Transcript Document

Adapting to the Future:
The Impact of Accelerating Change
Challenges for World Security Policy
John Smart
USAWC, August 2004, Carlisle, PA
Los Angeles
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© 2004 Accelerating.org
Systems Theory
Systems Theorists Make Things Simple
(sometimes too simple!)
"Everything should be made as simple as possible, but not simpler."
— Albert Einstein
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© 2004 Accelerating.org
Institute for the Study of
Accelerating Change
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
ISAC (Accelerating.org) is a nonprofit community of scientists,
technologists, entrepreneurs, administrators, educators,
analysts, humanists, and systems theorists discussing and
dissecting accelerating change.

We practice “developmental future studies,” that is, we seek to
discover a set of persistent factors, stable trends, convergent
capacities, and highly probable scenarios for our common future,
and to use this information now to improve our daily evolutionary
choices.

Specifically, these include accelerating intelligence, immunity,
and interdependence in our global sociotechnological systems,
increasing technological autonomy, and the increasing intimacy
of the human-machine, physical-digital interface.
© 2004 Accelerating.org
Intro to Future Studies
Four Types of Future Studies
–
–
–
–
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Exploratory (Speculative Literature, Art)
Agenda-Driven (Institutional, Strategic Plans)
Consensus-Driven (Political, Trade Organizations)
Research-Predictive (Stable Developmental Trends)

The last is the critical one for acceleration studies and
singularity studies

It is also the only one generating falsifiable hypotheses

Accelerating and increasingly efficient, autonomous,
miniaturized, and localized computation is apparently a
fundamental meta-stable universal developmental trend.
Or not. That is a key hypothesis we seek to address.
© 2004 Accelerating.org
Observation 1:
The “Prediction Wall”



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The faster change goes, the shorter-term our average
business plans. Ten-year plans (1950's) have been
replaced with ten-week (quarterly) plans (2000's).
Future appears very contingent, on average.
There is a growing inability of human minds to
imagine some aspects of our future, a time that must
apparently include greater-than-human technological
sophistication and intelligence.
Judith Berman, in "Science Fiction Without the
Future," 2001, notes that even most science fiction
writers have abandoned attempts to portray the
accelerated technological world of fifty years hence.
© 2004 Accelerating.org
Observation 2:
The Prediction Crystal Ball
What does hindsight tell us
about prediction?
The Year 2000 was the
most intensive long range
prediction effort of its time,
done at the height of the
forecasting/ operations
research/ cybernetics/
think tank (RAND) driven/
“instrumental rationality”
era of future studies
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(Kahn & Wiener, 1967).
© 2004 Accelerating.org
Lesson 1: Forecasting in certain domains of
the modern environment is highly predictable
Example: Information and Communication Technologies
Evaluating the predictions of The Year 2000,
technology roadmapper Richard Albright notes:
“Forecasts in computers and communication stood
out as about 80% correct, while forecasts in all other
fields (social, political, etc.) were judged to be
less than 50% correct.”
Why? Here TY2000 used trend extrapolation (simple).
The major ICT change they missed was morphological
(nonsimple) the massive “network transition,” to
decentralized vs. centralized computing.
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Richard Albright, “What can Past Technology Forecasts Tell Us About the Future?”,
Technological Forecasting and Social Change, Jan 2002
© 2004 Accelerating.org
Many Technology-Related Transformations
are Amazingly Predictable
Miniaturization (per linear dimension)
 Price Performance in Computing (Moore’s Law)
 Input-Output, Storage, Bandwidth
 Network Node Density (Poor’s Law)
 Protein Structure Solution (Dickerson’s Law)
 Algorithmic Efficiency (Statistical NLP, etc.)
 Software Performance (6 year doubling)
 Economic Growth (2-4% year, over long spatial scales)

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Thought Question: Is annual economic growth
a function of exponential technological surprise
interfacing with human expectation?
(Remember: Efficient market hypothesis in
Economics would predict zero annual growth)
© 2004 Accelerating.org
Relative Growth Rates are Also
Amazingly Predictable
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Brad DeLong (2003) noted that memory density predictably
outgrows microprocessor density, which predictably outgrows
wired bandwidth, which predictably outgrows wireless.
Expect: 1st: New Storage Apps, 2nd: New Processing Apps, 3rd: New
Communications Apps, 4th: New Wireless Apps
© 2004 Accelerating.org
Some Tech Capacity Growth Rates Are
Independent of Socioeconomic Cycles
There are many natural cycles:
Political-Economic Pendulum,
Boom-Bust, War-Peace…
Ray Kurzweil first noted that a
generalized, century-long Moore’s
Law was unaffected by the U.S.
Great Depression of the 1930’s.
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Conclusion: Human-discovered,
Not human-created complexity here.
Not that many intellectual or physical
resources are required to keep us on
the accelerating developmental
trajectory. (“MEST compression
is a rigged game.”)
Age of Spiritual Machines, 1999
© 2004 Accelerating.org
Lesson 2: Both Social and Developmental
Factors Determine Forecasting Expertise
Professional futurists Joseph Coates, John Mahaffie,
and Andy Hines, a broad literature review, note:
“In reviewing the 54 areas (in science and technology) in which we
gathered forecasts, four clearly stood out as the best: aerospace,
information technology, manufacturing, and robotics.”
They also note:
“In aerospace and information technology, there is widespread
interest and governmental emphasis on forecasts… In other
fields, such as economics and basic mathematics, there is little or
nothing [in forecasting the futures of the field, vs. using the field for
forecasts].
Q: What causes this selective interest?
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Joseph Coates, John Mahaffie, Andy Hines, “Technological Forecasting: 1970-1993”,
Technological Forecasting and Social Change, 1994
© 2004 Accelerating.org
Accelerating Systems Theory
Something Curious Is Going On
Unexplained.
(Don’t look for this in your physics or information theory texts…)
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Brief History of Accelerating Change
Billion
Years Ago
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Generations Ago
12
Big Bang (MEST)
11.5
Milky Way (Atoms)
8
Sun (Energy)
4.5
Earth (Molecules)
3.5
Bacteria (Cell)
2.5
Sponge (Body)
0.7
Clams (Nerves)
0.5
Trilobites (Brains)
0.2
Bees (Swarms)
0.100
Mammals
0.002
Humans, Tools &
Clans Co-evolution
100,000
Speech
750
Agriculture
500
Writing
400
Libraries
40
Universities
24
Printing
16
Accurate Clocks
5
Telephone
4
Radio
3
Television
2
Computer
1
Internet/e-Mail
0
GPS, CD, WDM
© 2004 Accelerating.org
Observation 1:
Tech Interval Time Compression
3 million years ago
collective rock throwing; early stone tools
1.5 million years ago lever, wedge, inclined plane
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500,000 years ago
control of fire
50,000 years ago
bow and arrow; fine tools
5,000 years ago
wheel and axle; sail
500 years ago
printing press with movable type; rifle
50 years ago
commercial digital computers
10 years ago
commercial internet
© 2004 Accelerating.org
Obs. 2: Continuous Tech Innovation (Even
in 400-1400 A.D., Fall of Rome to Black Plague)
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Technological or Sociotechnological Innovation
Date (A.D.), Location
Alchemy (pre-science) develops a wide following
Constantinople University
Powers and Roots (Arybhata)
Heavy plow; horse shoes; practical horse harness
Wooden coffins (Alemanni)
Draw looms (silk weaving)
Decimal reckoning
Canterbury Monastery/University
Book printing
Suan-Ching (Science Encyclopedia)
Originum Etymologiarum Liibri XX (Sci. Encyc.)
First surgical procedures
Water wheel for milling (Medieval energy source)
Stirrup arrives in Europe from China
Early Chemistry (Abu Masa Dshaffar)
410, Europe
425, Turkey
476, India
500, Europe
507, Germany
550, Egypt
595, India
598, England
600, China
619, China
622, Spain
650, India
700, Europe
710, Europe
720, Mid-East
© 2004 Accelerating.org
Continuous Tech Innovation
(400-1400 A.D., Fall of Rome to Black Plague)
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Medicine, Astronomy, Math, Optics, Chemistry
Hanlin Academy
Pictorial Book Printing
Iron and smithing become common; felling ax
Chemistry (Jabir)
Mayan Acropoli (peak)
Algebra (Muhammed al Chwarazmi)
Ptolemaic Astronomy; Soap becomes common
Rotary grindstone to sharpen iron
Paper money
Salerno University
Iron becomes common; Trebuchets
Astrolabe (navigation)
Angkor Thom (city)
New Mathematics and Science (Jahiz, Al-Kindi)
Viking shipbuilding
Paper arrives in Arab world
750, Arab Spain
750, China
765, Japan
770, Europe
782, Mid-East
800, Mexico
810, Persia
828, Europe
834, Europe
845, China
850, Italy
850, Europe
850, Mid-East
860, Cambodia
870, Mid-East
900, Europe
900, Egypt
© 2004 Accelerating.org
Continuous Tech Innovation
(400-1400 A.D., Fall of Rome to Black Plague)
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Salerno Medical School
Linens and woolens
First European bridges
Arithmetical notation brought to Europe by Arabs
1,000 volume encyclopedia
First Mayan and Tiuanaco Civilizations
Horizontal loom
Astrolabe arrives in Europe
Greek medicine arrives in Europe (Constantine)
Water-driven mechanical clock
Antidotarum (2650 medical prescriptions)
Bologna University
Mariner's compass
Town charters granted (protecting commerce)
Al-Idrisi's "Geography"
Oxford University
Vertical sail windmills
900, Italy
942, Flanders
963, England
975, Europe
978, China
1000, Cent./S.America
1000, Europe
1050, Europe
1070, Europe
1090, China
1098, Italy
1119, Italy
1125, Europe
1132, France
1154, Italy
1167, England
1180, Europe
© 2004 Accelerating.org
Continuous Tech Innovation
(400-1400 A.D., Fall of Rome to Black Plague)
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Glass mirrors
Second Mayan Civilization
Cambridge University
Arabic numerals in Europe (Leonardo Fibonacci)
Tiled roofs
Cotton manufacture
Coal mining
Roger Bacon, our first scientist (Opus; Communia)
Goose quill writing pen
The inquisition begins using instruments of torture
Tradesman guilds engage in street fighting over turf
Toll roads
Human dissection
Wood block printing; spectacles
Standardization of distance measures (yard, acre)
Use of gunpowder for firearms (Berthold Schwarz)
Sawmill; wheelbarrow; cannon (large and hand)
1180, England
1190, Cent. America
1200, England
1202, England
1212, England
1225, Spain
1233, England
1250, England
1250, Italy
1252, Spain
1267, England
1269, England
1275, England
1290, Italy
1305, England
1313, Germany
1325, Europe
© 2004 Accelerating.org
Continuous Tech Innovation
(400-1400 A.D., Fall of Rome to Black Plague)
Pisa and Grenoble Universities; Queens College
First scientific weather forecasts (William Merlee)
Mechanical clock reaches Europe
Blast furnaces; cast iron explodes across Europe
Steel crossbow first used in war
Vienna, Hiedelberg, and Cologne Universities
Incorporation of the Fishmonger's Company
Johann Gutenberg, inventor of mass printing, born
1330, Europe
1337, England
1354, France
1360, Europe
1370, Europe
1380, Europe
1384, England
1396, Germany
Lesson: Tech innovation appears to be a developmental process,
independent of Wars, Enlightenments, Reformations, Inquisitions,
Crusades, Subjugations, and other aspects of our cyclic
evolutionary ideological, cultural, and economic history.
Tech advances are something we consistently choose, even
unconsciously, regardless of who is in power, because they have
strong "non-zero sum" effects on human aspirations.
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Many Capacity-Based “Meta-Trends” in
and Thresholds in Tech Acceleration

