Tag Archives: Brian Arthur

Increasing Returns and Path Dependence in the Economy by Brian Arthur

Summary

  1. The idea of increasing returns has come up every few decades but Brian Arthur’s precise and fully-modeled papers caused us to clearly understand what kinds of models have what kinds of implications. One outstanding characteristic of Arthur’s viewpoint is emphatically dynamic in nature. Learning by using or doing plays an essential role, as opposed to static examples of returns to scale (those based on volume-area relations). The object of study is a history. Another distinctive feature of most of the work is its stochastic character. This permits emphasis on the importance of random deviations for long-run tendencies. Other tendencies include the multiplicity of possible long-run states, depending on initial conditions and on random fluctuations over time, and the specialization (in terms of process or geographical location) in an outcome achieved. Increasing returns may also serve as a reinforcement for early leading positions and so act in a manner parallel to more standard forms of increasing returns. A similar phenomenon occurs even in individual learning, where again successes reinforce some courses of action and inhibit others, thereby causing the first to be used more intensively, and so forth. There are in all of these models opposing tendencies, some toward achieving an optimum, some toward locking in on inefficient forms of behavior. 

 Key Takeaways

  1. The papers here reflect two convictions I have held since I started work in this area. The first is that increasing returns problems tend to show common properties and raise similar difficulties and issues wherever they occur in economics. The second is that the key obstacle to an increasing returns economics has been the “selection problem” – determining how an equilibrium comes to be selected over time when there are multiple equilibria to choose from. Thus the papers here explore these common properties – common themes – of increasing returns in depth. And several of them develop methods, mostly probabilistic, to solve the crucial problem of equilibrium selection. 
  2. Arthur studied electrical engineering so was vaguely familiar with positive feedback already and became more intrigued when he read about the history of the discovery of the structure of DNA and read whatever he could about molecular biology and enzyme reactions and followed these threads back to the domain of physics. In this work, outcomes were not predictable, problems might have more than one solution, and chance events might determine the future rather than be average away. The key to this work, I realized, lay not in the domain of the science it was dealing with, whether laser theory, or thermodynamics, or enzyme kinetics. It lay in the fact that these were processes driven by some form of self-reinforcement, or positive feedback, or cumulative causation – processes, in economics terms that were driven by nonconvexities. Here was a framework that could handle increasing returns. 
    1. Great discoveries tend to come from outside the field 
  3. Polya Process – path-dependent  process in probability theory 
  4. In looking back on the difficulties in publishing these papers, I realize that I was naive in expecting that they would be welcomed immediately in the journals. The field of economics is notoriously slow to open itself to ideas that are different. The problem, I believe is not that journal editors are hostile to new ideas. The lack of openness stems instead from a belief embedded deep within our profession that economics consists of rigorous deductions based on a fixed set of foundational assumptions about human behavior and economic institutions. If the assumptions that mirror reality are indeed etched in marble somewhere, and apply uniformly to all economics problems, and we know what they are, there is of course no need to explore the consequences of others. But this is not the case. The assumptions economists need to use vary with the context of the problem and cannot be reduced to a standard set. Yet, at any time in the profession, a standard set seems to dominate. I am sure this state of affairs is unhealthy. It deters many economists, especially younger ones, from attempting approaches or problems that are different. It encourages use of the standard assumptions in applications where they are not appropriate. And it leaves us open to the charge that economics is rigorous deduction based upon faulty assumptions. At this stage of its development economics does not need orthodoxy and narrowness; it needs openness and courage. 
  5. I did not set out with an intended direction but if I have had a constant purpose it is to show that transformation, change, and messiness are natural in the economy. The increasing-returns world in economics is a world where dynamics, not statics, are natural; a world of evolution rather than equilibrium; a world or probability and chance events. Above all, it is a world of process and pattern change
  6. Positive Feedbacks in the Economy
