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Applied Big History
A Guide for Entrepreneurs, Investors,
and Other Living Things
William Grassie
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© 2018 William Grassie
All rights reserved.
ISBN-13: 978-1719853071
ISBN-10: 171985307X
Version 1.2
Please send corrections, comments, and feedback to
grassie@metanexus.net
Metanexus Imprints
New York, NY
Cover&Photo&Credit:&NASA$Earth$Observatory$images$by$Joshua$Stevens,$
using$Suomi$NPP$VIIRS$data$from$Mi guel$Román,$NASA's$Goddard$Space$Flight$
Center$
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Table of Contents
Table of Contents!..............................................................................!i!
Foreword by Mitch Julis!...............................................................!iv!
Chapter 1: Thriving in a Complex World!...............................!1!
Outperforming the Market .................................................. 3
Caveat Emptor .................................................................... 5
Applied Big History ............................................................ 8
Wikipedia ......................................................................... 10
Chapter 2: The Great Matrix of Being!..................................!13!
Size ................................................................................... 14
Time ................................................................................. 16
Matter ............................................................................... 18
Energetics ......................................................................... 19
Electromagnetism ............................................................. 23
Sound ............................................................................... 25
Information-Ingenuity ....................................................... 25
Sentience-Consciousness .................................................. 30
Culturally Constructed Hierarchies ................................... 31
Emergent Complexity ....................................................... 32
A Multi-Dimensional Matrix ............................................. 35
Chapter 3: The Economy of a Single Cell!.............................!39!
The Central Bank of Chemistry ......................................... 40
The Currency of Life ........................................................ 44
The Business Models of Life ............................................. 45
The First Agricultural Revolution ..................................... 47
The First Industrial Revolution ......................................... 48
The Whole Economy of Nature ......................................... 51
Chapter 4: Complexity Economics!..........................................!53!
“All Hell Broke Loose” ..................................................... 53
Big Money ........................................................................ 59
Short- and Long-Term Oscillations ................................... 63
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Productivity Growth ......................................................... 67
Scaling Effects .................................................................. 69
Complex Adaptive Systems .............................................. 71
Complicated and Complex Systems .................................. 73
Fluid Dynamics of Markets ............................................... 75
Natural and Economic Selection ....................................... 77
Chapter 5: Death and Taxes!.....................................................!83!
Energy Density Flow ........................................................ 85
Goldilocks Gradients ........................................................ 88
Creative Destruction ......................................................... 89
Energy Regimes................................................................ 90
Instability and Resilience .................................................. 93
Chapter 6: Your Hunter-Gatherer Brain!.............................!95!
A Really Great Ape .......................................................... 96
The Great Cooperators ...................................................... 98
What We Don’t Know .................................................... 100
Survival .......................................................................... 100
Reproduction .................................................................. 104
Sex-Gender Differences .................................................. 110
The Cognitive Revolution ............................................... 113
Stone-Age Brains ............................................................ 116
Divided Self.................................................................... 118
System 1 and System 2 ................................................... 121
Luck of the Genes ........................................................... 125
Our Inner Demons .......................................................... 127
Our Better Angels ........................................................... 128
Natural Values, Natural Morality .................................... 130
Caveats and Cautions ...................................................... 133
Chapter 7: The Big Lollapalooza!..........................................!137!
Welcome to the Anthropocene ........................................ 137
The Secret of Our Success .............................................. 141
Collective Learning ........................................................ 142
Network Effects .............................................................. 144
Imaginary Worlds and Artificial Instincts ....................... 145
Energy Capture ............................................................... 147
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Information-Ingenuity Capture ........................................ 149
Gene-Culture Coevolution of Collective Brains .............. 152
Chapter 8: Existential Challenges!........................................!155!
Anthropogenic Existential Challenges: ............................ 155
Natural Existential Challenges: ....................................... 155
Peak Humanity ............................................................... 156
Climates Change ............................................................. 159
Useless Arithmetic .......................................................... 162
The Next Leap in Energy-Matter-Ingenuity ..................... 169
Chapter 9: The Bottom Line!..................................................!173!
Creating and Capturing Value ......................................... 174
Parasites or Symbionts .................................................... 175
Species of Specialization................................................. 177
Little Bets, Big Wins....................................................... 178
Picking Winners ............................................................. 179
Diversification ................................................................ 181
The Alphas and the Rest of Us ........................................ 183
Teams Work ................................................................... 185
Inventing the Future ........................................................ 186
Bad Things Happen to Good Investors ............................ 190
Disaster Preparedness ..................................................... 191
Investing in Values ......................................................... 192
Fundamental Values........................................................ 193
Impact Investing ............................................................. 194
Creating a Little Big History ........................................... 195
Our Big Future ................................................................ 196
The Bottom Line ............................................................. 197
Acknowledgments!.......................................................................!199!