Moore's Law - Miniaturization
 Processing, Storage, ...
 Price/Performance 2X over 12-18 months

Metcalf's Law - Interconnection
 Economic value of a network increases as the square of
the number of connections

Gilder's Law - Quantization
 Bandwidth increases 3X every 36 months

Negroponte's Law - Digitization
 Superiority of "bits over atoms"
 Profound impact felt in "Knowledge Economy" where
ideas are ultimate raw material

Smith's Law - Simulation
Alvy Ray Smith, Microsoft Research (to Howard Rheingold)
“Reality is 80 million polygons a second.”
 A demand saturation threshold, like CPUs and
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productivity apps (which human-saturated in 1990’s).
 No market saturation until we reach this point © 2004 Accelerating.org
Transistor Doublings (2 years)
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Courtesy of Ray Kurzweil and KurzweilAI.net
© 2004 Accelerating.org
Processor Performance (1.8 years)
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Courtesy of Ray Kurzweil and KurzweilAI.net
© 2004 Accelerating.org
DRAM Miniaturization (5.4 years)
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Courtesy of Ray Kurzweil and KurzweilAI.net
© 2004 Accelerating.org
Many Unexpected Physical Processes are
Moore’s-Related, e.g. Dickerson’s Law
Richard Dickerson,
1978, Cal Tech:
Protein crystal
structure solutions
grow according to
n=exp(0.19y1960)
Dickerson’s law predicted 14,201 solved crystal
structures by 2002. The actual number (in online
Protein Data Bank (PDB)) was 14,250. Just 49 more.
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Macroscopically, the curve has been quite consistent.
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Hans Moravec, Robot, 1999
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Henry Adams, 1909:
The First Singularity Theorist
The final Ethereal
Phase would last
only about four
years, and
thereafter "bring
Thought to the
limit of its
possibilities."
Wild speculation
or computational
reality?
Still too early to
tell, at present.
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© 2004 Accelerating.org
The Technological Singularity:
2nd Order “Envelope of S-Curves”?
Each unique physicalcomputational substrate
appears to have its own Sshaped “capability curve.”
The information inherent in
these substrates is apparently
not made obsolete, but is
instead incorporated into the
developmental architecture of
the next emergent system.
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© 2004 Accelerating.org
Punctuated Equilibrium (in Biology,
Technology, Economics, Politics…)
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
Eldredge and Gould
(Biological Species)

Pareto’s Law (“The 80/20 Rule”)
(income distribution  technology, econ, politics)
Rule of Thumb: 20% Punctuation (Development)
80% Equilibrium (Evolution)
Suggested Reading:
For the 20%: Clay Christiansen, The Innovator's Dilemma
For the 80%: Jason Jennings, Less is More © 2004 Accelerating.org
Saturation: A Biological Lesson
How S Curves Get Old
Resource limits in a niche
Material
Energetic
Spatial
Temporal
Competitive limits in a niche
Intelligence/Info-Processing
Curious Facts:
1. Our special universal structure permits each new computational
substrate to be far more MEST resource-efficient than the last
2. The most complex local systems have no intellectual competition
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Result: No apparent limits to the acceleration of local intelligence,
interdependence, and immunity in new substrates over time.
© 2004 Accelerating.org
P.E. Lesson: Maintaining Equilibrium
is Our 80% Adaptive Strategy
While we gamely try unpredictable evolutionary strategies
to improve our intelligence, interdependence, and
resiliency, these don’t always work. What is certain
is that successful solutions always increase MEST
efficiency, they “do more, better, with less.”
Strategies to capitalize on this:
 Teach efficiency/OR as a civic and business skill.
 Look globally to find most resource-efficient solutions.
 Practice competitive intelligence for MEST-efficiency.
 Build a culture that rewards MEST refinements.
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Examples: Brazil's Urban Bus System, Copied in LA.
Open Source Software. Last year’s mature technologies.
Recycling. 30 million old cell phones in U.S., send to EN’s.
© 2004 Accelerating.org
Saturation Example 1:
Total World Population
Positive
feedback loop:
Agriculture,
Colonial
Expansion,
Economics,
Scientific Method,
Industrialization,
Politics,
Education,
Healthcare,
Information
Technologies, etc.
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© 2004 Accelerating.org
So What Stopped the Growth?
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© 2004 Accelerating.org
Saturation Example 2:
Total World Energy Use
DOE/EIA data shows total world energy use growth rate peaked in
the 1970’s. Real and projected growth is progressively flatter since.
Saturation factors:
1. Major conservation after 1973-74 oil shocks
2. Stunning MEST efficiency of each new
generation of technological system
3. Saturation of human population, and of
human needs for tech transformation
Steve Jurvetson notes (2003) the DOE estimates solid state
lighting (eg. the organic LEDs in today's stoplights) will cut the
world's energy demand for lighting in half over the next 20 years.
Lighting is approximately 20% of energy demand.
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Expect such MEST efficiencies to be multiplied dramatically in
coming years. Technology is becoming more energy-effective in
ways very few of us currently understand.
© 2004 Accelerating.org
End of Fossil Fuels?
Don’t Hold Your Breath
Hydrogen, Solar, and other renewables may well turn out to have
been an unachievable dream, like Nuclear Powered Houses and
20th Century Mars Colonies. Promising on paper but ruthlessly
outcompeted by accelerating MEST efficiencies in older, mature
legacy technologies, like zero emission fossil fuel combustion,
carbon sequestration, nanofiltration (desalination, etc.).
China is pioneering coal liquefaction and nuclear power. China,
Australia, Canada, several others are very coal-rich nations.
Natural gas conversion is now down to $40/barrel.
We have hundreds of years of planetary NG reserves, at least a
thousand years of proven coal reserves, and (theoretically) similar
methane hydrate and deep ocean oil reserves.
Bucky Fuller was right. Energy is so plentiful on Earth it is becoming
steadily less geopolitically important, as the economy “etherealizes”
(virtualizes). Old paradigm.
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© 2004 Accelerating.org
The Theory of
Evolutionary Development
Evolution vs. Development
“The Twin’s Thumbprints”
Consider two identical twins:
Thumbprints
Brain wiring
Evolution drives almost all the unique local patterns.
Development creates the predictable global patterns.
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Understanding Development
Just a few thousand
developmental genes ride
herd over all that molecular
evolutionary chaos.
Yet two genetic twins look, in
many respects, identical.
How is that possible?
They’ve been tuned, cyclically,
for a future-specific
convergent emergent order,
in a stable development
environment.
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Origination of Organismal Form, Müller and Newman, 2003
© 2004 Accelerating.org
Adaptive Radiation/Chaos/
Pseudo-Random Search
Evolution
Multicellularity
Discovered
Complex Environmental Interaction
Cambrian Explosion
Bacteria 
Insects
Invertebrates
Selection/Emergence/
Phase Space Collapse/
MEST Collapse
Development
Vertebrates
570 mya. 35 body plans emerged immediately after. No new body plans since!
Only new brain plans, built on top of the body plans (homeobox gene duplication).
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Body/brain plans: “eukaryotic multicell. evolutionary developmental substrates.”
© 2004 Accelerating.org
Replication, Variation
Natural Selection
Pseudo-Random Search
Evolution
Complex Interaction
Memetic Evolutionary Development
Selection, Convergence
Convergent Selection
MEST Compression
Development
Variations on this ev. dev. model have been proposed for:
Neural arboral pruning to develop brains (Edelman, Neural Darwinism, ‘88)
Neural net connections to see patterns/make original thoughts (UCSD INS)
Neural electrical activity to develop dominant thoughts (mosaics, fighting
for grossly 2D cortical space) (Calvin, The Cerebral Code, 1996)
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Input to a neural network starts with chaos (rapid random signals), then
creates emergent order (time-stable patterns), in both artificial and biological
nets. Validity testing: Hybrid electronic/lobster neuron nets (UCSD INS)
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Replication & Variation
“Natural Selection”
Adaptive Radiation
Chaos, Contingency
Pseudo-Random Search
Strange Attractors
Evolution
Complex Environmental Interaction
The Left and Right Hands of
“Evolutionary Development”
Left Hand
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New Computat’l Phase Space Opening
Selection & Convergence
“Convergent Selection”
Emergence,Global Optima
MEST-Compression
Standard Attractors
Development
Right Hand
Well-Explored Phase Space Optimization
© 2004 Accelerating.org
RVISC Life Cycle of
Evolutionary Development