    1. Diminishing returns, what conventional economic theory is built around, imply a single economic equilibrium point for the economy, but positive feedback – increasing returns – makes for many possible equilibrium points. There is no guarantee that the particular economic outcome selected from among the many alternatives will be the “best” one. Furthermore, once random economic events select a particular path, the choice may become locked-in regardless of the advantages of the alternatives
    2. Increasing returns do not apply across the board – agriculture and mining (resource-based portions) – are subject to diminishing returns caused by limited amounts of fertile land or high quality deposits. However, areas of the economy which are knowledge-based are largely subject to increasing returns. Even the production of aircraft is subject to increasing returns – it takes a large initial investment but each plane after that is only a fraction of the initial cost. In addition, producing more units means gaining more experience in the manufacturing process and achieving greater understanding of how to produce additional units even more cheaply. Moreover, experience gained with one product or technology can make it easier to produce new products incorporating similar or related technologies. Not only do the costs of producing high-technology products fall as a company makes more of them, but the benefits of using them increase. Many items such as computers or telecommunications equipment work in networks that require compatibility; when one brand gains a significant market share, people have a strong incentive to buy more of the same product so as to be able to exchange information with those using it already. 
    3. Timing is important too in the sense that getting into an industry that is close to being locked in makes little sense. However, early superiority does not correlate with long term fitness 
    4. Like punctuated equilibrium, most of the time the perturbations are averaged away but once in a while they become all important in tilting parts of the economy into new structures and patterns that are then preserved and built on in a fresh layer of development 
  7. Competing technologies, increasing returns, and lock-in by historical events 
    1. There is an indeterminacy of outcome, nonergodicity (path dependence where small events cumulate to cause the systems to gravitate towards that outcome rather than others). There may be potential inefficiency and nonpredictability. Although individual choices are rational, there is no guarantee that the side selected is, from any long term viewpoint, the better of the two. The dynamics thus take on an evolutionary flavor with a “founder effect” mechanism akin to that in genetics 
  8. Path dependent processes and the emergence of macrostructure 
    1. Many situations dominated by increasing returns are most usefully modeled as dynamic processes with random events and natural positive feedbacks or nonlinearities. We call these nonlinear Polya processes and show that they can model a wide variety of increasing returns and positive feedback problems. In the presence of increasing returns or self reinforcement, a nonlinear Polya process typically displays a multiplicity if possible asymptotic outcomes. Early random fluctuations cumulate and are magnified or attenuated by the inherent nonlinearities of the process. By studying how these build up as the dynamics of the process unfold over time, we can observe how an asymptotic outcomes becomes “selected” over time 
    2. Very often individual technologies show increasing returns to adoption – the more they are adopted the more is learned about them; in then the more they are improved, and the more attractive they become. Very often, too, there are several technologies that compete for shares of a “market” of potential adopters 
  9. Industry location patterns and the importance of history 
    1. This study indeed shows that it is possible to put a theoretical basis under the historical-accident-plus-agglomeration argument (mostly arbitrary location for determining where a city is established but then more people flock to it, it receives more investment, more buildings come up, etc. which leads to agglomeration and increasing returns).
  10. Information Contagion
    1. When a prospective buyer is making purchasing decisions among several available technically-based products, choosing among different computer workstations, say, they often augment whatever publicly available information they can find by asking previous purchasers about their experiences – which product they chose, and how it is working for them. This is a natural and reasonable procedure; it adds information that is hard to come by otherwise. But it also introduces an “information feedback” into the process whereby products compete for market share. The products new purchasers learn about depend on which products the previous purchasers “polled” or sampled and decided to buy. They are therefore likely to learn more about a commonly purchased product than one with few previous users. Hence, where buyers are risk-averse and tend to favor products they know more about, products that by chance win market share early on gain an information-feedback advantage. Under certain circumstances a product may come to dominate by this advantage alone. This is the information contagion phenomenon
  11. Self-Reinforcing Mechanisms in Economics