About the Author!........................................................................!203!
Bibliography!.................................................................................!205!
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Chapter 8:
Existential Challenges
In spite of the stellar rise of our species, many existential challenges
face us in the future. We have a lot of potential catastrophes to
consider—both anthropogenic and nonanthropogenic challenges to our
future prospects.
Anthropogenic Existential Challenges:
• weapons of mass destruction
• rising greenhouse gases
• runaway artificial technology
• biotech run amok
• self-replicating nanotechnology
• cyber insecurity
• pandemics
• social anarchy
• overpopulation
• mineral depletion
• collapse of global economic markets.
Natural Existential Challenges:
• sun flares
• impact events
• supervolcanos
• mega-earthquakes
• massive tsunamis
• evolved pathogens
• Earth wobbles
• changing climates.
Like the White Queen in Lewis Carroll’s Through the Looking
Glass, I find it useful to imagine these “impossibilities” a little bit each
day. “When I was younger I always did it for a half an hour a day,” the
Queen tells Alice. “Why sometimes I believed as many as six
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impossible things before breakfast.”
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It is not bad to think of
impossibly dark possibilities. Contemplating one’s own death, or the
death of billions, feels impossible, even though it is a certainty from the
day of our birth. Reflecting on death is an important spiritual practice in
many different traditions—one that investors should also remember. A
little bit each day is a way to focus life on really important matters.
Taking the White Queen’s lead, I try to do my imaginings before
breakfast, so I can spend the rest of my day focusing on the positive
things in the world. So many disasters to contemplate! In the next two
sections I offer contrarian considerations of the prospects of climate
change and human population growth.
Peak Humanity
I was born in 1957. Eisenhower was president. The Soviet Union
launched Sputnik. The Cold War was heating up, even as McCarthyism
literally died out. Science and technology were all the rage. Leonard
Bernstein’s West Side Story debuted on Broadway. Leave It to Beaver,
with its vision of the ideal American family, premiered on television.
There were 2.8 billion people alive in 1957 and 172 million of
them were Americans. In 2011 demographers figure that the world’s
population reached 7 billion. There are two and a half times more
people alive on the planet now than in 1957. Here in the United States,
the population is now at 326 million.
At the beginning of the Common Era (C.E.), the number of
humans living on this planet was about 130 million, distributed across
the globe. Rome and Xi’an would have been the largest cities in the
world, each with an estimated population of 400,000.
It would not be until 1800 that the world population reached 1
billion. In 1930 we reached 2 billion. Today we are at 7.3 billion. The
largest city today is Tokyo, with 32 million inhabitants. Seoul, Mexico
City, and New York vie for the next largest with around 20 million
each. These numbers, and the sciences and societies behind them, are
profoundly important to understanding the trajectory of humanity on its
recent unprecedented growth spurt. It is important to know in some
detail how we got here and what scenarios might lie in store for the
planet and its people over the next hundred years.
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Lewis Carroll, Through th e Looking Glass (Project Gutenberg, 1871).
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Population growth is a factor of three trends: birth rates, life
expectancy, and the mortality or death rate. Global fertility rates have
dropped from 5 or more children per woman post–World War II to 2.5
children per woman today. At the same time, life expectancy at birth
has gone up and mortality rates have gone down. This is great news.
Fewer children are born, they are less likely to die in childhood, and we
tend to live longer lives.
The surge in human population in the last century is primarily the
result of three factors:
1. Sanitation and civil engineering, the unsung heroes of public
health, from which we derive clean drinking water and safe
sewage disposal;
2. Modern medicine, particularly vaccinations, through which we
have dramatically reduced occurrences of communicable
diseases;
3. Increased agricultural production through the use of hybrid
crops, petrochemicals, irrigation, and industrialization at
economies of scale in a now global food market.
Since the 1950s, life expectancy at birth around the world
increased from about 47 years to 68 years. In North America, life
expectancy is now about 78 years. Mortality rates are closely related to
life expectancy, but significantly different in how they impact age
distributions and growth within a population. How long you linger on
this planet, when and how you die—for instance, before or after
reproduction—all end up impacting population growth. Infant mortality
is more significant in demography than old-age mortality.