Replication
Spacetime stable structure, transmissible partially by internal
(DNA) template and partially by external (universal
environmental) template. Templates are more internal with time.

Variation
Ability to encode “requisite variety” of adaptive responses to
environmental challenges, to preserve integrity, create novelty.

Interaction (Complex, Spacetime Bounded)
Early exploration of the phase space favors natural selection, full
exploration (“canalization”) favor developmental selection.

Selection (“Natural/Evolutionary” Selection)
Information-producing, randomized, chaotic attractors.

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Convergence (“Developmental” Selection)
MEST-efficient, optimized, standard attractors.
© 2004 Accelerating.org
Marbles, Landscapes, and Basins
(Complex Systems, Evolution, & Development)
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The marbles (systems) roll around on the landscape, each
taking unpredictable (evolutionary) paths. But the paths
predictably converge (development) on low points (MEST
compression), the “attractors” at the bottom of each basin.
© 2004 Accelerating.org
How Many Eyes Are
Developmentally Optimal?
Evolution tried this experiment.
Development calculated an operational optimum.
Some reptiles (e.g. Xantusia vigilis, certain skinks) still
have a parietal (“pineal”) vestigial third eye.
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© 2004 Accelerating.org
Optimization and MEST Efficiency:
The Promise of Operations Research
Is a Four Wheeled Automobile an Inevitable
Developmental Attractor?
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Examples: Wheel on Earth. Social computation device.
Diffusion proportional to population density and diversity.
© 2004 Accelerating.org
Troodon and the Dinosauroid Hypothesis
Dale Russell, 1982: Anthropoid
forms as a standard attractor.
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A number of small dinosaurs
(raptors and oviraptors) developed
bipedalism, binocular vision,
complex hands with opposable
thumbs, and brain-to-body ratios
equivalent to modern birds. They
were intelligent pack-hunters of
both large and small animals
(including our mammalian
precursors) both diurnally and
nocturnally. They would likely
have become the dominant
planetary species due to their
superior intelligence, hunting, and
manipulation skills without the K-T
event 65 million years ago.
© 2004 Accelerating.org
Why is Upright Posture
Energetically More Efficient?
Observation: The smartest bioorganisms are slow-moving bipeds.
Once a species is culturally computing using behavioral mimicry (and
later, sounds), in high-density living environments, and using mimicry
defenses like collective rock throwing at 80 mph (which requires
opposable thumbs and strong arms), such favored species no longer need
to be fast, thick-skinned, or sharp-taloned.
From this point forward, they can optimize computation by moving more
densely and slowly on average, within their newest phase space for
evolutionary development: mimicry and memetic culture.
Theory: Our once-horizontal backs have only very recently been coaxed
into an almost always upright position, for maximum hand manipulation
ability, hence the "scoliosis curve" of our lower back with its pains.
In the modern world niche, we spend most of our days physically inactive
inside large boxes (now mainly in front of electronic boxes), or moving
between boxes inside smaller wheeled boxes, while our collective
computations flow across the planet at the speed of light.
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The brains of our electronic successors (not their sensors and effectors) will
most certainly be even more immobile still, if the developmental singularity
hypothesis is correct.
© 2004 Accelerating.org
The Challenge in Managing
Technological Development
Since the birth of civilization, humanity has been
learning to build special types of technological systems
that are progressively able to do more for us, in a more
networked and resilient fashion, using less resources
(matter, energy, space, time, human and economic
capital) to deliver any fixed amount of complexity,
productivity, or capability.
We are faced daily with many possible evolutionary
choices in which to invest our precious time, energy, and
resources, but only a few optimal developmental
pathways will clearly "do more, and better, with less."
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© 2004 Accelerating.org
Evolution and Development:
Yin and Yang
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© 2004 Accelerating.org
Evolution and Development:
Two Universal Systems Processes
Evolution
Development
Chance
Randomness
Variety/Many
Possibilities
Uniqueness
Uncertainty
Accident
Bottom-up
Divergent
Differentiation
Necessity
Determinism
Unity/One
Constraints
Sameness
Predictability
Design (self-organized or other)
Top-Down
Convergent
Integration
Each are pairs of a fundamental dichotomy, polar opposites, conflicting
models for understanding universal change. The easy observation is that
both processes have explanatory value in different contexts.
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The deeper question is when, where, and how they interrelate.
© 2004 Accelerating.org
Evo-Devo Provides
Reasons for Polarities
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Evolution
Development
Creativity
Novelty-Seeking
Female
“Right Brain”
Democratic
Freedom
Experimentation
Play
Entropy Creation
“Watch a Movie at 1am”
“Sleep at 1pm”
Discovery
Truth-Seeking
Male
“Left Brain”
Republican
Justice
Optimization
Work
Entropy Density Maximization
“Sleep at 1am”
“Watch a Movie at 1pm”
We each have both of these qualities. Best use always
depends on context. Use them both! Keep the balance!
© 2004 Accelerating.org
Political Polarities:
Generativity vs. Sustainability
Evo-Devo Theory Brings Process Balance to
Political Dialogs on Innovation and Sustainability
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Developmental sustainability without generativity creates
sterility, clonality, overdetermination, adaptive
weakness (e.g., Maoism).
Evolutionary generativity without sustainability creates
chaos, entropy, a degradation that is not natural
recycling (e.g., Anarchocapitalism).
© 2004 Accelerating.org
Human Migration Patterns and
Large Land Mammal Extinctions
Gone:
Bison
Flightless Birds
Elephants
Lions
Marsupial Tigers
Etc.
We depleted the
easiest fuel first.
Everywhere.
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Jared Diamond, The Third Chimpanzee, 1994
 Likely a
computationally
optimal strategy.
© 2004 Accelerating.org
Rise and Fall of Complex Societies

