broader scientific literature, but Chaitin seems to be taking his pedestal as a reasonably popular science writer to increase the visibility of his work here. He admittedly mentions that his effort stems from his hobby as his primary area is algorithmic information theory and computer science and not biology or evolution, though his meager references in the text do at least indicate some facility with some of the “right” sources in these latter areas.
Speaking from a broad public perspective, there is certainly interest in this general topic to warrant such a book, though based on the reviews of others via Amazon, Goodreads, etc. the book has sadly missed it’s mark. He unfortunately sticks too closely to the rule that inclusion of mathematical equations is detrimental to the sale of ones books. Sadly, his broader point is seemingly lost on the broader public as his ability to analogize his work isn’t as strong as that of Brian Greene with respect to theoretical physics (string theory).
From the a higher perspective of a researcher who does work in all of the relevant areas relating to the topic, I was even more underwhelmed with the present text aside from the single URL link to the original much more technical paper which Chaitin wrote in 2010. To me this was the most valuable part of the entire text though he did provide some small amount of reasonable detail in his appendix.
I can certainly appreciate Chaitin’s enthusiastic following of John von Neumann but I’m disappointed in his lack of acknowledgement of Norbert Weiner or Claude Shannon who all collaborated in the mid part of the 20th century. I’m sure Chaitin is more than well aware of the father of information theory, but I’ll be willing to bet that although he’s probably read his infamous master’s thesis and his highly influential Bell Labs article on “A/The Mathematical Theory of Communication”, he is, like most, shamefully and wholly unaware of Shannon’s MIT doctoral thesis.
Given Chaitin’s own personal aim to further the acceptance of his own theories and work and the goal of the publisher to sell more copies, I would mention a few recommendations for future potential editions:
The greater majority of his broader audience will have at least a passably reasonable understanding of biology and evolution, but very little, if any, understanding of algorithmic information theory. He would be better off expounding upon this subject to bring people up to speed to better understand his viewpoint and his subsequent proof. Though I understand the need to be relatively light in regard to the number of equations and technicalities included, Chaitin could follow some of his heroes of mathematical exposition and do a slightly better job of explaining what is going on here. He could also go a long way toward adding some significant material to the appendices to help the higher end general readers and the specifically the biologists understand more of the technicalities of algorithmic information theory to better follow his proof which should appear in intricate glory in the appendix as well. I might also recommend excising some of the more philosophical material which tends to undermine his scientific “weight.” Though I found it interesting that he gives a mathematical definition of “intelligent design”, I have a feeling its intricacies were lost on most of his readership — this point alone could go a long way towards solidifying the position of evolution amongst non-scientists, particularly in America, and win the support of heavyweights like Dawkins himself.
I’ll agree wholeheartedly with one reviewer who said that Chaitin tends to “state small ideas repeatedly, and every time at the same shallow level with astonishing amount of redundancy (mostly consisting of chit-chat and self congratulations)”. This certainly detracted from my enjoyment of the work. Chaitin also includes an awful lot of name dropping of significant scientific figures tangential to the subject at hand. This may have been more impressive if he included the results of his discussions with them about the subject, but I’m left with the impression that he simply said hello, shook their hands, and at best was simply inspired by his having met them. It’s nice that he’s had these experiences, but it doesn’t help me to believe or follow his own work.
Though I would certainly agree that we could use a mathematical proof of evolution, and that Chaitin has made a reasonable theoretical stab, this book sadly wasn’t the best one to motivate broader interest in such an effort. I’ll give him five stars for effort, three for general content, but in the end, for most it will have to be at most a 2 star work overall.
RNA: Grant me eternal life. Genie: That’s not in my power to give. RNA: Grant me then at least a wish? Genie: (laughing) One wish? RNA: Yes, only one. Genie: Go ahead… RNA: (with great wile and guile) Make me thrifty. Genie: (with a cherry nod and a wink) Granted! RNA: Thank you!
David Christian, a trained historian, is one of the leading proponents of the relatively new concept of Big History, which I view as a sea-change in the way humans will begin to view not only the world but our place in it and what we might expect to come in the future. His work presents a truly monumental and profound thesis and a drastically new framework for where humankind fits into the universe. Of the broad variety of works I’ve read in the past several decades, it is simply one of the most interesting and cohesive theses I’ve come across, and I highly and unreservedly recommend it to everyone I know. I’d put it on par or above works like Jared Diamond’s Guns, Germs, and Steel and Matt Ridley’s The Rational Optimistamong others for its broad impact on how I now view the world. For scientists and researchers it has the potential to be the philosophical equivalent of The Bible and in fact, like many religious texts, it is in effect a modern day “creation myth,” albeit one with a scientific underpinning.