Longer-living humans and declining fertility rates are creating
challenging demographic and economic issues, such as increased
pension payouts, skyrocketing health care costs, and a smaller labor
force to support the elderly. Of course, at some point, mortality rates
are 100 percent.
Demographers develop prediction models based on these factors,
noting also the distribution of age groups within a population. Most
models predict that the world population will peak at around 9 to 10
billion by 2050. From 7 billion to 9 billion people doesn’t seem like a
big deal, but what it means in the larger context of Big History is that
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humanity must grow as much food over the next 40 years to feed itself
as it has grown over the last 10,000 years since the rise of agriculture.
Presumably we will have to do so with less waste, less water, fewer
petrochemicals, less nitrogen, and less soil erosion.
Population growth, however, is uneven. Seventy percent of the
population growth in the next forty years is predicted to take place in
extremely poor countries, while many of the rich countries are now
stable or in demographic decline. In economics, a growing population
also tends to grow the economy, as it requires more economic activity.
And more people are also seen as a resource to spur growth. More
humans provide more labor, more productivity, more consumption, and
more creativity. Human population growth is thus an engine of
economic growth, not simply an economic burden.
Decreasing birth rates have huge implications for economic
growth and environmental well-being. Education, health care, family
planning, urbanization, and, especially, increased opportunities for
adolescent girls and women are all highly correlated with lower
fertility. Families are desiring and deciding to have fewer children, and
they now have the means and know-how to make those decisions. If
fertility rates drop from 2.5 today down to 1.6 in the near future, then
peak humanity will occur around 8 billion by 2025 and will actually
decrease to 5 billion by 2100. Exponential patterns work going up and
could also work coming down.
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Environmentalists might applaud such a scenario—a planet with 2
billion fewer people than today at the turn of the next century —as it
seems like fewer people would relieve some of the pressure on the
planet’s ecosystems. Indeed, one of the ways to increase energy density
flow is to decrease the mass of the system, i.e., the mass of humans on
the planet.
The economic consequences of such a population decline,
however, could be catastrophic in the short term. It is not clear that we
can have economic growth with a declining population. If economies
don’t grow, then paying off debt becomes an exponential burden,
unleashing a downward economic spiral. Peak humanity may involve a
difficult economic and demographic deleveraging that will span an
entire generation.
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United Nations, "World Population Prospects: The 2012 Revisions," (New York: UN
Department of Economic and Social Affairs, 2012); Leslie Roberts, "9 Billion?," Science 333, no.
6042 (2011).
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The collapse of our global economy is, counterintuitively, also
likely to be devastating for our global environment, as desperate people
aren’t likely to care much about protecting the planet. And economic
factors also help drive the decisions of families to have fewer children.
It seems that we are in a triple-bind between containing population
growth, protecting the environment, and growing economies.
The prospect of declining fertility also raises evolutionary
concerns about the future of humanity on a soon-to-be child-scarce
planet. Children are literally the future of our species. Children
humanize us. They inspire adults to be nurturing and future oriented.
We need a planet with fewer children in a world that invests more in
those few children, even though they may be someone else’s children.
Fostering that kind of altruism and long-term commitment
unfortunately runs contrary to our tribal instincts and hunter-gatherer
mentality.
At some point, human population on Earth will peak, for as
Darwin observed, any exponential growth curve within a finite space
cannot continue forever, for “the world cannot hold them all.” It may
happen sooner than we anticipate, perhaps later. It may plateau for a
while or it may start to decline and rise again. The future history will
involve rates of births, deaths, and lives lived at rates, ranges, and
intensities that we cannot know in advance. Flat and declining
populations, however, are already having an economic impact on a
number of countries.
Climates Change
Climate changing is hardly front-page news for geologists. It is the
whole story from beginning to end. Geologists read this story from the
text of rock, mud, water, ice, and air, in the half-lives of radioactive
isotopes, in the orientation of magnetic sediments, in geological
deposits, and in the traces of ancient glaciers, mountain ranges,
canyons, craters, fossils, bygone oceans, and tectonic plates. The 4.5-
billion-year-old-Earth story is one of continuous and dramatic
metamorphoses on a time scale difficult to imagine, unless, of course,
you happen be a geologist. We are the first generation to know this
about our past and future planet.