Los Angeles
Palo Alto
Mesopotamia, “Cradle of Civilization” (Modern
Iraq: Assyrians, Babylonians, Sumerians)
6000 BC – 500 BC. Mineral salts from
repeated irrigation, no crop rotation decimated
farming by 2300 BC). Fertile no more.
© 2004 Accelerating.org
Rise and Fall: Nabatea
Petra (Nabateans), 400 BC – 400 CE (Jordan:
trading experts, progressively wood-depleted
overirrigated, and overgrazed (hyrax burrows)
Rock Hyrax
(burrows are
vegetation
time capsules)
Los Angeles
Palo Alto
Jared Diamond, The Third Chimpanzee, 1994
© 2004 Accelerating.org
Rise and Fall: Anasazi
Chaco Canyon and Mesa Verde (Anasazi), 800 – 1200
CE (New Mexico, Colorado: trading, ceremonial, and
industry hubs, wood depleted (100,000 timbers used in
CC pueblos!), soil depleted (Chaco and Mesa Verde).
No crop rotation. Unsupportable pop. for the agrotech.
Pueblo Bonito, Chaco Canyon, NM
Los Angeles
Palo Alto
Cliff Palace, Mesa Verde, CO
© 2004 Accelerating.org
Dominant Empire Progression-Combustion
(Phase I: Near East-to-West)
Hellennistic (Alexander)
Egyptian (New Kingdom)
Babylonian
Spanish
Austria
Germany
British
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Palo Alto
Roman
French
© 2004 Accelerating.org
Dominant Empire Progression-Combustion
(Phase II: West-to-Far East)
Japan
(Temporary: Pop density,
Few youth, no resources.
East Asian Tigers
(Taiwan
Hong Kong
South Korea
Singapore)
American
India
China
Los Angeles
Palo Alto
Expect a Singapore-style “Autocratic Capitalist”
transition. Population control, plentiful resources,
stunning growth rate, drive, and intellectual capital.
U.S. science fairs: 50,000 high school kids/year.
Chinese science fairs: 6,000,000 kids/year. For now.
BHR-1, 2002
© 2004 Accelerating.org
Subtle Lessons:
Life Cycles of Dominant Cultures
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Each culture burns through its resource base (wood, farmland,
population, natural resources) as fast as it can, creating as much
innovation as it can.
Even civilizations go through growth, maturity, decline, and
renewal.
The more powerful technology gets, the less painful and
environmentally impactful this natural renewal/rebirth cycle.
(Example: Japan doesn’t collapse, only suffers a decade of
malaise, even as it gets technologically greener every year.)
Key Question: Why is a civilization life cycle apparently
the optimal evolutionary developmental strategy?
Assumption: We’ve seen this pattern for too long, and
in too many contexts, for it to be suboptimal.
Los Angeles
Palo Alto
© 2004 Accelerating.org
Life Cycles: Further Thoughts
Compare and Contrast:
universes, stars, complex
planets, life forms,
civilizations, cities,
technologies, states of mind.
Stellar Life Cycle
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Palo Alto
The more complex a system becomes, the more MEST
efficient and information-protective the life cycle.
Consider species extinction vs. cultural extinction (and
digital capture).
When was the last time the death of a less adaptive
thought in your mind was seen as wasteful or disruptive?
© 2004 Accelerating.org
Simplicity and Complexity
Universal Evolutionary Development is:
Simple at the Boundaries, Complex In Between
Simple Math
Of the Very Small
Simple Math
Of the Very Large
(Big Bang,
Quantum Mechanics,
Chemistry)
(Classical Mechanics,
General Relativity)
Complex Math
Of the In Between
(Chaos, Life, Humans,
Coming Technologies)
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Palo Alto
Ian Stewart, What Shape is a Snowflake?, 2001
© 2004 Accelerating.org
The Meaning of Simplicity
(Wigner’s ladder)
Complex systems
are evolutionary.
Simple systems
are developmental.
Evolution
Development
Non-Pattern
Pattern
Variety
Uniformity
Symmetry and
Supersymmetry
Symmetry
Breaking
Chaotic Math
Simple Math
The universe is painting complex local evolutionary pictures, on a
simple universe-wide developmental scaffolding.
The picture (canvas/intelligence, in the middle) is
mathematically complex (Gödelian incomplete),
and trillions of times evolutionarily unique.
Los Angeles
Palo Alto
The framework (easel/cosmic structure, very large,
& paint/physical laws, MEST structure, very small)
is uniform, and simple to understand.
© 2004 Accelerating.org
Our Universe Has an Evolutionary
Developmental Purpose
The more we study the dual processes of Evo-Devo, the
better we discover the simple background, and can
create a complex foreground. Take Home Points:
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Palo Alto
Evolutionary variation is generally increasing and
becomes more MEST efficient with time and substrate.
Development (in special systems) is on an accelerating
local trajectory to an intelligent destination.
Humans are both evolutionary & developmental actors,
creating and catalyzing a new substrate transition.
We need both adequate evolutionary generativity,
(uniqueness) and adequate developmental
sustainability (accelerating niche construction) in this
extraordinary journey.
© 2004 Accelerating.org
Understanding the Bifurcation
Prediction Wall is Evolutionary Change
Prediction Crystal Ball is Developmental Change
Los Angeles
Palo Alto
© 2004 Accelerating.org
Examples of
Hierarchical Emergence
Cosmic Embryogenesis
(in Three Easy Steps)
Geosphere/Geogenesis
(Chemical Substrate)
Biosphere/Biogenesis
(Biological-Genetic Substrate)
Noosphere/Noogenesis
(Memetic-Technologic Substrate)
Pierre Tielhard de Chardin
(1881-1955)
Jesuit Priest, Transhumanist,
Developmental Systems Theorist
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Palo Alto
Le Phénomène Humain, 1955
© 2004 Accelerating.org
Eight Useful Systems For Universal
Computation (a.k.a. “Substrates”)
Substrate
1.
2.
3.
4.
5.
6.
7.
8.
Galactic-Subatomic
Stellar-Elemental
Planetary-Molecular
Biomass-Unicellular
Neurologic-Multicellular
Cultural-Linguistic
Computational-Technologic
AI-Hyperconscious
I.P. System
"Galactic"
"Atomic"
"Chemetic"
"Genetic"
"Dendritic"
"Memetic"
"Algorithmic“
"Technetic"
Note: Each is Vastly More MEST-Compressed and IP-Enabled
Los Angeles
Palo Alto
© 2004 Accelerating.org
Every Substrate Has its Niche
The entire evolutionary history of life
involves each organisms increasingly
intelligent (value driven) modification
of their niche, and environmental
responses to these changes.
“Organisms do not simply 'adapt' to
preexisting environments, but actively
change and construct the world in which
they live. Not until Niche Construction,
however, has that understanding been
turned into a coherent structure that brings
together observations about natural history
and an exact dynamical theory.”
– Richard Lewontin, Harvard
Los Angeles
Palo Alto
Niche Construction, Odling-Smee, Laland, Feldman, 2004
© 2004 Accelerating.org
Niches are Increasingly Local in Spacetime
Biogenesis required a cooling Earth-crust, and billennia.
Multicellular organisms required a Cambrian Explosion,
and millennia.
Human culture required a Linguistic Explosion, and tens
of thousands of years.
Science and technology revolutions required a Cultural
Enlightenment, the decomposing biomass of a fraction of
Earth’s dead organisms, and hundreds of years.
Intelligent computers will likely be able to model the birth
and death of the universe with the refuse thrown away
annually by one American family. In tens of years?
Los Angeles
Palo Alto
© 2004 Accelerating.org
Five Astrobiologically Developmental
Systems for Human Computation?
Individual (Vitality,Creativity,Spirituality)
 Family/Relationship (Culture,Psychology)
 Tribal/Nation (Politics,Economics)
 Species/Planet (Peace,Globalization,Environment)
 Universal (Science,Technology,Computation)

–
Question: Which is unlike the others? This last
system is growing apparently asymptotically in
local capacities
These five systems/dialogs seem likely to exist
on all Earth-like planets (e.g., astrobiologically
developmental).
Los Angeles
Palo Alto
© 2004 Accelerating.org
Three Hierarchical Systems
of Social Change

Sociotechnological
(dominant since 1950!)
“It’s all about the technology” (what it enables, how
inexpensively it can be developed)

Economic (dominant 1800-1950’s, secondary now)
“It’s all about the money” (who has it, control they gain with it)