    1. Dynamical systems of the self-reinforcing or autocatalytic type – systems with local positive feedbacks – in physics, chemical kinetics, and theoretical biology tend to possess a multiplicity of asymptotic states or possible “emergent structures”. The initial starting state combined with early random events or fluctuations acts to push the dynamics into the domain of one of these asymptotic states and thus to “select” the structure that the system eventually “locks into”. 
    2. Self-reinforcing mechanisms are variants of or derive from four generic sources:
      1. Large set up or fixed costs (which give the advantage of falling unit costs to increased output)
      2. Learning effects (which act to improve products or lower their cost as their prevalence increases)
      3. Coordination effects (which confer advantages to “going along” with other economic agents taking similar action)
      4. Self-reinforcing expectations (where increased prevalence on the market enhances beliefs of further prevalence)
    3. Besides these 4 properties, we might note other analogies with physical and biological systems. The market starts out even symmetric, yet it ends up asymmetric: there is “symmetry breaking.” An “order” or pattern in market shares “emerges” through initial market “fluctuations.” The two technologies compete to occupy one “niche” and the one that gets ahead exercises “competitive exclusion” on its rival. And if one technology is inherently superior and appeals to a larger proportion of purchasers, it is more likely to persist: it possesses “selectional advantage.”
    4. Some more characteristics: multiple equilibria (multiple “solutions” are possible but the outcome is indeterminate, not unique and predictable); possible inefficiency, lock-in, path dependence
    5. We can say that the particular equilibrium is locked in to a degree measurable by the minimum cost to effect changeover to an alternative equilibrium. In many economic systems, lock-in happens dynamically, as sequential decisions “groove” out an advantage that the system finds it hard to escape from. Exiting lock-in is difficult and depends on the degree to which the advantages accrued by the inferior “equilibrium” are reversible or transferable to an alternative one. It is difficult when learning effects and specialized fixed costs are the source of reinforcement. Where coordination effects are the source of lock-in, often advantages are transferable. As long as each user has certainty that the others also prefer the alternative, each will decide independently to “switch”. Inertia must be overcome though because few individuals dare change in case others do not follow
  12. Path Dependence, Self-Reinforcement, and Human Learning
    1. There is a strong connection between increasing returns mechanisms and learning problems. Learning can be viewed as competition among beliefs or actions, with some reinforced and others weakened as fresh evidence and data are obtained. But as such, the learning process may then lock-in to actions that are not necessarily optimal nor predictable, by the influence of small events
    2. What makes this iterated-choice problem interesting is the tension between exploitation of knowledge gained and exploration of poorly understood actions. At the beginning many actions will be explored or tried out in an attempt to gain information on their consequences. But in the desire to gain payoff, the agent will begin to emphasize or exploit the “better” ones as they come to the fore. This reinforcement of “good” actions is both natural and economically realistic in this iterated-choice context; and any reasonable algorithm will be forced to take account of it. 
  13. Strategic Pricing in Markets and Increasing Returns
    1. Overall, we find that producers’ discount rates are crucial in determining whether the market structure is stable or unstable. High discount rates damp the effect of self-reinforcement and lead to a balanced market, while low discount rates enhance it and destabilize the market. Under high discount rates, firms that achieve a large market share quickly lose it again by pricing high to exploit their position for near-term profit. And so, in this case the market stabilizes. Under low discount rates, firms price aggressively as they struggle to lock in a future dominant position; and when the market is close to balanced shares, each drops its price heavily in the hope of reaping future monopoly rents. The result is a strong effort by each firm to “tilt” the market in its favor, and to hold it in an asymmetric position if successful. And so, in this case strategic pricing destabilizes the market
    2. The simple dynamics and stochastic model of market competition analyzed in this paper reveals striking properties. First, positive feedback or self-reinforcement to market share may result in bistable stationary distributions with higher probabilities assigned to asymmetric market shares. The stronger the positive feedback, the lower the probability of passing from the region of relative prevalence of one product to that of the other. Second, when producers can influence purchase probabilities by prices, in the presence of positive feedback, optimal pricing is highly state-dependent. The producers struggle for market shares by lowering prices, especially near pivot states with balanced shares. 