These dynamics and others have been at work on the earth since
its beginning. The Earth wobbles on its axis. The planet is ever so
slightly out of kilter. The wobbles have a periodicity, known as the
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Milankovitch Cycle. This is why ice ages come and go with irregular
regularity. As ice ages advance, enormous glaciers extend down from
the poles and suck up the oceans of our planet, turning them into mile-
deep rivers of moving ice that sculpt the contours of continents. As the
ice ages recede, the land rises and melting water refills our planetary
bathtubs. Since the last glacial maximum some 20,000 years ago, ocean
levels have risen some 160 meters to today’s levels. A grassroots
movement to “stop Earth wobbles” is not likely to succeed, no matter
how sincerely felt.
Under the weight of the ice sheets and oceans, the Earth’s crust
bends and buckles, rises and falls. Variations in the volume of liquid
water on the Earth are eustatic changes, i.e., depending on the
distribution of glaciated ice, atmospheric water, ocean water, and
geologically bounded water captured in aquifers, lakes, soil, and rock.
The shape of the ocean floor and land mass, however, can also
dramatically affect sea levels. These isostatic changes (i.e., changes in
shape of the Earth’s crust) in sea levels are caused by changes in the
contours of Earth’s ocean basin and continents, which can increase or
decrease the volume of the global bathtub and the height of the land
mass. When the ocean basin is smaller, global sea levels rise
everywhere. The ocean cup runneth over onto all of the continents. Or,
as the case may be in the reverse, sea levels can also drop dramatically
depending on the shape of the ocean floor, as the Earth’s crust warps,
cracks, and bends.
Our sun, too, is dynamic, sometimes overly exuberant in bathing
the Earth with excess solar energy, and sometimes providing too little.
Solar flares present a special challenge to our technologically advanced
civilization, as the electromagnetic pulse from a major solar flare
hitting Earth has the capacity to destroy much of the electronic
infrastructure upon which our civilization now depends.
A single supervolcano can ruin your whole day, dumping volcanic
ash meters deep over entire continents, causing widespread earthquakes
and tsunamis and mucking up the upper atmosphere so as to create a
“nuclear winter,” and possibly a runaway feedback loop giving rise to
an instant ice age. Our common ancestors survived just such a
catastrophe 74,000 years ago, when Mount Toba, a supervolcano in
Sumatra, exploded. By this time in our wanderings out-of-Africa, our
ancestors had followed the coastlines along the Middle East and South
Asia, settling as far as Southeast Asia and Australia. The supervolcano
changed everything overnight for our ancestors. It dumped six meters
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of volcanic ash over much of South Asia. The massive eruption also
brought on an instant ice age. Humanity was reduced to a mere 10,000
individuals, a story written in our mitochondrial DNA. And yet, we,
and the other flora and fauna, survived. And as the sky cleared and ice
slowly retreated over millennia, we resumed our migrations and
expansions.
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The Earth has experienced large impact events throughout its
history. Large asteroids and comets occasionally smash into the Earth.
A major impact event can set lose earthquakes, volcanic eruptions,
tsunamis, and the onset of an instant ice age. We may soon have the
technological means to detect and deflect large impact events, but we
are not going to stop platetectonics, supervolcanos, solar flares, and
Earth-wobbles. The Holocene—the 10,000 years since the last ice
age—will not last forever. Indeed, it may already be over.
On the one hand, significant climate change will be a disaster of
unimaginable magnitude for most humans. On the other hand, of all the
large mammals, humans are most likely to survive future climatic
disasters. Much of the flora and fauna may require our help to survive
and thrive on the other side of catastrophe. What should concern us
most about future evolutionary bottlenecks is the information-ingenuity
that may be lost—what we have accomplished in 10,000 years of
human civilization—and how it will be passed on through the eye of an
evolutionary needle. Humans need a lot more than just our genes to
survive and thrive on the other side of future catastrophes. I maintain
that constructing a resilient global civilization that can bounce back
from geological disasters will also significantly reduce fossil fuel
consumption. The larger perspective offered here supports efforts to
reduce the impact of anthropogenic climate change without framing the
political conflict as an eco-apocalyptic battle between forces of light
and darkness.
All rock is ultimately metamorphic rock. This includes the
concrete, steel, and glass monuments of human engineering and
architecture built in cities around the world. I often imagine my
beloved New York City, and every other city at some point in the
future, crushed under mile-thick glacier ice, someday under the ocean
again, or perhaps absorbed back into the molten core of the Earth
through normal plate tectonics. A geologist knows that it is only a
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Stanley H. Ambrose, "Volcan ic Winter, and Differentiation of Modern Humans. Bradshaw
Foundation. ," Bradshaw Foundation, http ://www.b radsh awfoundation.com/stanley_ambrose.php.