Christian’s work was initially brought to my attention by an article in the Chronicle of Higher Education by Jeffrey R. Young in which he mentioned that Bill Gates was a big fan of Christian’s work and had recommended it himself at a TED conference. (Gates is now also a financial supporter of Christian’s Big History Project.) I myself was aware of the Learning Company’s generally excellent coursework offerings and within a few weeks got an audio copy of the course of forty-eight lectures to listen to on my daily commute.
I’ve now devoured both his rather large text on the subject as well as a lecture series he created for a course on the subject. Below are brief reviews of the two works.The magnum written opus Maps of Time: An Introduction to Big History is an interesting change of reference from a historical perspective combining the disciplines of physics, cosmology, astronomy, geology, chemistry, microbiology, evolutionary theory, archaeology, politics, religion, economics, sociology, and history into one big area of contiguous study based upon much larger timescales than those traditionally taken in the study of historical time periods. Though it takes pieces from many disciplines, it provides for an interesting, fresh, and much needed perspective on who humans are and their place in not only the world, but the entire universe.
By looking at history from a much broader viewpoint (billions of years versus the more common decades or even just a few centuries) one comes away with a drastically different perspective on the universe and life.
I’d highly recommend this to any general reader as early as they can find time to read through it, particularly because it provides such an excellent base for a variety of disciplines thereby better framing their future studies. I wish I had been able to read this book in the ninth or tenth grade or certainly at the latest by my freshman year in college – alas the general conception of the topic itself didn’t exist until after I had graduated from university.
Although I have significant backgrounds in most, if not all, of the disciplines which comprise the tapestry of big history, the background included in the book is more than adequate to give the general reader the requisite introductions to these subjects to make big history a coherent subject on its own.
This could be an extremely fundamental and life-changing book for common summer reading programs of incoming college freshman. If I could, I would make it required reading for all students at the high school level. Fortunately Bill Gates and others are helping to fund David Christian’s work to help introduce it more broadly at the high school and other educational levels.
Within David Christian’s opus, there is also a collection of audio lectures produced by The Learning Company as part of their Great Courses series which I listened to as well. The collection of forty-eight lectures is entitled Big History: The Big Bang, Life on Earth, and the Rise of Humanity (Great Courses, Course No. 8050). It provides a much quicker philosophical overview of the subject and doesn’t delve as deeply into the individual disciplines as the text does, but still provides a very cohesive presentation of the overall thesis. In fact, for me, the introduction to the topic was much better in these audio lectures than it was in the written book. Christian’s lecture style is fantastic and even better than his already excellent writing style.
In the audio lectures Christian highlights eight major thresholds which he uses as a framework by which to view the 13.4 billion years of history which the Universe has presently traversed. Then within those he uses the conceptualization of disparities in power/energy as the major driving forces/factors in history in a unique and enlightening way which provides a wealth of perspective on almost every topic (scientific or historical) one can consider. This allows one to see parallels and connections between seemingly disparate topics like the creations of stars and the first building of cities or how the big bang is similar to the invention of agriculture.
I can easily say that David Christian’s works on big history are some of the most influential works I’ve ever come across – and having experienced them, I can never see our universe in the same naive way again.
For those interested in taking a short and immediate look at Christian’s work, I can recommend his Ted Talk “The History of Our World in 18 Minutes” which only begins to scratch the surface of his much deeper and profound thesis:
Given how profound the topic of big history is, I’m sure I’ll be writing about and referring to it often. Posts in relation to it can be found here with the tag: “big history“.
In Big History and the Future of Humanity, Fred Spier has built on an earlier work of his and on the work of Eric Chaisson to produce what is currently by far the most sophisticated attempt to construct a thematic scaffolding for big history. He carefully links the idea of increasing complexity with the associated themes of energy flows and the idea of goldilocks conditions—the notion that complexity can increase only under very special conditions and within quite exacting “boundary conditions.” Here are broad theoretical ideas that can help give greater depth and coherence to the story told within big history.
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big history promises to open up exciting new research agendas (including the meaning of complexity and energy flows, and the role of information across many disciplines),
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Introduction: A Modern Creation Myth?
sociologist Émile Durkheim referred to as “anomie”: the sense of not fitting in,
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Russian matryoshka doll
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Accounts of the past that focus primarily on the divisions between nations, religions, and cultures are beginning to look parochial and anachronistic—even dangerous.
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Chaisson, Eric J. Cosmic Evolution: The Rise of Complexity in Nature. Cambridge, Mass.: Harvard University Press, 2001.