Political/Cultural (dominant pre-1800’s, tertiary now)
“It’s all about the power” (who has it, control they gain with it)
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Palo Alto
Developmental Trends:
1. The levels have reorganized, to “fastest first.”
2. More pluralism (a network property) on each level.
Pluralism examples: 40,000 NGO’s, rise of the power
of media, tort law, Insurance, lobbies, etc.
© 2004 Accelerating.org
The Developmental Spiral
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Homo Habilis Age
Homo Sapiens Age
Tribal/Cro-Magnon Age
Agricultural Age
Empires Age
Scientific Age
Industrial Age
Information Age
Symbiotic Age
Autonomy Age
Tech Singularity
2,000,000 yrs ago
100,000 yrs
40,000 yrs
7,000 yrs
2,500 yrs
380 yrs (1500-1770)
180 yrs (1770-1950)
70 yrs (1950-2020)
30 yrs (2020-2050)
10 yrs (2050-2060)
≈ 2060
© 2004 Accelerating.org
Gently Tightening Subcycles
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Period
Subcycle
Some Features
1390-1500, 110 yrs
1500-1600, 100 yrs
1600-1690, 90 yrs
1690-1770, 80 yrs
1770-1840, 70 yrs
1840-1900, 60 yrs
1900-1950, 50 yrs
1950-1990, 40 yrs
1990-2020, 30 yrs
2020-2040, 20 yrs
2040-2050, 10 yrs
2050-2060, 5/2/1
Pre-Scientific Rev.
1st Scientific Rev.
2nd Scientific Rev.
3rd Scientific Rev.
1st Industrial Rev.
2nd Industrial Rev.
3rd Industrial Rev.
1st Computer Rev.
2nd Computer Rev.
1st Symbiotic Rev.
2nd Symbiotic Rev.
Autonomy Rev’s
Oresme, Coord.Geom., Series
Copernicus, Vesalius
Bruno, Kepler, Descartes
Newton, Linnaeus
“CWT: Coal, Wood, Textiles”
“SST: Steam,Steel,Telegrph”
“ICE: Int.Comb,Chem, Electr”
“Dig.Comp,Engrg,MNC’s,TV”
“Planetnet, MIME, Security”
“GUI,LUI,NUI, Peace/Justice”
“Coll. Intell., Minor Magic”
“Autonomy-Under-the-Hood”
Circa 2060
Tech Singularity
“AI,Earthpark”(Next:Uploads)
© 2004 Accelerating.org
Four Pre-Singularity Subcycles?

A 30-year cycle, from 1990-2020
–

A 20-year cycle, from 2020-2040
–

LUI personality capture (weak uploading), Mature
Self-Reconfig./Evolutionary Computing.
2050: Era of Strong Autonomy
–
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Palo Alto
LUI network, Biotech, not bio-augmentation,
Adaptive Robots, Peace/Justice Crusades.
A 10-year cycle, from 2040-2050
–

1st gen "stupid net "/early IA, weak nano, 2nd
gen Robots, early Ev Comp. World security begins.
Progressively shorter 5-, 2-, 1-year tech cycles,
each more autocatalytic, seamless, human-centric.
© 2004 Accelerating.org
Tech Singularity – Overview

Circa 2060: Technological Singularity
–
–
The AI (shortly thereafter, AI's) claim selfawareness. True, 3rd-gen uploading begins.
World population hits its maximum (2030-2050),
declines increasingly rapidly thereafter.
2040
Any Fixed-Complexity
Replicating Substrate
(e.g. Homo Sapiens)
1970
“The Envelope Curve is
Local Universal Computation”
Los Angeles
Palo Alto
Warren Sanderson, Nature, 412, 2001
Tom McKendree, Hughes Aircraft, 1994
© 2004 Accelerating.org
Types of Singularities
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Mathematical
Physical
Cosmological (our best model?)
Computational
Developmental (our best model?)
Technological
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Los Angeles
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"singular" human-competitive A.I. Emergence
discontinuous (physical-dynamical singularity)
unknowable (computational-cognitive singularity)
convergent (developmental singularity)
hierarchical (developmental singularity)
instantaneous (developmental singularity)
reproductive (developmental singularity)
© 2004 Accelerating.org
Finite-Time Singularities
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Los Angeles
Palo Alto
PDE’s of General Relativity in a mass field, leading to
black hole formation
PDE’s of Euler equations of inviscid fluids in relation
to turbulence
Rotating coin spinning down to a table (Euler’s disk)
Earthquakes (ex: slip-velocity Ruina-Dieterich friction
law and accelerating creep)
Micro-organism chemotaxis models (aggregation to
form fruiting bodies)
Stock market crashes (as catastrophic events).
Source: Didier Sornette, Critical Phenomena in the Natural Sciences, 1999
© 2004 Accelerating.org
Macrohistorical Finite-Time
Singularities
Ray Kurzweil
Los Angeles
Palo Alto
Why Stock Markets Crash, 2003
The Singularity is Near, 2005
Singularity 2050 ±10 years
Singularity 2050 ±20 years
© 2004 Accelerating.org
Macrohistorical Finite-Time
Singularities (cont’d)
Los Angeles
Palo Alto
Trees of Evolution, 2000
The Evolutionary Trajectory, 1998
Singularity 2080 ±30 years
Singularity 2130 ±20 years
© 2004 Accelerating.org
From the Big Bang to Complex Stars:
“The Decelerating Phase” of Universal ED
Los Angeles
Palo Alto
© 2004 Accelerating.org
From Biogenesis to Intelligent Technology:
The “Accelerating Phase” of Universal ED
Carl Sagan’s
“Cosmic
Calendar”
(Dragons of
Eden, 1977)
Each month is
roughly 1
billion years.
Los Angeles
Palo Alto
© 2004 Accelerating.org
A U-Shaped Curve of Change?
Big Bang Singularity
50 yrs: Scalar Field Scaffolds
50 yrs ago: Machina silico
100,000 yrs: Matter
100,000 yrs ago: H. sap. sap.
1B yrs: Protogalaxies
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Palo Alto
Developmental Singularity?
8B yrs: Earth
© 2004 Accelerating.org
Eric Chaisson’s “Phi” (Φ):
A Universal Moore’s Law Curve
Free Energy Rate Density
Substrate
Ф
(ergs/second/gram)
time
Galaxies
Stars
Planets (Early)
Plants
Animals/Genetics
Brains (Human)
Culture (Human)
Int. Comb. Engines
Jets
Pentium Chips
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Palo Alto
0.5
2 (“counterintuitive”)
75
900
20,000(10^4)
150,000(10^5)
500,000(10^5)
(10^6)
(10^8)
(10^11)
Source: Eric Chaisson, Cosmic Evolution, 2001
© 2004 Accelerating.org
Just what exactly are black holes?
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Palo Alto
© 2004 Accelerating.org
Lee Smolin’s Answer:
“Cosmological Natural Selection”
At least 8 of the 20 “standard model”
universal parameters appear tuned for:
– black hole production
– multi-billion year old Universes
(capable of creating Life)
Los Angeles
Palo Alto
The Life of the Cosmos, 1996
© 2004 Accelerating.org
Developmental Singularity – Overview

Post 2060
–
–
Full AI Sim of Human Thoughtspace (ref.: Our multimillion
dollar sims of bacterial metabolome)
Historical Computational Closure (astronomy, geography,
brains, etc.). Maps rapidly close the very large and very
small, leaving only the very complex…
"Inner space," not outer space, now appears to be our constrained
developmental destiny, incredibly soon in cosmologic time. "
Los Angeles
Palo Alto
For astronomical closure, see Martin Harwit, Cosmic Discovery, 1981
© 2004 Accelerating.org
Physics of a “MESTI” Universe
Physical Driver:
 MEST Compression/Efficiency/Density
Emergent Properties:
 Information Intelligence (World Models)
 Information Interdepence (Ethics)
 Information Immunity (Resiliency)
 Information Incompleteness (Search)
An Interesting Speculation in Information Theory:
Entropy = Negentropy
Universal Energy Potential is Conserved.
Los Angeles
Palo Alto
© 2004 Accelerating.org
Binding Energy (of Computational Structure)
Systems theorist Ervin Laszlo (Evolution, 1987) notes each hierarchically
emergent universal substrate greatly decreases the binding energy of its
diverse (evolutionary) physical configurations. Examples:
 matter (earliest emerging physical substrate), e.g., protons and neutrons
within the nucleus of atoms, is bound by nuclear exchange ("strong") forces
 atoms are joined by much weaker ionic or covalent (electromagnetic) bonds
 cells within multicellular organisms are connected "another dimension down
the scale of bonding energy."
 memes encoded in a vesicular-morphologic language of synaptic weights and
dendritic arborization involve vastly less binding energy still
 technemes, in communicable electronically-encoded algorithms and logic
circuitry involve orders of magnitude less binding energy yet again.
 gravitons. Note gravity is the 2nd weakest of the five known forces (only dark
energy is weaker). Yet in Smolin’s model gravity guides us to black holes as a
developmental attractor for substrate computation in this universe.
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Palo Alto
In other words, the MEST efficiency, or energy cost of computation, of
learning (encoding, remembering, reorganizing) rapidly tends to zero in
emergent substrates as we approach the developmental singularity.
© 2004 Accelerating.org
Growth and Limits of Computation

Universal Computing to Date: 10^120 logical ops
–

Digital Computing to Date: 10^31 logical ops
–

Understanding most Developmental History and some of
Evol. History. (e.g., CA’s, Gen. Engrg.)
Computing right down to Planck Scale?
–
–
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Half this was produced in the last 2 year doubling.
300 Doublings (600 years) to a “Past-Closed”
Omega Computer?
–