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matter of time—hot or cold, fast or slow, sea levels up or down, round
and round the Sun we go—before there are dramatic changes on our
restless and exuberant planet. Maybe this will happen soon, maybe
suddenly, and maybe not for a long, long time, at least relative to the
scale of human life, but it will happen, if the past is any guide.
Life, as we learned, also changes climates, most dramatically in
the Great Oxidation Event. The rise of photosynthesizing microbes 2
billion years ago resulted in an increase in atmospheric oxygen, causing
a “snowball” Earth. Life also gave rise to the formation of large
hydrocarbon deposits hundreds of millions of years ago, which we have
been digging up and burning over the last two centuries to fuel
humanity’s exponential growth spurt. The result is increased levels of
carbon dioxide, methane, and nitrous oxide in the atmosphere, which
have increased the heat-retention properties of the Earth system and
caused an international political uproar over the dangers of human-
caused climate change.
Again, we are the first generation to know this about our past and
future planet. Most of the details were discovered only over the last
fifty years by scientists working in diverse disciplines. Perhaps our
panic about anthropogenic climate change can be understood as a way
of denying and channeling this larger and more unsettling truth. We
delude ourselves into thinking that by merely reducing the emission of
greenhouse gases, we can control our restless planet. The new geology
is simply too frightening to face head on. Climates do change. We
don’t know when it will happen, only that it will. Sooner or later, fast
or slow, hot or cold, wet or dry, this card will eventually be dealt, again
and again throughout our big future.
Useless Arithmetic
The sciences of modeling and predicting climate change provide
an important case study in the challenges of making economic models
and predictions. It turns out that we are not very good at predicting or
managing environmental changes. The problems are endemic to all
modeling of complex natural and human systems, including economic
markets. Predictions from any computer simulations of any complex
reiterative dynamic processes are constrained by unknown parameters
and the chaotic properties of the evolving systems.
In their book Useless Arithmetic: Why Environmental Scientists
Can’t Predict the Future, Orrin H. Pilkey and Linda Pilkey Jarvis
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discuss the limits of climate change models. There are about fifteen
major climate change models used by scientists around the world today.
Favored are bottom-up models, involving a long chain of events and
very complicated computer simulations with enormous data inputs run
on supercomputers. This approach uses a great aggregation of models,
and models of models, all the way up. In other words, it is also models
all the way down. The assumption here is that the more variables
included in the meta-model, the better the meta-model. Another
approach, the minority view, favors top-down models, which focus only
on larger systems and simplify, average, estimate, and test, but do not
presume to include every potentially relevant variable at greater
resolution with ever more detail. Economists, investors, and other
living things, take note—our global economy also defies accurate and
quantitative prediction because of its complexity.
In the case of climate change, a short list of variables and feedback
loops might include the following:
§ the absorption of CO2 by the ocean (resulting in ocean
acidification)
§ the heat exchange between the oceans and the atmosphere
§ the effect of cloud cover
§ other variations in the Earth’s albedo
§ ocean current circulation
§ local climate perturbations
§ arctic ice melt
§ release of methane from melting arctic tundra
§ health of phyloplankton
§ variations in amounts and types of precipitation
§ variable rates of carbon absorption by plants
§ long-term climate cycles.
Any of these variables could accentuate or ameliorate climate
change and could do so with runaway dynamics. Personally, I lean
agnostic to pessimistic on the prospects for near-term climate change
resulting from anthropogenic causes. It may not be all that bad. It may
even be worse than we imagine. It may already be too late. We have no
way of knowing, in spite of the many billions of dollars invested in the
climate change prediction industry. Whether sea levels go up or down,
the Pilkeys warn:
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What a daunting task faces those who choose to predict the futures
of the sea-level rise! We have seen that the factors affecting the
rate are numerous and not well understood. Even if our
understanding improves, the global system simply defies accurate
and quantitative prediction because of its complexity . . .
Assumption upon assumption, uncertainty upon uncertainty, and
simplification upon simplification are combined to give an
ultimate and inevitably shaky answer, which is then scaled up
beyond the persistence time to make long-term predictions of the
future of sea-level rise. Aside from the frailty of the assumptions,
there remains ordering complexity: the lack of understanding of
the timing and intensity of each variable.
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The American Petroleum Institute, however, should take no
pleasure over these limitations to the global climate-change prediction
industry and the impassioned advocates for reducing fossil fuel
consumption. Anthropogenic climate change is a real concern. And,
furthermore, the same types of modeling errors and known unknowns
presumably also call into question industry models of global petroleum
reserves and the future value of those reserves.