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Margulis, Lynn, and Dorion Sagan. Microcosmos: Four Billion Years of Microbial Evolution. London: Allen and Unwin, 1987.
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Maynard Smith, John, and Eörs Szathmáry. The Origins of Life: From the Birth of Life to the Origins of
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Spier, Fred. The Structure of Big History: From the Big Bang until Today. Amsterdam: Amsterdam University Press, 1996.
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Part I: The Inanimate Universe
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This is very much how modern nuclear physics views the idea of a vacuum: it is empty but can nevertheless have shape and structure, and (as has been proved in experiments with particle accelerators) “things” and “energies” can pop out of the emptiness.
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Popol Vuh, or “Council Book,” a sixteenth-century Mayan manuscript,
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Dr. Lightfoot from Cambridge “proved” that God had created humans at exactly 9:00 AM on 23 October 4004 BCE.13
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The particles that did find a partner were transformed into pure energy,
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Perhaps this is where dark matter and energy are hiding?
As an anonymous wit is supposed to have put it: “Hydrogen is a light, odorless gas which, given enough time, changes into people.”25
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The idea that form and matter are different expressions of the same underlying essence was proposed by the Italian Giordano Bruno as early as 1584, in a book called Concerning the Cause, Principle, and One.
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Eric Chaisson’s Cosmic Evolution (2001) is an attempt to think through the meaning of order and entropy at many different scales, from stars to microbes,
Highlight (green) – 1. The First 300,000 Years: Origins of the Universe, Time, and Space > Location 1394
The second law of thermodynamics ensures that all complex entities will eventually die; but the simpler the structure, the better its survival chances, which is why stars live so much longer than humans
Highlight (yellow) – 2. Origins of the Galaxies and Stars: The Beginnings of Complexity > Location 1521
Even in the densest part of the galaxy, the disk, regions of empty space normally contain only about one atom in each cubic centimeter. But in the earth’s atmosphere, there may be 25 billion billion molecules in the same space.15 And pouring though this matter is the energy emitted every second by the Sun. In other words, human history has taken place in a pocket of the universe that is dense in matter and packed with energy. It is the extraordinary richness and complexity of this environment that made life possible.
Highlight (yellow) – 2. Origins of the Galaxies and Stars: The Beginnings of Complexity > Location 1755
A Danish scientist, Nicholas Steno, first argued that fossils were the remains of organisms that had once lived on earth.
Highlight (yellow) – 3. Origins and History of the Earth > Location 1991
Charles Lyell first stated clearly what came to be known as the principle of uniformitarianism.
Highlight (yellow) – 3. Origins and History of the Earth > Location 1999
As the English philosopher Francis Bacon pointed out in 1620, it was easy to see from these maps that the continents looked like pieces of a jigsaw puzzle. This similarity was most striking when the west coast of Africa was matched up with the east coast of South America.
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The idea that the continents really had drifted apart was given a thorough scientific basis in a book called The Origin of Continents and Oceans, written in 1915 by a German geographer, Alfred Wegener.
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uppermost layer of the earth (the lithosphere) consists of a number of rigid plates, like a cracked eggshell. There are eight large plates and seven smaller ones, as well as smaller slivers of material.
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Part II: Life On Earth
“The unfolding of events in the life cycle of an organism exhibits an admirable regularity and orderliness, unrivalled by anything we meet with in inanimate matter.”
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2158
In Schrödinger’s famous phrase, each living organism seems to have an astonishing capacity for “continually sucking orderliness from its environment.”
Highlight (blue) – 4. The Origins of Life and the Theory of Evolution > Location 2166
Unlike stars or crystals, which are general, all-purpose antientropy machines, …
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Think of homoestasis vs longevity
Darwin rarely used the term evolution, perhaps because it seems to imply some sort of mystical force that drives biological change in particular directions and thus would contradict his own view of biological change as a more open-ended process.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2240
Herbert Spencer, who did the most to popularize the term,
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2242
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Erasmus Darwin, suggested that species evolved so as to adapt better to their environments.
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In a book first published in 1809, the French naturalist Jean-Baptiste Lamarck suggested a possible mechanism. Perhaps minor changes acquired during a creature’s lifetime could somehow be passed on to its descendants.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2317
Time we spend in the gym does not guarantee that our children will be fit.