Turing, Von Neumann, Ed Fredkin, John Wheeler
No Minimum Energy to Send a Bit (Landauer)
Quantum and Femto-Scale Processes
Sources: Seth Lloyd, “Computational Capacity of the Universe, Phys.Rev.Lett., 2002
C. Bennett & R. Landauer, “Fund. Phys. Limits of Computation, Sci. Am., July 1985
© 2004 Accelerating.org
Understanding MEST Compression
We
End Up
Here
The Finite
Universe Box
Six Billion
Years Ago
MEST compression/Time
Los Angeles
Palo Alto
© 2004 Accelerating.org
A Developmental Universe?
Developmental Lesson: A Possible Destiny of Species
MEST compression, Intelligence, Interdependence, Immunity
Inner Space, Not Outer Space (Mirror Worlds, Age of Sims)
Black Hole Equivalent Transcension?
Los Angeles
Palo Alto
© 2004 Accelerating.org
The Fermi Paradox
So where are the ET’s?
Andromeda Galaxy
Only 2 mill light yrs away
Our Milky Way Galaxy is just
45,000 light years in radius.
Earth-like planets 3-5 Billion years
older than us nearer the core.
Los Angeles
Palo Alto
A Dev. Sing. Prediction:
SETI Fossils by 2080
© 2004 Accelerating.org
Present Score:
13 for Transcension, 2 for Expansion
The Case For Transcension
1. Universal Speed Limit (c), and Isolation of Everything Interesting
2. Singularities Everywhere
3. Hyperspace (Our Universe is a Riemann Manifold in 4D Space)
4. String and Supersymmetry Theory (10, 11, or 26 Dimensions)
5. Multiverse Theories (CNS, INS)
6. Fermi Paradox (Parsimonious Transcension Solution)
7. Relentless MEST Compression of Substrate Emergence
8. Technological Singularity Hypothesis
9. “Plenty of Room at the Bottom” (Richard Feynman about Nanotech)
10. Bottom is Strange (Quantum Weirdness), But Stably Convergent!
11. A Non-Anthropomorphic Future
12. Lambda Universe Message (The Kerrigan Problem. "Why Now?")
13. Midpoint Principle (Subset of Cosmic Watermark Hyp./Wigner's Ladder)
The (Highly Suspect) Case for Expansion
1. 3D Space is Suited to Humanity
2. A Comfortable Extrapolation of our Frontier Experience
Los Angeles
Palo Alto
© 2004 Accelerating.org
Virtual Space:
Is Inner Space the Final Frontier?
Mirror Worlds, David Gelernter, 1998.
Large scale structures in spacetime are:
• A vastly slower substrate for evolutionary development
• Relatively computationally simple and tractable (transparent)
• Rapidly encapsulated by our simulation science
• A “rear view mirror” on the developmental trajectory of
emergence of universal intelligence?
versus
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Palo Alto
Non-Autonomous ISS
Autonomous Human Brain
© 2004 Accelerating.org
Physical Space:
A Transparent Society (“Panopticon”)
David Brin,
The Transparent Society, 1998
Hitachi’s mu-chip:
RFID for paper currency
Los Angeles
Palo Alto
© 2004 Accelerating.org
Ephemeralization (MEST Efficiency of
Physical-Computational Transformations)
In 1938 (Nine Chains to the Moon), the poet and polymath
Buckminster Fuller coined "Ephemeralization,” positing
that in nature, "all progressions are from material to
abstract" and "every one of the ephemeralization
trends.. eventually hits the electrical stage" such that
"even efficiency (doing more with less) ephemeralizes."
In 1981 (Critical Path), he called ephemeralization, "the invisible
chemical, metallurgical, and electronic production of ever-moreefficient and satisfyingly effective performance with the investment
of ever-less weight and volume of materials per unit function
formed or performed". In Synergetics 2, 1983, he called it "the
principle of doing ever more with ever less weight, time and energy
per each given level of functional performance” This meta-trend has
also been called “virtualization” by other theorists.
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Combined, these statements may be among the first to name MEST
compression/efficiency/density of computational transformations,
the apparent driver of accelerating change in special physical
© 2004 Accelerating.org
environments.
The Practical Benefit of Understanding MEST
Compression: Developmental Foresight
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Palo Alto
GDP weight trends down in every developed
country.
More MEST-efficient systems have increased
“system dynamism”/degrees of structural
freedom (Jack Hipple, TRIZ)
New technological paradigms generally use
dramatically less MEST/capital investment.
(Nano, Bio, Info, Cogno vs. Coal, Steel, and
Oil development). Exception: Some infotech
hardware (chip fab plants, microrobotics, etc.).
© 2004 Accelerating.org
Seeing MEST Efficiency and
Compression Everywhere in the World
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Palo Alto
Cities (>50% of world population circa 2005)
Working in Offices (or telecommuting with
coming videophone virtual offices)
Wal-Marts, Mega-Stores, 99 Cent Stores (Retail
Endgame: Wal-Mart #1 on Fortune 500 since
2001)
Flat-Pack Furniture (Ikea)
Big Box Retail (Home Depot, Staples)
Supply-Chain & Market Aggregators (Dell,
Amazon, eBay)
Local community/Third Space (Starbucks)
© 2004 Accelerating.org
Key Shifts in the Venture Capital Market
Switching is shifting from circuits to packets.
Data, then voice; Backbone, then access
Transmission is shifting from electronic to photonic.
First long haul, then metro, then local access
Functions are moving from the enterprise to the Net.
IP universal protocol/ platform of choice is the Net
Offerings are moving from products to services.
"Utilitization" of processing, applications, storage, knowledge
Bioscience is moving from in vitro to in silico.
First Genomics, then Proteomics, then nanotechnologies
(More agent-based, more MEST-compressed, more network-like,
more information-based, more hardware oriented.)
Los Angeles
Palo Alto
Source: Jim Spohrer, IBM Almaden, 2004
© 2004 Accelerating.org
Stratellites:
A Developmental Attractor?
Inventor: Hokan Colting
21stCenturyAirships.com
180 feet diameter. Autonomous.
60,000 feet (vs. 22,000 miles)
Permanent geosynch. location.
Onboard solar and navigation.
A “quarter sized” receiver dish.
Why are satellites presently losing
against the wired world?
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Los Angeles
Palo Alto