 What I got out of it

  1. Influential read discussing self-reinforcement, lock-in, increasing returns in knowledge-based economies/industries, path dependence, and more. Extremely applicable for business, investing, economics, learning, and more. A great mental model to have in your toolbox

The Nature of Technology: What it is and How it Evolves by Brian Arthur

Summary

  1. This book is an argument about what technology is and how it evolves. Technologies are put together from pieces – themselves technologies – that already exist. Technologies therefore share ancestry, combine more, and combined again to create further technologies. Technology evolves similar to how a coral reef builds itself from activities of small organisms – it creates itself from itself; all technologies are descended from earlier technologies. Technologies are not “inventions” that come from nowhere so in a sense, technology created itself 

Key Takeaways

  1. Technology, Evolution, Recursion, Phenomena
    1. Technologies have a recursive structure and collectively advance by capturing phenomenon and putting them to use. The economy arises from technologies and therefore issued forth from all these capturings of phenomena and subsequent combinations
    2. We are caught between two huge and unconscious forces: our deepest hope as human’s lies in technology but our deepest trust lies in nature. These forces are like tectonic plates grinding inexorably into each other in one long slow collision. The collision is not new but more than anything else it is defining our era. Technology is steadily creating the dominant issues and upheavals of our time. We are moving from an era where machines enhance the natural to one that brings in technologies that resemble or replace the natural. As we learn to use these technologies we are moving from using nature to intervening directly within nature. And so the story of the century will be about the clash between what technology offers and what we feel comfortable with. 
    3. We have great understanding about individual technologies but very little in the way of the general understanding. Much like in 1800 there was a great understanding about the family relationships among animals but few principles like evolution to hold all this knowledge together. Missing in other words is the theory of technology – an “Ology” of technology
    4. For me how technology evolves is the central question in technology because if we could understand its evolution we could understand that most mysterious of processes: innovation. Combination drives change or at least the innovation of technology. Invention proceeds from the constructive assimilation of pre-existing elements into new syntheses. So the very cumulation of earlier technologies begets further accumulation. The more there is to invent with the greater will be the number of inventions. These two pieces lead to a theory of evolution of technology that novel technologies arise by combination of existing technologies and that existing technologies beget further technologies. 
    5. Why we are seeing change, innovations, disruption at levels never before seen – there are more building blocks than ever before that can be combined and recombined in new ways, leading to new innovations. This trend seems likely only to continue
    6. The change in vision I am proposing is from standalone technologies, each with a fixed purpose, to seeing them as objects that can be formed into endless new combinations. These technologies can be easily combined and they form building blocks which can be used again and again. Technology, once a means of production, is becoming a chemistry
    7. Arthur gives three definitions of technology:
      1. A means to fulfill a human purpose
      2. An assemblage of practices and components
      3. An entire collection of devices and practices available to a culture.
      4. A means to fulfill a purpose: a device, method, or process (combination, recursiveness, reliance on a natural effect(s) 
    8. Technology consists of parts organized into component systems or modules and some of these form the central assembly and others have supporting functions. This is a general rule: what starts as a series of parts loosely strung together, if used heavily enough, congeals into a self-contained unit. The modules of technology over time become standardized units. In this sense technologies have a recursive structure as they consist of technologies within technologies all the way down to the elemental parts. There is no characteristic scale for technology as every technology stands ready, at least potentially, to become a component in further technologies at a higher level 
    9. Combination is inherently a very disciplined process as all these different modules must not only work together but further the primary function 
    10. Just like higher level technologies are composed of a series of assemblies and subassemblies, they’re also composed of a series of natural phenomenon. For example, maybe one or two phenomena such as trucks use the burning of fuel and low friction to roll or several phenomena such as detecting planets that are too far away to see directly. But, in either case, it is combinations of natural effects that we can exploit for greater technology
    11. Phenomena are the source of all technologies. In the essence of technology lies and orchestrating them to fulfill a purpose. Phenomenon or simply natural effects exist independently of humans and of technology. They have no use attached to them. The principal by contrast is the idea of use of a phenomenon for some purpose and it exist very much in the world of humans and of use. In practice, before phenomenon can be used for technology, they must be harnessed and set up to work properly. They can barely be used in raw form and must be coaxed to operate satisfactorily and may only work in a narrow range of conditions. So, the right combination of means to set them up for the purpose intended must first be found. Therefore the practical technology consists of many phenomena working together. Technology can then be thought of as a collection of phenomenon captured and put to use. In its essence a technology consist of certain phenomenon programmed for some purpose. Technology can then be seen as a metabolism where the phenomenon are the genes of technology – they interact in complex ways, converse with each other, similar to how subroutines and computer programs call each other. Biology programs genes into myriad structures and technology programs phenomena to myriad uses 