No matter how much data is collected or how sophisticated the
computer program, science cannot deterministically model and predict
complex dynamic systems. Long-term predictions about the Earth’s
climate are about as useful as long-term predictions of economic
markets. There are too many variables, too many feedback loops
between variables, and the system is dynamic in ways that we do not
understand and cannot fully represent through mathematics. Investors
should already understand this merely by reading the history of
economics and finance.
The Pilkeys advocate a qualitative methodology that merely seeks
to predict tendencies, directions, and magnitudes of possible changes.
A supercomputer simulation is not required to document actual glacial
declines around the world over the last few decades. Before-and-after
photographs of Muir Lake, Alaska, from the 1940s and today provide
compelling evidence for major changes. Several decades of space
telemetry and ground observations in the Antarctic reveal disturbing
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Orrin H. Pilkey and Linda Plkey-Jarvis, Useless Arithmetic: Why Environmental Scientists
Can't Predict the Future (New York: Columbia University Press, 2007), 82.
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short-term trends. Over a three-year period, the West Antarctic Ice
Sheet lost 36 cubic miles of ice per year. The complete melting of the
West Antarctic Ice Sheet alone would produce a 13-foot global eustatic
rise in sea level, perhaps accompanied by isostatic changes in the
contours of the ocean basins that could accentuate or mitigate the
impact.
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Of course, many things can be predicted with a great deal of
accuracy. On March 20, 2019, the sun will rise in New York City at
7:00 a.m. and set at 7:08 p.m. And on that day, the sun will reach an
altitude of 49.2 degrees above the horizon. The sun will be at a distance
of 92,570,000 miles from Earth. Also on March 20, 2019, we can
accurately predict a full moon rising at 7:04 p.m., setting at 6:49 a.m.,
at a distance of 223,395 miles from Earth.
It is comforting that many things can be known with certainty.
Regularity and reproducibility have traditionally been seen as
hallmarks of science. I count on it every time I log into this computer,
get on an airplane, or take an elevator to the eighth floor. Predictive
success is thought to be the sine qua non in most science, technology,
and engineering fields. In some domains, however, science is going to
need to let go of prediction and certainty.
Two things have changed in the recent past that now affect how
we approach prediction and certainty:
1. the rise of complexity and
2. the rise of computation.
Environmental and human processes, including economic markets,
have always been complex. This is not new. It is just that now we have
a lot more insights and background information. We know a lot more of
the details, so we are compelled by the known facts at every turn to ask
more and more complex questions. This is true in many disciplines,
including economics and finance.
The complexity challenge also arises because of the availability of
the computer. Every scientific discipline has been dramatically changed
over the last forty years by the growing power and availability of
computers. Scientists, like investors, can now collect and query
enormous data sets and run computer simulations. Without computers,
there would be an epistemic bias toward asking simpler questions and
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Ibid., 78.
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ignoring questions that were thought to be beyond the capabilities of
science. Today, science is bumping up against horizons of complexity
and chaos that may be, in principle, beyond reduction and prediction.
Whether we are forecasting economic markets or climate change,
we need to be aware of how the models employed can distort our
understanding of reality. There are two sources of this distortion—
human frailty and finitude, on the one hand, and the nature of complex
and chaotic systems, on the other hand.
The human factors include all of the cognitive biases of our
hunter-gatherer brains—the System 1 heuristics—along with any
number of technical mistakes, uncertain quality assurance, and
debugging challenges that creep into the coding of complex algorithms.
Moreover, algorithms have agendas— algorithmic biases based on
important assumptions, pessimist and optimist biases, and political
advocacy biases.
These human frailties are then compounded and confounded by
the very nature of complex adaptive systems. We may understand how
complexity and chaos function, but not in a way that allows for useful
prediction. Complexity errors result from the nature of complexity
itself, not frailty or lack of acuity on the part of the researchers. Our
models necessarily make assumptions about partially known and
unknown relationships, expressed in the ordering of variables with
different valences, intensities, and vectors. Mitigating and reinforcing
feedbacks are built into the models. No matter how large the data
sets—the size of the data set is normally really important for reliable
research—when it comes to simulating the climate or the economy, it
ends up being models all the way down. What we simulate in the
supercomputers is not nature, but the model itself, often mistaking the
map for the terrain. This is what Alfred North Whitehead labeled “the
fallacy of misplaced concreteness.”