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Though epigenitics may be at work; see the studies of weight of self vs peers from c. 2010
Evolution works in fits and starts, according to the modern theory of “punctuated evolution,’ which was proposed by Niles Eldridge and Stephen Jay Gould in 1972.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2481
1920s by Alexander Oparin and J. B. S. Haldane, uses the basic ideas of evolutionary theory to explain not just the evolution of life on earth but also its initial appearance.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2512
But precisely how chemical evolution generated the first living organisms remains unclear. To understand these difficulties, we must break the problem into several levels. First, we need to explain how the basic raw materials of life were created: the chemical level. Second, we need to explain how these simple organic materials were assembled into more complex structures. Finally, we need to explain the origins of the precise mechanisms of reproduction encoded in the DNA that is present in all living organisms today. At present, we have reasonably good answers to the first question; we have plausible answers to the second question; and we are still puzzled by the third question.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2519
Harold Urey and his graduate student, Stanley Miller.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2537
Fred Hoyle and Chandra Wickramasinghe have argued that Earth was seeded with life from outside. This theory is known as Panspermia.
Highlight (yellow) – 4. The Origins of Life and the Theory of Evolution > Location 2572
A. G. Cairns-Smith has suggested that in shallow water, tiny crystals of clay may have provided a template for the formation of more complex molecules.
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Humans do not have the 60,000 to 80,000 genes we once believed were necessary to construct us but half that number, about 30,000. Roundworms have two-thirds as many genes as us (ca. 19,000), and fruit flies just under half (ca. 13,000); even Escherichia coli, a bacterium that inhabits our gut, may have as many as 4,000 genes. So, though constructing large organisms is tougher than constructing small organisms, the difference is not as great as we once imagined.
Highlight (yellow) – 5. The Evolution of Life and the Biosphere > Location 2782
It would seem that we’re not really becoming that more complex from a relative perspective here. What is the next major jump on the hockey stick?
As Margulis and Sagan put it: “For the macrocosmic size, energy, and complex bodies we enjoy, we trade genetic flexibility.”
Highlight (blue) – 5. The Evolution of Life and the Biosphere > Location 2867
The first extensive fossil evidence of multicellular organisms dates from the Ediacaran era, ca. 590 million years ago. But the fossil record of multicellular organisms really becomes abundant during the Cambrian era, from ca. 570 million years ago.
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In the middle of the nineteenth century, the German biologist Ernst Haeckel suggested that all single-celled organisms be classified within a separate kingdom of Protista. Then, in the 1930s, biologists realized that there was a fundamental difference between cells with nuclei and those without. As a result, they began to divide all organisms into two distinct kingdoms, the Prokaryota (organisms whose cells had no nuclei) and the Eukaroyta (organisms whose cells had nuclei). In some systems, the Eukaryota also include all multicellular organisms. In the second half of the twentieth century, powerful arguments emerged for the creation of separate kingdoms for fungi and for viruses (which are so simplified that they cannot even reproduce without hijacking the metabolic systems of other organisms). In the 1990s, Carl Woese proposed a new large classification to distinguish between the archaea and other forms of bacteria. Like all prokaryotes, archaea do not have nuclei; but unlike other prokaryotes they take in energy neither from sunlight nor from oxygen but from other chemicals.
Highlight (yellow) – 5. The Evolution of Life and the Biosphere > Location 3057
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John Maynard Smith and Eörs Szathmáry’s The Origins of Life (1999) is a history of life on Earth, constructed around the central idea of the evolution of complexity.
Highlight (green) – 5. The Evolution of Life and the Biosphere > Location 3367
Part III: Early Human History: Many Worlds
Net primary productivity (NPP) is that portion of energy from sunlight that enters the food chain through photosynthesis and is turned into plant material.
Highlight (yellow) – 6. The Evolution of Humans > Location 3418
This means that the impact of human history will be visible on scales of at least a billion years.
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new ways of extracting resources from their environments.
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We have seen that the emergence of new forms of complexity always involves the creation of large structures within which previously independent entities are locked into new forms of interdependence and new rules of cooperation.7 Following this hint, we should expect to find that the transition to human history is primarily marked not by a change in the nature of humans as individuals but rather by a change in the way individuals relate to each other.
Highlight (yellow) – 6. The Evolution of Humans > Location 3482
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In an article first published in 1967, two biochemists working in the United States, Vincent Sarich and Alan Wilson, argued that much genetic change is subject to similar rules.
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another possible candidate for the oldest hominine, Ardipithecus ramidus kadabba,
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It is possible that tool use evolved through a process known as Baldwinian adaptation (named after the nineteenth-century American psychologist who first described it systematically). This is a form of evolutionary change that appears to combine Darwinian and cultural elements, because behavioral changes lead to changes in an animal’s lifeways, thereby creating new selective pressures that lead, over time, to genetic changes.