    12. I like to think of phenomena as hidden underground – not available until discovered in mind into. This is general with phenomena as a family of phenomena is mined into effect. Some covered earlier begin to create methods and understandings that help uncover later. One effect leads to another, then to another, until eventually a whole vein of related phenomenon has been mined into. A family of a facts forms a set of chambers connected by seams and passageways – one leading to another. And that is not all. The chambers in one place, one family, of the facts leads through passageways to chambers elsewhere to different families. Quantum phenomenon could not have been uncovered without the prior uncovering of the electrical phenomena. Phenomenon form a connected system of excavated chambers and passageways. The whole system underground is connected. This build out happens slowly as it earlier forms of instruments and devices help uncover later ones. In this way, the uncovering a phenomenon builds itself out of itself. Phenomena accumulate by bootstrapping their way forward. 
    13. Not every phenomenon of course has an immediate use but when a family of phenomenon is uncovered, a train of technology typically follows. 
    14. Technology is not merely applied science. It is better to say it builds both from science and from its own experience. Science is in no small part the probing of nature via instruments and methods – via technology
    15. Evolution works by new technologies forming from existing ones which act as building blocks. Sometimes these blocks come from radical innovation but novel building block elements also arise from standard day-to-day engineering. 
    16. Novel technologies come from linking, conceptually or physically, the needs of some purpose with an exploitable effect (or set of effects). Invention, we can say, consists in linking a need with some effect to satisfactorily achieve that need
    17. Technologies tend to become more complex – much more complex – as they mature. 
  2. Domains
    1. The greatest innovations are new domainings – a switching to a new cluster of technologies. They allow not only a wholly new and more efficient way to carry out a purpose but allow entirely new possibilities. As when the provision of power switched from being expressed in waterwheel technology to steam. A change in domain is the main way in which technology progresses but a novel domain may appear to have little direct importance early on. Such components and the way they are used do not just reflect the style of the times, they define the style of the times. An era does not just create technology, technology creates the era
    2. Half of the effectiveness of a domain lives in its reach. The possibilities it opens up. The other half lives in using similar combinations again and again for different purposes
    3. The domain’s grammar determines how its elements fit together and the conditions under which they fit together determines what works. Where do such grammars arise from? Well, of course ultimately from nature. Behind the grammar of electronics lies the physics of the electron motions and the laws of electrical phenomena. Big grammar determines how the elements interrelate, interact, and combine to generate structures. Grammars in large part reflect our understanding of how nature works in a particular domain. Mastery in the technology in fact is difficult to achieve because of technology grammar. Unlike a linguistic one, this grammar changes rapidly. 
    4. Domains are worlds in the sense that experts lose themselves in them. They disappear mentally into them just as we disappear into the world of English when we write a letter. They think in terms of purposes and work these backwards into individual operations in their mental world. Much as a composer works a musical theme back into the instrumental parts that will express it. Some domains have deep worlds with a lot of possibilities. What can be accomplished easily in the domain’s world constitutes that domains power. So, understanding this leads to the natural conclusion that an object or business activity to be worked on effectively must be brought into more than one world to make use of what can be accomplished in each. But there is a general lesson here: cost accumulates anywhere and activity leaves one world and enters another. Shipping a freight containers by sea is not expensive but transferring freight from the domain of rail into the shipping container world requires the cumbersome and expensive technologies of railhead, stocks, container handling cranes, and stevedoring. Such bridging technologies are usually the most awkward aspect of a domain. They create delays and bottlenecks and therefore run-up costs but they are necessary because they make the domain available in control what can enter and leave its world. We can think of a domain as containing a small number of central operations that are streamlined and cheap – maritime container transportation say. But, surrounding these on the outer edges of the domain, are the slower and more awkward technologies that allow activities to enter the world and leave it when finished – the docs and gantry cranes of that world. These in general are costly. Domains reflect the power of the worlds they create but they also reflect its limitations. There is nothing static about these worlds. What can be accomplished constantly changes as a domain evolves and as it expands its base of phenomena. One implication is that innovation is not so much a parade of inventions with subsequent adoptions. It is a constant re-expressing or redomaining of old tasks within new worlds of the possible
