xv The most valuable gift one can receive is thoughtful criticism
p.6 The economy is a marvel of complexity. Yet no one designed it and no one runs it... when one steps back
and looks at the entirety of the $36.5 trillion global economy, it is clear that no one is really in charge.
p.12 Evolution is an algorithm; it is an all-purpose formula for innovation, a formula
that, through its special brand of trial and error, creates new designs and solves difficult problems. Evolution
can perform its tricks... in any system that has the right information-processing and information-storage characteristics.
In short, evolution's simple recipe of "differentiate, select, and amplify" is a type of computer program - a program
for creating novelty, knowledge, and growth. Because evolution is a form of information processing, it can do its
order-creating work in realms ranging from computer software to the mind, to human culture, and to the economy. [JLJ - perhaps
even in the process of selecting paths to explore in playing a game ]
p.13 The evolutionary philosopher Daniel Dennett calls evolution a general-purpose algorithm for creating
"design without a designer."
p.14 Evolution creates designs, or more appropriately, discovers designs, through
a process of trial and error. A variety of candidate designs are created and tried out in the environment; designs that are
successful are retained, replicated and built upon, while those that are unsuccessful are discarded... Evolution
is a method for searching enormous, almost infinitely large spaces of possible designs for the almost infinitesimally small
fraction of designs that are "fit" according to their particular purpose and environment. As [evolutionary philosopher Daniel
C. ] Dennett puts it, evolution is a search algorithm that "finds needles of good design in haystacks of possibility."
p.18 Scientists refer to parts or particles that have the ability to process information and adapt their
behavior as agents and call the systems that agents interact in complex adaptive systems. Other
examples of complex adaptive systems include the cells in your body's immune system, interacting organisms
in an ecosystem, and users on the internet. [JLJ - perhaps even interacting pieces on a gameboard.]
p.19-20 If the economy is indeed a complex adaptive system then this has four important implications. First,
it means that for the past century, economists have fundamentally misclassified the economy and that the mainstream economic
theory reflected in textbooks, management thinking, and government policies today is either wrong or, at best, only approximately
right... Second, viewing the economy as a complex adaptive system provides us with a new set of tools, techniques,
and theories for explaining economic phenomena... Third, it means that wealth must be a product of evolutionary processes...
Fourth and finally, history shows that each time there has been a major shift in the paradigm of economic theory, the tremors
have been felt far beyond the academic world... we can begin to explore its implications for business and society.
p.31-32 [Leon] Walras saw the balance of supply and demand in a market as metaphorically like the balance
of forces in a physical equilibrium system... Walrus imported the concept of equilibrium from physics into economics and laid
he mathematical foundations for the Traditional Economics found in textbooks and journals today.
p.55 As we will see in chapter 8, in complex adaptive systems, small innocuous events can occasionally
set off avalanches of change.
p.69 In chapter 1, I defined a complex adaptive system as a system of interacting agents that adapt
to each other and their environment.
p.74 Like a snowball starting down a hill, the idea of viewing the economy as a complex adaptive
system gathered pace.
p.99 In chapter 3, I argued that the economy had been misclassified by Traditional Economics
as an equilibrium system, but in fact is a complex adaptive system.
p.100 A useful starting point is to observe that the economy is a dynamic system...
A convenient way to describe a dynamic system is in terms of stocks and flows... When one
starts thinking of the economy as a collection of stocks and their related flows, it quickly becomes apparent that the various
stocks and flows are connected to each other in complex ways.
p.138 there is a complex battle of beliefs going on within the heads of agents and among the agents, which
leads to volatility and complex patterns in the market... In the complex adaptive system of the economy, understanding
the micro-level behaviors of individuals is essential to understanding how the system as a whole behaves. For over
a hundred years, economics has made do with a model of human behavior that most economists now recognize as overly simplistic
and fundamentally at odds with an enormous body of evidence, simply for the sake of mathematical tractability.
p.141 Networks are an essential ingredient in any complex adaptive system. Without interactions
between agents, there can be no complexity... Yet, despite the importance of networks to economic
activity, they have not been a central concern of economists until quite recently... Traditional Economics
has tended to gloss over networks because they don't fit neatly into the equilibrium paradigm.