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the so-called Levallois or Mousterian tools.
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Roger Lewin’s Human Evolution (4th ed., 1999)
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Steven Mithen has proposed that a number of once discrete brain modules, some of which may have been present in the earliest hominines, merged quite suddenly—perhaps within the last hundred thousand years—in a sort of linguistic “big bang.”
Highlight (yellow) – 7. The Beginnings of Human History > Location 4025
The Symbolic Species, Terrence Deacon
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Two factors stand out: the volume and variety of the information being pooled, and the efficiency and speed with which information is shared.
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In a deliberately provocative essay published in 1972, the anthropologist Marshall Sahlins describes the world of the Stone Age as “the original affluent society.”
Highlight (yellow) – 7. The Beginnings of Human History > Location 4323
In his simple but influential model of social structures, Eric Wolf has suggested that “kin-ordered” societies constitute a major type of human community, one that survives in many different forms even in the modern world.26
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Australian archaeologist Rhys Jones referred to such techniques as “fire stick farming.”39 Fire stick “farmers” deliberately set fire to bushland in regular cycles. In part, their aim was to prevent buildups of combustible material that could lead to hotter and more dangerous fires. But by clearing away underbrush, fire stick farming also encouraged the growth of new plants that, in turn, attracted browsers that could be hunted. Recent research suggests that such techniques may have been used as early as 45,000 years ago.40
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Part IV: The Holocene: Few Worlds
All of recorded human history has taken place within the Holocene interglacial.
Highlight (yellow) – 8. Intensification and the Origins of Agriculture > Location 4768
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The Trap of Sedentism
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In fact, most of human history (chronologically speaking) has taken place in communities quite innocent of state power. Even in the villages of the early agrarian era, for most people, most of the time, the important relationships were personal, local, and fairly egalitarian. Most households were self-sufficient, and people dealt with each other as people rather than as the representatives of institutions.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5442
But exploitation, like symbiosis, is never simple or unambiguous. Like predation in the nonhuman world, it can take more or less brutal forms. Lynn Margulis and Dorion Sagan observe, “In the long run, the most vicious predators, like the most dread disease-causing microbes, bring about their own ruin by killing their victims. Restrained predation—the attack that doesn’t quite kill or does kill only slowly—is a recurring theme in evolution.”
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5525
irrigation could raise agricultural productivity decisively, which is why irrigation has been one of the most revolutionary of all technological innovations.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5674
But population growth itself counts as a form of intensification, for in the era before fossil fuels, the energy resources available to human societies came mostly from human or animal muscle power.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5702
Inequality is what all top-down theories of state formation predict.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5730
as the sociologist Émile Durkheim first suggested, our thinking about the way the universe works often mirrors the way our own societies work.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5756
But most were used as sources of stored energy for their owners: where human labor power was as important a source of energy as oil is today, controlling energy meant controlling people. To make slaves more amenable to control, they were often separated at birth from their families. And, like domestic animals, many were deliberately kept in a state of infantile dependence that inflicted a sort of psychic amputation on them—they remained like children, and their helplessness made them easier to control. Both animal and human slaves could be controlled best if kept economically and psychically dependent on their owners.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 5797
Highlight (orange) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 6004
Outside the cities, they usually had little authority over the more localized forms of violence used to collect taxes, prosecute offenders or deal with banditry, or right local injustices. These powers were exercised by local elites or kinship groups. For most individuals, the righting of wrongs remained the duty of the household or kin group, which might seek the support of local patrons or officials.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 6032
Sounds like modern day Muslim middle eastern practice now…
Wolf calls “tributes.” This is justification for regarding societies with states as an entirely new type of social structure. Wolf treats the emergence of what he calls “tribute-taking” societies as a major transformation in the lifeways and the organization of human societies.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 6127
They include the emergence of dense populations, which generated a complex division of labor that posed new organizational problems, led to increased need for conflict resolution and to more frequent warfare, and encouraged the building of large monumental buildings as well as the creation of some form of writing.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 6136
The demographic dynamism introduced into human history by agriculture ensured that sooner or later, humans, like termites, would face the novel challenge of living in dense communities of their own species. For all the local differences, the solutions humans found in different parts of the world turned out to be remarkably similar to each other—and also strikingly similar to those found by termites and other social insects.
Highlight (yellow) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 6173
Marvin Harris’s classic essay, “The Origin of Pristine States” (1978).