    5. If we can see technologies as having dynamic insides we can better understand how technology can modify themselves over their lifetime. We can see that technologies interior components are changing all the time. As better parts are substituted, materials improve, methods for construction change, the phenomenon the technology is based on are better understood, and new elements become available, its parent domain develops. So, technology is not a fixed thing that produces a few variations or updates from time to time. It is a fluid thing – dynamic, alive, highly configurable, and highly changeable overtime. The second difference lies in how we see technology’s possibilities in its collective sense. Technology does not just offer a set of limited functions. It provides a vocabulary of elements that can be put together or programmed in endlessly novel ways for endlessly novel purposes. 
  3. Design & Invention
    1. Requirements start from the key purpose and proceed outward, the needs of one assembly determining those of the next. A design is a set of compromises. Intention comes first and the means to fulfill it – the combination of components – fall in behind it. Design is expression 
    2. Many innovations and great designs do not come from genius but from an accumulation of knowledge and expertise slowly gathered over years 
    3. The search is continuous, conceptual, wide, and often obsessive. This continuous thinking allows the subconscious to work, possibly to recall an effect or concept from past experience, and it procures a subconscious alertness so that when a candidate principle or a different way to define the problem suggests itself the whisper at the door is heard. Strangely, for people who report such breakthroughs, the insight arrives whole, as if the subconscious had already put the parts together. And it arrives with a “knowing” that the solution is right – a feeling of its appropriateness, its elegance, its extraordinary simplicity. The insight comes to an individual person, not a team, for it wells always from an individual subconscious. And it arrives not in the midst of activities or in frenzied thought, but in moments of stillness. One must be open to see a purpose for what appears to be a spurious effect 
    4. At the creative heart of invention lies appropriation, some sort of mental borrowing that comes in the form of a half conscious suggestion 
    5. Invention at its core is mental association. Principles often apply across field and at the core of this mechanism – call it principle transfer – is seeing an analogy. 
    6. An emerging technology always emerges from a cumulative of previous components and functionalities already in place. This is the pyramid of causality. Particularly important is knowledge – both scientific and technical – that has cumulated over time 
    7. Origination is at bottom a linking – a linking of the observational givens of a problem with a principle (a conceptual insight) that roughly suggests these, and eventually with a complete set of principles that reproduces these. At heart, all inventions had the same mechanism: all link a purpose with a principle that will fulfill it, and all must translate that principle into working parts 
    8. A technology develops not just by the direct efforts applied to it. Many of a technology’s parts are shared by other technologies, so a great deal of development happens automatically as components improve in other uses “outside” that technology. A technology piggybacks on the external development of its components. This internal replacement is part of what makes technologies more complex as they age but so does structural deepening. Sometimes changing internal components won’t do, so adding assemblies or systems is needed. 
    9. Origination is not just a new way of doing things, but a new way of seeing things. But it threatens. It can cause an emotional mismatch between the potential of the new and security of the old. Old technologies can lock in because of this and causes a phenomenon we will call adaptive stretch. It is easier to reach for the old technology and adapt it by “stretching” it to cover the new circumstances. There is a natural cycle. A new principle arrives, begins development, runs into limitations, and its structure elaborates. The new base principle is simpler, but in due course it becomes elaborated itself. 
    10. Just as pulling on one thread of a spider’s web causes the web to stretch and reshape itself in response, so the arrival of a new technology causes the web of prices and production in the economy to stretch and reshape itself across all industries. Cheaper steel due to the Bessemer process caused railroads, construction, and heavy machinery to changed their costs and what they could offer their consumers 
    11. Innovation emerges when people are faced by problems: particular, well-specified problems. It arises as solutions to these are conceived of by people stating many means or many functionalities that they can combine. It is enhanced by funding that enables this by training and experience in myriad functionalities. By the existence of special projects and labs devoted to the study of particular problems and by local cultures which foster deep craft. But it is not a monopoly of a single region or country or people. It arises anywhere problems are studied and sufficient background exists in the pieces that will form solutions. In fact we can see that innovation has two main themes. One is this constant finding or putting together of new solutions out of existing tool boxes of pieces and practices. The other is industries constantly combining their practices and processes with functionality is drawn from newly arriving toolboxes, new domains. This second theme, like the first, is about the creation of new processes and arrangements, new means to purposes. But it is more important. This is because it is a new domain of significance. Think of the digital one – it is encountered by all industries in an economy. As this happens, the domain combines some of its offerings with arrangements native to many industries. The result is new processes and arrangements, new ways of doing things – not just in one area of application but all across the economy. 