p.153 The more interactions required to get something done, the higher the probability of a conflict
or a constraint.
p.167 We have previously discussed how the micro-level interactions of agents in a complex adaptive
system create macro-level structures and patterns.
p.185 Complexity Economics does not have all the answers to the puzzle of economic patterns,
but it provides us with new tools to begin to understand how these various factors combine to result in the behaviors
we observe.
p.187 Businesspeople, journalists, and academics all gravitate quite naturally to using images of
ecosystems and evolution when they speak about the economy. One of the strongest claims of Complexity Economics is
that this language is no mere metaphor - organizations, markets, and economies are not just like evolutionary systems;
they truly, literally are evolutionary systems. [JLJ - perhaps this applies to chess as well ]
p.187 evolution is not just about biology. Rather, evolution is a general-purpose and highly powerful
recipe for finding innovative solutions to complex problems. It is a learning algorithm that adapts to changing
environments and accumulates knowledge over time. It is the formula responsible for all the order, complexity, and
diversity of the natural world... it is the same formula that lies behind all the order, complexity, diversity, and, ultimately,
wealth in the economic world... Daniel Dennett, an evolutionary theorist... calls evolution a method
for "creating design without a designer."
p.211 evolution manages what John Holland calls the tension between exploration and exploitation...
Every time evolution occupies a new part of the fitness landscape, it is placing bets to sample the unknown.
But like any bettor, as evolution gets more information, it wants to double up on the bets that look most promising.
p.212 I have already mentioned Dennett's notion of Good Tricks. Good Tricks are moves on
the fitness landscape that are not required on pain of extinction, but rather are so attractive that there is a strong probability
they will be repeatedly and independently discovered by evolutionary searches of the landscape.
p.212 Dennett also refers to another factor - Forced Moves. In the game of chess, players sometimes
find themselves in a position in which they have no choice on what to do next... Some Forced Moves are created by
the constraints imposed by the laws of physics and chemistry.
p.213 Mathematicians and evolutionary theorists have explored a variety of alternative search algorithms
on different landscape shapes. Some are better for searching perfectly random landscapes, and some are better for
searching highly ordered and regular landscapes. But for landscapes that are in between, are rough-correlated,
and have complex features such as plateaus, holes, and portals, evolution is hard to beat. And when the landscape
is constantly changing, when the search problem is a dynamic one, when one must balance the tension between exploring and
exploiting - evolution truly is the grand champion.
p.216 In effect, evolution says, "I will try lots of things and see what works and do more of what
works and less of what doesn't." ... The algorithm learns what the fitness function "wants," ... the evolutionary
process generates novelty as it searches for fitter and fitter designs.
p.222 [Kaufman quoted] Adaptive evolution is a search process
- driven by mutation, recombination, and selection - on fixed or deforming fitness landscapes. An adapting
population flows over the landscape under those forces. The structure of such landscapes, smooth or rugged,
governs both the evolvability of populations and the sustained fitness of their members. The structure of
fitness landscapes inevitably imposes limitations on adaptive search
p.324 We may not be able to predict or direct economic evolution, but we can design our institutions
and societies to be better or worse evolvers... The message of Complexity Economics is that evolution may indeed
be cleverer than we are, but rather than outsmart it, we can understand it and harness its power to serve human purposes.
p.324 Strategy can be defined as the determination of the basic long-term goals and objectives of
an enterprise, and the adoption of courses of action and the allocation of resources necessary for carrying out these goals...
First, strategy is inherently forward looking. To develop a strategy, one must make a determination about where one
wants to be in the future. Second, strategy is about creating a plan for getting to the desired future state
and committing to a course of action defined by that plan.
p.329 All competitive advantage is temporary. [JLJ - perhaps, but a true competitive advantage should be
dynamic enough to adapt to unknown, changing conditions and re-establish itself. ]
p.334 Rather than thinking of strategy as a single plan built on predictions of the future, we should
think of strategy as a portfolio of experiments, a population of competing... plans that evolves over time.
p.336,337 One way of interpreting what [Microsoft CEO Bill] Gates did [in the year 1987]
was that he set a high level aspiration - to be the leading PC software company - and then he created a portfolio
of strategic experiments that had the possibility of evolving toward that aspiration... the effect was to
create an adaptive strategy that was robust against the twists and turns of potential history.