Border monitoring
(low altitude drug flights)
City monitoring
Early warning radar
Urban broadband
Latency, bandwidth, and launch costs.
MEST compression always wins.
Don’t bet against it!
© 2004 Accelerating.org
The Future of
Automation and Economics
World Economic
Performance
GDP Per Capita in
Western Europe,
1000 – 1999 A.D.
This curve looks
very smooth on a
macroscopic scale.
The “knee of the
curve” occurs at the
industrial revolution,
circa 1850.
Los Angeles
Palo Alto
© 2004 Accelerating.org
Understanding Automation
Between 1995 and 2002 the world’s 20 largest economies lost
22 million industrial jobs. This is the shift from a Manufacturing
to a Service/Information Economy.
1995-02, America lost 2 million industrial jobs, mostly to China.
China lost 15 million such jobs, mostly to machines. (Fortune)
Despite the shrinking of America's industrial work force, our
country's overall industrial output increased by 50% since
1992. (Economist)
“Robots are replacing humans or are greatly enhancing human performance in
mining, manufacture, and agriculture. Huge areas of clerical work are also
being automated. Standardized repetitive work is being taken over by
electronic systems. The key to America's continued prosperity depends on
shifting to ever more productive and diverse services. And the good news is
jobs here are often better paying and far more interesting than those on we
knew on farms and the assembly line.” (Tsvi Bisk)
Los Angeles
Palo Alto
"The Misery of Manufacturing," The Economist. Sept. 27, 2003
"Worrying About Jobs Isn't Productive," Fortune Magazine. Nov. 10, 2003
“The Future of Making a Living,” Tsvi Bisk, 2003
© 2004 Accelerating.org
Interface:
Understanding Process Automation
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Palo Alto
Perhaps 80-90% of today's First World
paycheck is paid for by automation
(“tech we tend”).
Robert Solow, 1987 Nobel in
Economics (Solow Productivity Paradox,
Theory of Economic Growth)
“7/8 comes from technical progess.”
Human contribution (10-20%) to a First
World job is Social Value of Employment
+ Creativity + Education
Developing countries are next in line
(sooner or later).
Continual education and grants
(“taxing the machines”) are the final job
descriptions for all human beings.
Termite Mound
© 2004 Accelerating.org
Work in 2050 Scenario:
100:10:1 Tax:Foundation:Corporate Global Philanthropy
 As technology-driven corporate GDP grows exponentially at 4% or more
each year, historical analysis argues governments will continue to do by far
the most “social contract giving,” (100:10:1 govt. to individual to corporate
giving ratio). That would mean that the service work of many, perhaps even
most of our 200 million+ employees (total 2050 pop. of 300-400 million) circa
2050 will be supported by the equivalent of “grant proposals to the
government” to do various public works, in the same the way our country’s
1.5 million nonprofits presently are supported by government and private
foundation grants today. Thus the 1/6 of us that presently work for (or live
off) the government will likely double by 2050 (European model).
 Secondarily, individuals and their foundations, with progressively increased
social leverage due to tech-aided wealth increase, will do more giving each
year. Look to individuals, with their uniquely creative and transformative
giving styles (through foundations, legacy, and discretionary giving) to
usher in an Age of Global Philanthropy in the post-LUI era after 2020.
 To recap, while corporations will bring lots of new technology-enabled
wealth into the world, philanthropy will likely continue to be driven first by
governments (100X) then individuals (10X) and finally business (1X).
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See: Millionaires and the Millennium, Havens and Schervish, 1999
© 2004 Accelerating.org
Process Automation Example:
Oil Refinery (a Multi-Acre Automatic Factory)
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Tyler, Texas, 1964. 360 acres. Run by three operators,
each needing only a high school education.
The 1972 version eliminated the three operators.
© 2004 Accelerating.org
Problem: Social Disruption Due to
Technological Revolutions
Manufacturing Globalization Revolution (1980’s)
 Info Tech (IT) Globalization Revolution (2000’s)
 LUI Automation Revolution (2020’s)
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Some jobs that went to Mexican maquiladoras in the
1980’s are going to China in the 2000’s. Many of these
jobs will go to machines in the 2020’s.
What to do?
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© 2004 Accelerating.org
Automation Development Creates
Massive Economic-Demographic Shifts
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Automating of farming pushed people into
factories (1820, 80% of us were farmers, 2% today)
Automating of factories is pushing people
into service (1947, 35% were in factories, 14% today)
Automating of service is pushing people into
information tech (2003, 65% of GDP is in service industry)
Automating of IT will push people into
symbiont groups (“personality capture”)
Automating of symbiont groups will push
people beyond biology (“transhumanity”)
© 2004 Accelerating.org
IT’s Exponential Economics
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Courtesy of Ray Kurzweil and KurzweilAI.net
© 2004 Accelerating.org
Automation and the Service Society
Our 2002 service to manufacturing labor ratio,
110 million service to 21 million goods workers, is 4.2:1
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© 2004 Accelerating.org
De Chardin on Acceleration:
Technological “Cephalization” of Earth
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“Finite Sphericity + Acceleration =
Phase Transition”
"No one can deny that
a world network of
economic and psychic
affiliations is being woven
at ever increasing speed
which envelops and
constantly penetrates more
deeply within each of
us. With every day that
passes it becomes a little
more impossible for us
to act or think otherwise
than collectively."
© 2004 Accelerating.org
U.S. Transcontinental Railroad:
Promontory Point Fervor
Built by hard-working
immigrants
The Network of the 1880’s
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© 2004 Accelerating.org
IT Globalization Revolution (2000-20):
Promontory Point Revisited
The more things change, the
more some things stay the
same.
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The coming intercontinental internet will be built
primarily by hungry young programmers and tech
support personnel in India, Asia, third-world
Europe, Latin America, and other developing
economic zones. In coming decades, such individuals
will outnumber the First World technical support
population between five- and ten-to-one.
Consider what this means for the goals of modern
business and education: Teaching skills for global
management, partnerships, and collaboration.
© 2004 Accelerating.org
Technological Globalization: Winners
Globalization is less a choice than a
statistical inevitability, once we have
accelerating, globe-spanning technologies
(communication, databases, travel) on a
planet of finite surface area (“sphericity”).
There are some clear winners in this phase transition, such as:
Network Memes and Traditions like Free Markets,
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Democracy, Peace and other Interdependencies
(The Ideas that Conquered the World, Michael Mandelbaum)
Big Cities (backbone of the emerging superorganism)
(Global Networks, Linked Cities, Saskia Sassen)
Global Corporations (large and small)
(New World, New Rules, Marina Whitman)
© 2004 Accelerating.org
Technological Globalization: Losers
Some of the longer term losers:
Non-Network Memes and Traditions like
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Autocracy, Fascism, Indefinite Protectionism, Communism
(Power and Prosperity, Mancur Olson)
 Centrally-Planned (mostly Top-Down) vs. Market-Driven
(mostly Bottom-Up) Economies (“Third World War”)
(The Commanding Heights, Daniel Yergin)
(Against the Tide, Douglas Irwin)
 Groups or Nations with Ideologies/Religions Sanctioning
Network-Breaking Violence (“Fourth World War”)
(The Clash of Civilizations, Samuel Huntington)
Centrally-Planned vs. Self-Organizing Political Systems
(excepting critical systems, like Security)
(The Future and Its Enemies, Virginia Postrel)
© 2004 Accelerating.org
Technological Globalization: Uncertains
Most elements of modern society, of course, are evolutionary,
meaning they remain ‘indeterminate’ actors which may or may
not become winners. Their fate depends critically on the paths
we choose. Some key examples:
Humanist Memes like Justice, Equal Opportunity,
Individual Responsibility, Education, Charity, Compassion,
Cultural Diversity, Sustainability, Religious Tolerance
(The Dignity of Difference, Jonathan Sacks)
The Unskilled Poor (In All Economies, U.S. to Uganda)
(A Future Perfect, Micklethwait and Wooldridge)
 The Developing World
(The Mystery of Capital, Hernando de Soto)
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© 2004 Accelerating.org
“NBICS”: 5 Choices for Strategic
Technological Development
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Nanotech (micro and nanoscale technology)
Biotech (biotechnology, health care)
Infotech (computing and comm. technology)
Cognotech (brain sciences, human factors)
Sociotech (remaining technology applications)
It is easy to misspend lots of R&D money on a still-early
technology in any field.
Infotech examples: A.I., multimedia, internet, wireless
It is even easier to misspend disproportionate amounts of
R&D budgets on a less centrally accelerating field.
Current examples: Nanotech and biotech
Assumption: Any nation today can far more quickly get
substantially better infotech than biotech or nanotech.
© 2004 Accelerating.org
Is Biotech a Saturated Substrate?
21st century neuropharm and neurotech won’t
accelerate biological complexity (seems likely now).
– Neural homeostasis fights “top-down” interventions
– “Most complex structure in the known universe”
Strong resistance to disruptive biointerventions
– In-group ethics, body image, personal identity
We’ll learn a lot, not biologically “redesign humans”
– No human-scale time, ability or reason to do so.
– Expect “regression to mean” (elim. disease) instead.
Neuroscience will accelerate technological complexity
– Biologically inspired computing. “Structural mimicry.”
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© 2004 Accelerating.org
Computational Limits on
21st Century Biotechnology
Biology is Bottom-Up Designed, Massively Multifactorial,
and Nonlinearly Interdependent.
“Genetically engrd humans” (2000) are “atomic vacuum cleaners” (1950)
Increased Differentiation = Decreased Intervention
Clipping growth genes into frogs vs. mice vs. pigs. Developmental damage!
“Negative pleiotropy increases with complexity.”
Our Genetic “Legacy Code” Appears Highly Conserved
The entire human race is more genetically similar than a single baboon troop.
A massive extinction event circa 70,000 years ago is one proposal for this (ref).
Much more likely is simple developmental path dependency.
Mental Symbolic Manipulation is Deep Differentiation
Wernicke’s and Broca’s are apparent equivalent of metazoan body plans!
(see Terrence Deacon, The Symbolic Species, on co-evolution of lang. & brain)
Even with preadaptation (Gould) & requisite variety (Ashby), drift = dysfunction.