    12. Because all technologies come from some combination of past technologies, the value of the technology lies not only in what can be done with it but also in what further possibilities it will lead to. Inventions beget more inventions as there are more possible combinations, leading to exponential growth. Even if new technologies can potentially be supplied by the combination of existing ones, they will only come into existence if there exist some need, some demand for them. Or, even better yet, opportunities for technology niches they can usefully occupy. 
  4. Other
    1. Ironically we can say that design works by combining and manipulating clichés. But, still, a beautiful design always contain some unexpected combination that shocks us with its appropriateness. 
    2. We must get comfortable with technology with non-physical effects such as organizational or behavioral effects like the monetary system, contracts, symphonies, algorithms, legal codes, and so on
    3. All explanations are constructions from simpler parts
    4. I do not believe there is any such thing as genius. Rather it is the possession of a very large quiver of functionalities and principles. 
    5. New bodies of technology tend to have their leading edge highly concentrated in one country or region as real advanced technology issues not from knowledge but from something we’ll call deep craft. It is more than knowledge. It is a set of knowing. Knowing what is likely to work and not work. Knowing what methods to use, what principles, what parameters. It derives from a shared culture of beliefs, an unspoken culture of common experience. Deep knowings in a technology can be levered into deep knowings in another. Technology proceeds out of deep understandings of phenomena and he’s become embedded as a deep set of shared knowing that reside in people and establishes itself locally and that grows over time. This is why countries that lead in science lead also in technology. And so, if a country wants to lead in advanced technology, it needs to do more than invest in industrial parks for vaguely foster innovation. It needs to build its basic science without any stated purpose of commercial use and it needs to culture that science in a stable setting with funding and encouragement. Let the science sow itself commercially and small startup companies allow these nascent ventures to grow and sprout with minimal interference. Allow the science and its commercial applications to seed new revolutions. Building a capacity for advanced technology is not like planning production in a socialist economy but more like growing a rock garden. Planting, watering, and weeding are more appropriate than five year plans
    6. Human needs are not just created by biological nerds or prosperity but are also created directly by individual technologies. Once we possess rocketry, we experience a need for space exploration. However the vast majority of niches for technology are created not from human needs but from the needs of technologies themselves. The reasons are several. For one thing every technology by its very existence sets up an opportunity for fulfilling its purpose more cheaply or efficiently. And, so, for every technology there exists always an open opportunity. And, for another, every technology requires supporting technologies to manufacture it, organize for its production and distribution, maintain it, and enhance his performance. And these require their own sub supporting technologies. The third reason technology generates needs is because they often cause problems indirectly. In this it generates needs or opportunities for solutions
    7. These technologies and their needs grow fractally. Entertainment used to consist of public speeches or shows but now novels, movies, podcasts, sports and so much more exist too. 
    8. Arthur thinks of the economy as the set of arrangements and activities by which a society satisfies its needs. The economy is an expression of its technologies. The economy in this way emerges from its technologies. It constantly creates itself out of its technologies and decides which new technologies will enter it. Notice the circular causality at work here. Technology creates the structure of the economy and the economy mediates the creation of novel technology and therefore its own creation
    9. Technologies can cause structural change in the economy and this change is fractal – it branches out at lower levels just as an embryonic arterial system branches out as it develops into smaller arteries and capillaries 
    10. The more high-tech and sophisticated technologies become, the more they become biological we are beginning to appreciate the technology is as much metabolism as mechanism. As we come to better understand biology we are steadily seeing it as more mechanistic as we better understand the mechanisms behind it. Conceptually at least, biology is becoming technology and physically technology is becoming a biology. The two are starting to close on each other and, indeed, as we move deeper into genomics, more than this, they are starting to intermingle
    11. As technology becomes more biological and generative, the economy reflects this too. In the generative economy, management derives its competitive advantage not from its stock of resources and its ability to transform these into finished goods but from its ability to translate its stock of deep expertise into ever new strategic combinations. Reflecting this, nations will prosper not so much from the ownership of resources as from the ownership of specialized scientific and technical expertise

What I got out of it

  1. A fascinating and deep read about technology, how it evolves, permeates, and builds off of itself. Some rich language and concepts to apply to many disparate fields