Highlight (green) – 9. From Power over Nature to Power over People: Cities, States, and “Civilizations” > Location 6190
we can think of four main types of societies in this era: three—foragers, independent farmers, and pastoralists—lack states; one—agrarian civilizations—has states.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6226
World historians have become increasingly sensitive to the importance of large systems of interaction, and have often analyzed them using the notion of world-systems. Immanuel Wallerstein, the originator of such theories, argued that particularly in the modern era, it was necessary to analyze not just particular nations or civilizations, but rather the larger networks of power and commerce in which they were entangled, because these networks explained features that could not be explained solely from the internal history of particular regions. Wallerstein called these networks “world-systems,” even though they did not literally embrace the entire world, on the grounds that in many regards they functioned as separate worlds.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6354
Centers of gravity gave structure and shape to large networks of exchange, while hub regions were more lightweight and were more easily transformed by the exchanges that swept through them. So it was often in hub regions that significant innovations first became important because here was where they could have the greatest impact, while the mass and momentum of centers of gravity ensured that those regions normally changed more slowly.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6421
During the reign of Sargon of Akkad (who ruled from ca. 2350 BCE for ca. 50 years), we have the first evidence for a new stage in state formation: the appearance of a state controlling several different city-states and their hinterlands.14
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Rein Taagepera has tried to measure the areas ruled by “imperial systems” of Afro-Eurasia at different dates.
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three other factors shaped the pace and nature of innovation in this period: population growth, the expanding activity of states, and increasing commercialization and urbanization.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6721
Scale as a Source of Innovation
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“the respiration of a social structure.”
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6868
One reason for their immense influence was the overwhelming importance of the agrarian sector. Where most forms of production relied on organic materials and energy sources, agricultural output set limits to the production not just of foodstuffs but also of clothing, housing, energy, productive implements, and even parchment and paper.33 Because agriculture was the main motor of economic growth in the agrarian era, rates of innovation in agriculture dominated medium-term economic, political, and even cultural cycles.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6869
States as Sources of Accumulation
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 6998
The most stable states and the wisest rulers protected the productive base of their societies by taxing lightly, maintaining basic infrastructure, upholding law and order, and encouraging growth in rural populations and agricultural output.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 7063
Thus, an eleventh-century CE Muslim prince from Tabaristan wrote in a book for his son, “Make it your constant endeavor to improve cultivation and to govern well; for understand this truth: the kingdom can be held by the army, and the army by gold; and gold is acquired through agricultural development and agricultural development through justice and equity. Therefore be just and equitable.”50
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Powerful states spent freely on large prestige projects, including cities such as the Achaemenid capital, Persepolis. Such projects were designed to overawe subjects and rivals, but they also provided employment and attracted merchants and artisans.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 7086
In Muscovite history, the reign of Ivan the Terrible offers a horrifying example of the dangers of excessive predation.
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First, elites in tribute-taking societies had to be specialists in coercion and management rather than in production.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 7118
Stable and long-lived polities such as that of China thrived in part because they were rich enough and durable enough to maintain predictable and relatively light levels of taxation, which gave peasants a greater stake in productivity-raising innovations.57
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as Joel Mokyr has argued, technological innovation is unlikely to happen quickly where those who work lack wealth, education, and prestige, and those who are wealthy, educated, and have prestige know nothing about productive work.
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Exchange, Commerce, and Urbanization
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Thus urbanization itself dampened population growth, and it did so most decisively when cities grew fastest.
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Though tributary states normally tolerated and sometimes encouraged commerce, their predatory methods and willingness to resort to force were ever-present threats to the freedoms needed for trade to flourish. There was therefore a fundamental long-term conflict between the methods of tribute takers and those of merchants; and as long as tributary elites dominated political systems, this conflict limited the productivity-raising potential of commercial activity.
Highlight (yellow) – 10. Long Trends in the Era of Agrarian “Civilizations” > Location 7293
Part V: The Modern Era: One World
Scythians north of the Black Sea more than 2,000 years ago:
But though they are on the whole less violent, personal relations in modern urban communities also lack the intimacy and continuity of those in most traditional societies. Increasingly, they are casual, anonymous, and fleeting. These changes may help explain the loss of a clear sense of values and meaning in modern lives, a subtle and disorienting alteration in the quality of modern life that the French sociologist Émile Durkheim referred to in the late nineteenth century as “anomie.”
The German sociologist Norbert Elias has argued that these changes have reached deep within our psyches, as modern forms of work and time discipline, enforced through the market, have shaped behavior in interpersonal relations, table manners, and attitudes toward sexuality. He has shown how the “emotional economy” typical in the modern world arises out of a relaxation of external restraints combined with an intensification of internal restraints: “The compulsions arising directly from the threat of weapons and physical force gradually diminish, and . . . those forms of dependency which lead to the regulation of the affects [feelings or emotions] in the form of self-control, gradually increase.”