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Every model or simulation must solve two problems. First, what is
the ordering of complexity in the system, the timing and intensity of
different parameters? And second, how does one best represent this
ordering of these parameters and complexities mathematically on a
computer? Algorithms need to be imagined. Relationships defined.
Data collected. Data analyzed. Values assumed. Code written. Models
tested. Simulations run. And all of this—the algorithms, the lines of
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232
Alfred North Whitehead, Science and the Modern World (New York: Free Press, [1925] 1967),
52.
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code, sets of data, computer storage and processing—have all been
growing exponentially over the last four decades. In the end, though,
the computer model is only simulating and testing itself. What is
represented on the computer is not the actual complex natural
phenomenon.
The Pilkeys advocate qualitative modeling, which at best can be
used only to predict general directions of change and possible
magnitudes. Qualitative modeling will not presume to offer a numerical
answer with a range of error. The approach asks why, how, and what if.
Qualitative modeling can also use large data sets, computer
simulations, and lots of useful arithmetic, but they are used to explore
different scenarios, contingencies, and normative relationships. At the
end, there is more humility and uncertainty, multiple scenarios, and no
hard-and-fast predictions. The authors offer the following chart as a
typology of qualitative versus mathematical modeling. Value investors
and other living beings might well apply these insights to every aspect
of their work.
Scenario Planning
Strategic Planning or
Mathematical Modeling
Qualitative input
Quantitative input
Exploits uncertainties
Minimizes uncertainty
Long-range planning
Short-term planning
Multiple answers
Single answer
Planning for the future
Predicting the future
Hypothetical events
Predetermined goals
233
The bad news about complex predictions is that we don’t know
anything with certainty and may never know anything concrete at all—
neither about future climate change, nor about storing radioactive waste
over eons, managing declining fisheries, invasive weed species, or
untangling complex genetic bureaucracies. Science is butting its head
against horizons of complexity that we may not be able to hack. Few
are willing to accept such epistemic limitations. It runs counter to the
very ethos of science. And yet complexity and chaos theories suggest
that certain kinds of problems cannot be solved with bigger data sets,
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233
Pilkey and Plkey-Jarvis, Useless Arithmetic: Why Environmental Scientists Can't Predict the
Future, 200.
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168!
better code, more powerful supercomputers, fewer flawed humans, and
less politicized science.
Complexity is not just more; it is something new. The really
creative processes in the world tend to be complex distributed systems,
not amenable to deterministic modeling This is the greatest challenge
for science today. It is also a challenge to applied ethics, because the
consequences of actions cannot always be known in advance. The
precautionary principle—"do no harm”—must reckon with unknown
and unintended consequences along with the unknown opportunity
costs of doing nothing.
Science produces lots of useful and reliable predictions.
Mathematical modeling works well with simpler systems, like plotting
the motion of the stars and planets in the evening sky or stress-
engineering concrete and steel bridges under variable loads and
conditions. Multiply the variables, however, add a lot of feedback
loops, and grow the complexity of a system and the questions posed,
and suddenly predictive modeling becomes an exercise in futility.
Predictive modeling cannot yield valid predictions for any complex
natural and human-related processes. The story is about approaching
limits to science in the domain of the complex.
A conclusion to be drawn is that humanity is now thrust willy-
nilly into the role of managing the Earth, even though we don’t really
know what we are doing. Humans will never have the complete know-
how, even though we certainly have increased our can-do. Humans
have themselves become an important variable in the planetary
evolution of the planet. In his environmental history of the twentieth
century, J. R. McNeill reflects on our dilemma.
The human race, without intending anything of the sort, has
undertaken a gigantic uncontrolled experiment on the earth. In
time, I think, this will appear as the most important aspect of
twentieth-century history, more so than World War II, the
communist enterprise, the rise of mass literacy, the spread of
democracy, or the growing emancipation of women.
234
This uncertainty does not relieve us of the responsibilities and
risks of taking action. We must and will make choices. We have to
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234
J.Robert McNeill, Something New under the Sun: An Environmental History of the Twentieth-
Century World (New York: W.W. Norton & Company, 2000).
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imagine and seek desirable outcomes. Let us try to model, design, and
build for sustainable and resilient futures. We have the possibility of
anticipatory adaptation, if we begin to think in terms of Big History and
the big challenges that we face.
How should governments, business, and citizens respond to the
real and perceived threat of global climate change? Perhaps the
question is as perplexing as asking how one would plan for and respond
to a dramatic nonanthropogenic climate change.