p.337 Constructing a portfolio of experiments requires a collective understanding of the current
situation and shared aspirations... processes need to be established that enable the amplification of successful
... Plans and the elimination of unsuccessful Plans.
p.338 A former senior executive... told me... He saw the point
of strategic planning not as predicting the future, but as a learning exercise to prepare people for a future that was inherently
uncertain... Most processes are focused on creating plans and making decisions rather than learning... the process
must be fueled by facts and analysis.
p.339 an evolutionary approach to strategy emphasizes creating choices, keeping options open, and
making the tree of possibilities as bushy as possible at any point in time. Options have value.
An evolving portfolio of strategic experiments gives the management team more choices, which means better odds that some of
the choices will be right... The objective is to be able to make lots of small bets, and only make big bets as part
of amplifying successful experiments when uncertainties are much lower.
p.343,344 the aspiration must capture an important insight about the selection pressures that the outside
world is subjecting the organization to... one must strike an important balance in formulating an aspiration. It needs
to be specific enough to provide selection pressure, but not so specific as to require the ability to predict the future...
a good aspiration provides a powerful motivating force to keep the company in constant motion, trying new things, and supporting
the ethic of experimentation... To be adaptive, a company must be restless, never satisfied with its progress, constantly
searching and experimenting.
p.345,346 An evolutionary approach to strategy emphasizes keeping the strategy tree bushy and the
options open for as long as possible... one must know which initiatives are promising and which are not... Every...
Plan must have clear, thoughtful measures of success and a plan for collecting data in as close to real time as possible...
Other, more operational measures... may provide a more complete, real-time picture of a strategy experiment's health than
would standard accounting-based financial measures alone. For an evolutionary approach to work, one needs real-time
feedback on where the nectar is [JLJ - an example was previously discussed involving Bees reporting the presence
of nectar to other bees and swarming to retrieve it] , and thus each strategy experiment must have a customary balanced
scorecard [JLJ - a set of performance metrics that is designed to provide visibility into value creation] and the measurement
systems for carrying it out.
p.347,348 one's mind-set is perhaps the most important factor in creating an adaptive approach to strategy.
One way to picture an adaptive mind-set is to think more like a venture capitalist than a manager... venture
capitalists use their portfolios to learn their way into the future and thus generate high returns out of some of the riskiest
and fastest changing markets in the business world... Above all, an adaptive mind-set is willing to say, "We
learned something new; we need to change course."
p.360 In essence, we balance exploring and exploiting over our lifetimes. The early
emphasis is on exploring while we form our mental models and get feedback from the environment, but eventually
we settle into a groove, and the emphasis shifts to exploiting the model we have developed.
p.360 the punctuated nature of change in complex adaptive systems is almost perniciously designed to lull
our pattern-recognizing, rule-building minds into a sense of stability and then hit us with big changes.
p.378 One of the questions Edith Penrose asked in her Theory of the Growth of the Firm was, what,
if any, are the fundamental constraints on firm size and growth? She identified two. The first is the ability
to manage complexity... The second constraint Penrose identified was knowledge.
A firm can only grow as fast as its knowledge. And, since knowledge is the product of evolutionary processes, we can say that
a firm can only grow as fast as its evolutionary processes allow it to grow. [JLJ - it seems the same constraints apply to
the ultimate strength of a machine playing a game.]
p.410 In evolutionary systems, profitability is not an objective in and of itself; rather,
it is a fundamental constraint that must be met if a business is to achieve the objective of
survival.
p.414 In a competitive evolutionary environment, "endure and grow" is the what,
and "adapt and execute" is the how. Enduring and growing are the timeless demands placed on designs in an
evolutionary system.
p.428 The common thread running through these examples is that micro-level behavior matters.
As we have discussed, in complex adaptive systems the rules of individual agent behavior often have profound and sometimes
unexpected effects on the macro performance of a system... Traditional Economics has historically taken a narrow
view of micro-level behavior - if everyone is assumed to be perfectly rational, then it makes no sense to explore how heterogeneous
patterns of individual behavior affect macro-level outcomes.
p.453 As mentioned before, the environment is a complex adaptive system itself, and the potential
for tipping points, radical change, and even collapse are very real.