As Daniel Headrick writes: “Knowledge is both cause and effect of economic growth, and the information industry has been the primary cause of the acceleration of technological change in the past 200 years.”
the very nature of most premodern states suggests that as a general rule, in agrarian civilizations tribute-taking generated more wealth and certainly more power than commercial exchanges. This differential helps us understand what might at first appear puzzling: though commercial networks are as old as agrarian civilization, their impact on rates of innovation has been limited until the past two or three centuries. Why, then, did commercial exchanges suddenly become so much more significant in the modern era? Did they reach some critical threshold?
And what then is the next threshold? For think of what the Internet is doing to the entertainment industry and their reticence to go along with it.
Speaking generally, it is the steepness of this gradient of wealth that accounts for capitalism’s remarkable dynamism, just as the large temperature gradient between the Sun and the space surrounding it drives complex processes on Earth.
is the steepness of the gradient that drives wealth so efficiently through capitalist societies and that helps explain why, paradoxically, modern states have to be so much larger and more complex than the states of the tributary world.
So the onus is on the workers to ensure that their labor is productive enough to find a buyer. In this way, the economic lash can stimulate genuine, even creative, self-discipline, whereas the overseer’s whip can generate no more than grudging conformity.
Well-to-do merchants accumulate goods and redouble their profits, while the less well-to-do sit in their shops and sell. They control the markets and daily enjoy their ease in the cities. They take advantage of the pressing needs of the government to sell at twice the normal price. Their sons do not plough or hoe. Their daughters do not raise silkworms or weave. They have fancy clothing and stuff themselves on millet and meat. They earn fortunes while suffering none of the hardships which the farmers suffer. Their wealth enables them to hobnob with princes and marquises, and to dispose of greater power than the officials.29
This quote about 2nd century BCE China sounds a lot like modern day China.
this process was completed by 1279 after the conquest of South China by the Mongols under Kublai Khan. After reunification, two of the three conditions encouraging states to support commercialization (small size and intense rivalries) vanished, and the third (easy access to rich trading systems) lasted only slightly longer.
wealth. The mercantilist policies of European states in the seventeenth century—such as the Navigation Acts of the English commonwealth, which protected British commerce within British colonies—are good examples of new government attitudes toward commerce and the actions that these changes encouraged. Also illustrating this trend is the proliferation throughout Europe of patent laws, which were pioneered in Venice in the fifteenth century. Governments also began to promote innovation through the founding of scientific societies or the offering of prizes.
Over time, commercialization transformed traditional tributary elites. Such transformation was most likely to occur when demands on elite incomes rose sharply in environments where commercial revenues were available for the taking. The English wool trade offers a classic example, for it tempted landowners to clear the land of tenants and replace them with sheep, particularly in the sixteenth century, when new land became available as a result of the dissolution of the monasteries.
the invention in France of the Jacquard loom, which pioneered the use of digital coding as a form of mechanical control (1801);
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As early as 1837, the French revolutionary Blanqui used the term industrial revolution
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For most rural dwellers, these changes were catastrophic.
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This is now what is happening in most of the rest of the world now.
The appearance of societies in which most people depended entirely on markets for their subsistence was a new phenomenon, and it gave a tremendous stimulus to commercial production of goods of mass consumption.
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The idea that atmospheric pressure was a potential source of mechanical power had a history going back at least to the sixteenth century, and it may have been familiar in China as well as in Europe.23
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In 1718, a new owner, Thomas Lombe, in an early example of planned industrial espionage, stole techniques already in use in Italy to set up an improved factory.
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Richard Arkwright’s water frame, James Hargreaves’s spinning jenny, and Samuel Crompton’s spinning mule, a modification of the jenny.24
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Karl Polanyi argues in a classic study of modernity,
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Where literacy spread, knowledge became more abstract and less personal, and abstract knowledge began to acquire an authority quite independent from the prestige of particular teachers.
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In the nineteenth century, beginning in Germany, science itself began to be incorporated into entrepreneurial activity as companies set up laboratories specifically to raise productivity and profits. By the late nineteenth century, scientific research was taking a leading role in processes of innovation that might have simply petered out if they had continued to rely on the technical and practical skills of individual entrepreneurs and artisans.
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Think about how this is done now and how much of it is done by universities instead of by industry. Where is his innovation happening in the future?
The modern world is ruled by larger and more impersonal forces, from faceless bureaucracies to abstractions such as “inflation,” or “the rule of law.” Where abstract forces take over the work of coercion from the landlord, the executioner, and the overseer, it is not surprising that there should emerge cosmologies ruled by equally abstract forces.