For my part, we need to deemphasize anthropogenic climate
change and look at other variables. There are many compelling
arguments for radically increasing efficiencies and reducing fossil fuel
consumptions. These reasons do not depend on prognostications of
climate models. Reducing fossil fuel consumption improves local
environmental air and water quality. It increases health, safety, and
quality of life. It slows resource depletion. Reducing fossil fuel
consumption improves the bottom line for individuals, corporations,
and entire economies. There are also important national security
interests in reducing fossil fuel imports. We don’t need a global climate
change scare in order to justify, rationalize, or motivate what should
already be obvious and sound public and private policy. It is in the best
interest of the United States and the world to dramatically reduce fossil
fuel consumption, especially through increased efficiency, while also
developing alternative energy sources. As discussed, the prime
directive of evolution is to minimize entropy while maximizing
creativity.
Remember that humans are being asked to make major political
and economic decisions in response to the perceived and presumably
real threat of anthropogenic climate change. And that is just the tip of
the iceberg, so to speak, of the many and varied complex ways that
humans and nature interact. We need to accept that things will not stay
the same, that the world will change in dramatic and unpredictable
ways. These transformations, for good and for bad, may make sense in
hindsight, but could not have otherwise been predicted. This is true of
evolution, climate change, the movements of economic markets, and
the odyssey of an individual life lived.
The Next Leap in Energy-Matter-Ingenuity
Based on the observed pattern in biological evolution and in
cultural evolution, we can hypothesize a new energetic leap in human-
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170!
generated energy density flows. This will be accomplished in part by a
reduction in human population, by new efficiencies in generating and
using energy, and by new technologies that will allow humans to more
directly harvest solar energy. We can extrapolate that this will be
accompanied by a commensurate jump in information-ingenuity
density flows. We already have intimations of the next big lollapalooza,
though not enough to pick winners and losers in the transformations
ahead.
In the end, humans must do what all life does so exquisitely. We
must innovate to capture energy-matter flows for the construction of
greater complexity. The critical inputs to economic growth are energy,
matter, and ingenuity. The task of investors and other living things is to
capture a tiny slice of that flow and, in so doing, to act as membrane-
like allocators of resources among organelles in a vast global exchange
system.
Humans now consume at a rate of 18 trillion watts of energy in a
variety of forms—fossil fuels (coal, oil, gas), hydropower, nuclear
power, renewables (solar, wind, biomass, biofuels, and geothermal),
and, of course, the food that the 7.3 billion of us eat. Without energy
constantly running through the arteries of our global civilization, the
world would collapse. Our cities, industries, transportation,
agriculture—indeed, every aspect of our contemporary lives—depend
on this tremendous flow of energy.
In order to meet the demands of a still-growing population and the
desperate needs of the energy poor, the world will need to increase its
energy production by about 50 percent in the next two decades. Note
that this is most easily and economically accomplished through
increased efficiency and not through increased production.
235
Emerging
markets—China, India, Brazil, and others—also aspire to achieve much
higher standards of living, comparable to those in the United States and
Europe. All of this increased demand occurs alongside of concerns
about anthropogenic climate change caused primarily by the burning of
fossil fuels.
It may be that greater energy efficiency has survival value at
different stages of our cosmic story and that we should start measuring
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235
Eric D. Beinhocker and Jeremy Oppenheim, "Economic Opportunities in a Low-Carbon
World," McKinsey & Company,
http://www.mckinsey.com/client_service/sustainability/latest_thinking/economic_opportunities_in
_a_low_carbon_world; IEA, "Energy Efficiency Market Report 2014," (Paris, France:
International Energy Agency, 2014)..
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those efficiencies in terms of energy density flows. Few of us think
about energy flows in our daily lives. We drive to the supermarket to
buy our groceries that we store in a refrigerator and cook on the stove.
Calculating the flow of energy in our morning breakfast, including
multiple conversions of energy from one form to another along the
entire journey from field to supermarket to body, requires a new kind of
scientific literacy and accounting principles.
236
Elegance in evolution is achieved when we do more for less with
the emphasis being on more, smaller, and faster. Productivity growth in
economics is also a more-for-less proposition. Evolution and ecology
have a lot to teach us about how to achieve sustainable economic
growth and a resilient planetary civilization.
Big History offers an interesting vantage point for thinking about
energy policies and solutions for the twenty-first century that can lead
to a healthier, cleaner, smarter, wealthier, and a more creative global
civilization. “Minimize entropy, maximize creativity” is the new
ethical, aesthetic, and pragmatic first principle, evolution’s prime
directive.
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Smil, Energy in Nature and Society.