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Joel Mokyr, The Lever of Riches (1990),
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Charles Tilly, Coercion, Capital, and European States, AD 990–1992 (rev. ed., 1992), is good on some of the political changes associated with the Industrial Revolution.
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During the “great depression” of the 1870s, it became apparent for the first time that economic growth could falter because of overproduction as well as underproduction.
Highlight (yellow) – 14. The Great Acceleration of the Twentieth Century > Location 9700
Over the following decades, it became clear that in a world of steadily increasing productivity, the problem of finding (or creating) markets would shape the rhythms of economic activity much as the problem of insufficient productivity had done in the agrarian era. As a result, the modern era is dominated by cycles of activity with a different (normally a shorter) periodicity, which we know as business cycles.
Highlight (yellow) – 14. The Great Acceleration of the Twentieth Century > Location 9702
Indeed, lifestyles have changed so greatly that they may be exerting a significant evolutionary impact on human bodies.
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The tensions and dislocations of the hurricane of change affecting the entire globe will ensure that conflict remains endemic, and modern weaponry will ensure that local conflicts continue to cause great suffering.
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Lester Brown argues that “while the Agricultural Revolution transformed the earth’s surface, the Industrial Revolution is transforming the earth’s atmosphere.”
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Part VI: Perspectives On The Future
“With chaos, it is sensitivity to initial conditions that makes the dynamics unpredictable. With emergent properties, it is the general inability of observers to predict the behavior of nonlinear systems from an understanding of their parts and interactions.”
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it is better than doing nothing at all, just as studying the form at a racetrack is better than tossing a coin. In the long run, you will end up with more money if you study the form.
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the space technologies envisioned by the Russian schoolteacher Konstantin Tsiolkovsky, which enabled the first human to leave Earth on 12 April 1961 and the first human to land on another heavenly body on 21 July 1969,
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Appendix 2: Chaos and Order
But the patterns we detect are really there, and their existence is one of the great puzzles of the universe. Why is there order of any kind? And what rules allow the creation and evolution of ordered structures?
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On Earth, the temperature differential between our sun and surrounding space provides the free energy needed to create most forms of complexity, including ourselves; energies created early in the history of our solar system drive the internal heat battery of Earth, which drives plate tectonics. These differentials enable energy to flow, and energy flows make patterns possible. And given enough time, the mere possibility of pattern makes it likely that patterns of many different kinds will eventually appear.
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After the first problem—explaining how order of any kind is possible—is addressed, the second problem remains. How did complex entities emerge, and, once they had emerged, how did they sustain themselves long enough to be noticed by us (or to be us)?
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Paradoxically, the tendency toward increasing entropy—the drive toward disorder—may itself be the engine that creates order.
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The drive toward disorder seems to create new forms of order, just as the energy of falling water can cause droplets of water to splash upward, or a river’s current can create eddies in which small amounts of water flow against the main current.
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Roughly speaking, the more complex a phenomenon is, the denser the energy flows it must juggle and the more likely it is to break down. So we should expect that as entities become more complex, they become less stable, shorter-lived, and rarer. Perhaps even a slight increase in complexity can sharply increase their fragility and, therefore, their scarcity.
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What we can do is to describe some of the ways in which complex structures emerge. The fundamental rule seems to be that complexity normally emerges step by step, linking already existing patterns into larger and more complex patterns at different scales.
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new rules of construction and change seem to come into play. These are known as emergent properties,
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“Leibig’s Law of the Minimum . . . states that populations will be limited by critical resources (e.g., water) that are in shortest supply” (Allen W. Johnson and Timothy Earle, The Evolution of Human Societies, 2nd ed. [Stanford: Stanford University Press, 2000], pp. 14–15).
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articles, “Immunological Time Scale for Hominid Evolution”; it was published in Science, 1 December 1967, pp. 1200–1203.
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There is a good short survey of theories of growth in J. L. Anderson, Explaining Long-Term Economic Change (Basingstoke: Macmillan, 1991); and see the survey in Mokyr, The Lever of Riches, chap. 7 (“Understanding Technological Progress”).
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Guide to highlight colors
Yellow–general highlights and highlights which don’t fit under another category below Orange–Vocabulary word; interesting and/or rare word Green–Reference to read Blue–Interesting Quote Gray–Typography Problem Red–Example to work through
Editor’s Note: Data relating to reading progress was added to this post on 10/21/16. Data relating to highlights, quotes, and marginalia added on 10/23/16.