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Features of Evol. and Expansion of Modern Humans, Inferred from
Genomewide Microsatellite Markers," Zhivotovsky, 2003, AJHG
© 2004 Accelerating.org
Nanotech and Cognotech are both
AI-Dependent Systems
Key Assumptions:
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Nanotech Will Require Bottom-Up,
Biologically-Inspired AI to Realize the full
“Drexlerian” molecular assember vision
(Erik Drexler, Engines of Creation, 1986).
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Cognotech (e.g., human consciousness) will
only expand past its current saturation when
we have nanotech and fine-grained AI
personality capture interfaces
© 2004 Accelerating.org
Infotech and Sociotech Are the Engine and
Driver of the Coming Transition
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Infotech (“AI”):
Process Automation
Storage, Networking, and Simulation
Biologically-Inspired Computing
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Sociotech (“IA”):
Digital Ecologies
Immunity, Compassion, and Interdependence
Linguistic User Interface
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© 2004 Accelerating.org
5 Info- and Socio-technological Levers
for Third World in the 21st Century
1. Infotech (Education, Digital Ecologies)
2. Globalization (Education, Bilingualism,
Unique Competitive Advantages)
3. Transparency (Education, Accountability,
Anti-Corruption)
4. Liberalization (Education, Legal and
Democratic Reform)
5. Compassion (Education, Rich-Poor Divides,
NGOs, Workfare, Philanthropy)
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© 2004 Accelerating.org
Infotech: Digital Ecologies
Key Questions: Public access? Subsidized? Education?
Strong network effects. Intrinsically socially stabilizing.
“There is no digital divide.” (Cato Institute)
Radio
Low Power TV
Groupware
Internet
IM/SMS
Avatars
Email
Cell Phones
Cordless Phones
Game PCs
Newspapers
(Program Guides)
Desktop PCs
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PDAs
Social Software
© 2004 Accelerating.org
AI-in-the-Interface (a.k.a. “IA”)
• AI is growing, but slowly (KMWorld, 4.2003)
― $1B in ’93 (mostly defense), $12B in 2002
(now mostly commercial). AGR of 12%
― U.S., Asia, Europe equally strong
― Belief nets, neural nets, expert sys growing
faster than decision support and agents
― Incremental enhancement of existing apps
(online catalogs, etc.)
• Computer telephony (CT) making strides
(Wildfire, Booking Sys, Directory Sys).
ASR and TTS improve. Expect dedicated DSPs
on the desktop after central CT. (Circa 2010-15?)
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• Coming: Linguistic User Interface (LUI)
Persuasive Computing, and
Personality Capture
© 2004 Accelerating.org
Linguistic User Interface
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Google’s cache (2002, % non-novel)
Watch Windows 2004 become
Conversations 2020…
Convergence of Infotech and Sociotech
© 2004 Accelerating.org
Today: Gmail
Free, search-based webmail service with 1,000
megabytes (1 gigabyte) of storage. Google
search quickly recalls any message you have
ever sent or received. No more need to file
messages to find them again.
All replies to each retrieved email are
automatically displayed (“threaded”). Relevant
text ads and links to related web pages are
displayed adjacent to email messages.
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© 2004 Accelerating.org
Tomorrow:
Social Software, Lifelogs
Gmail preserves, for the first time, everything we’ve ever
typed. Gmailers are all bloggers (who don’t know it).
Next, we’ll store everything we’ve ever said. Then
everything we’ve ever seen. This storage (and
processing, and bandwidth) makes us all networkable in
ways we never dreamed.
Lifeblog, SenseCam, What Was I Thinking, and
MyLifeBits (2003) are early examples of “LifeLogs.”
Systems for auto-archiving and auto-indexing all life
experience. Add NLP, collaborative filtering, and other
early AI to this, and data begins turning into wisdom.
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© 2004 Accelerating.org
Phase Transitions: Web, Semantic
Web, Social Software, Metaweb
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Nova Spivak, 2004
© 2004 Accelerating.org
Robo sapiens
“Huey and Louey”
AIST and Kawada’s HRP-2
(Something very cool
about this algorithm…)
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Aibo Soccer
© 2004 Accelerating.org
What Computers Do that Human’s Don’t
Humans Need Secrecy, Lies, Violence.
They Solve Computational Problems for Us.
(Harold Bloom, The Lucifer Principle). But Computers?
Open-Ended Learning Capacity: Hyperconsciousness
Greater Degrees of Freedom, "Perfect" Retention and Forgetting
Communication of Knowledge Structures, Not Just Language
Maintain Multiple Perspectives Until Data Come In. No Variation Cost.
Computational Ethics: NZS Games, Global Optima
Information Flow Hypothesis of Self (Boundary, Dennett)
Information Flow Hypothesis of Conflict (Rummel, etc.)
Tolerance of Human Beings vs. Human Brains (Minsky, Society of Mind)
Conclusion: AI’s Will Be Far More Interdependent,
Ethical, Empathic to Others, & Stable Than
Humans Could Ever Be, By Apparent Design
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© 2004 Accelerating.org
Solution: Personality Capture and
Transhumanity
In the long run, we become seamless with our machines.
No other credible long term futures have been proposed.
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“Technology is becoming organic. Nature is becoming
technologic.” (Brian Arthur, SFI)
© 2004 Accelerating.org
Your “Digital You” (Digital Twin)
“I would never upload my consciousness
into a machine.”
“I enjoy leaving behind stories about my life
for my children.”
Prediction: When your mother dies in 2050,
your digital mom will be “50% her.”
When your best friend dies in 2080, your
digital best friend will be “80% him.”
When you die in 2099, your digital you will be
99% you. Will this feel like death, or growth?
Successive approximation, seamless
integration, subtle transition.
When you can shift your consciousness between
your electronic and biological components, the
encapsulation and transcendence of the biological
will feel like only growth, not death.
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We wouldn’t have it any other way.
Greg Panos (and Mother)
PersonaFoundation.org
© 2004 Accelerating.org
System Meta-Properties: Intelligence
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Informational Intelligence
“The Cosmic Watermark Hypothesis” (E. Wigner)
Evidence: Ashby’s Law of Requisite Variety
Game is Rigged to Make Watermarks & Intelligence
Strongly Coadaptive.
Evidence: Historical Computational Closure:
Columbus's Geography  Harwit's Astronomy 
Smolin's Universe?
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© 2004 Accelerating.org
System Meta-Props: Interdependence
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Informational Interdependence
“The Empirical Ethics Hypothesis” (E.O. Wilson)
Evidence: Evolutionary Psychology
Matt Ridley on reciprocal altruism, Guppies to Gangsters.
Evidence: Non-Zero Sum Games
Robert Wright on capitalism, cooperation, ethics.
Evidence: Statistical Elimination of Social Violence
R.J. Rummel on Statistics for Democide
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© 2004 Accelerating.org
System Meta-Properties: Immunity
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Informational Immunity
“The Child-Proof Universe Hypothesis” (J. Smart)
Evidence: Average Distributed Complexity (ADC)
This measure always accelerating. Catastrophes only
catalyze and stabilize ADC.
Evidence: History of Tech (vs. Civilizations)
Fall of Egypt,Maya,Rome no effect on global tech diffusion.
Evidence: K-T Extinction
Genetic complexity only increased
Evidence: History of Plagues
Never, ever a species threat. Immunity always catalyzed.
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© 2004 Accelerating.org
System Meta-Props: Incompleteness
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Informational Intelligence
“The Incompleteness Theorem” (K. Godel)
Evidence: Godel, Church-Turing, Chaitin
Every system is computationally incomplete.
New substrates are necessary to answer undecidable
questions that can be posed from within any
formal logical system.
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© 2004 Accelerating.org
Accelerating Change, World Security,
and the Non-Integrating Gap
Connectivity is a
Developmental Attractor
Francis Fukuyama (The End of History),
Thomas Friedmann (The Lexus and the Olive
Branch), Robert Kagan (Of Power and
Paradise) Thomas Barnett (The Pentagon’s
New Map) and Samuel Huntington (The Clash
of Civilizations) are all mostly right.
The developmental destination for nation states
is clear. But the evolutionary path is bottom
up, and so must be culturally unique.
Our job is to facilitate this one-way transition as
uniquely and as measurably as possible.
These two goals sometimes conflict.
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© 2004 Accelerating.org
The Pentagon’s New Map
A New Global Defense Paradigm
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© 2004 Accelerating.org
Shrinking the Disconnected Gap
The “Ozone Hole”
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© 2004 Accelerating.org
The Disconnected Gap:
Our Planetary Ozone Hole
Global Polarization (Core vs. Gap)
“Disconnectedness (tech, economic, cultural) defines
danger.” (Thomas Barnett, Pentagon’s New Map)
 Strategy: Encircle, Support the Seam States
-- Plant resources in “supportive soil.”
-- Greatest comparative advantage for shrinking the
hole (eg. Koreas).
 Strategy: Don’t Stir Up the Ant’s Nest
-- This is difficult, as due to differential immunity, our
cultural memes (materialism, democracy, etc.) are as
powerful as the germs that wiped out up to 90% of the
less immunologically complex cultures (Rome, 1200AD, Europe, 1300, America, 1492-1600)
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© 2004 Accelerating.org
“Broken Windows” Policies:
A Precondition to MEV
Broken Windows theory of political scientist
James Wilson and criminologist George
Kelling (The Atlantic Monthly, March 1982)
Rapid response to and repair of the visibly
"broken" aspects of a local community
increases sense of control, ownership,
initiative and vigilance against crime.
Billboards with easy reporting phone numbers
and list of the top acts people should report.
Giving statistics and trends. Enlisting the
collective in simple vigilance.
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© 2004 Accelerating.org
Unconscious Gap Strategy:
Measurable Exponential Value (MEV)
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Culture-appropriate determination of needs
Invited solutions, two way communication,
feedback, local customization
Subsidize the solutions
Measure the growth rate (exponentiation)
Bottom up marketing
A mix of self sufficiency and philanthropy
(development)
If you don’t see exponential adoption,
intervention will not be perceived as a
comparative advantage. Adapt and iterate.
© 2004 Accelerating.org
Examples: Iraq
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Communications (cellphones)
Lighting (digital solid state)
Energy (centralized economies of scale, subsidized
deflationary prices; decentralized storage and
generation)
Example: Donkey cart generators
Security (networked cameras; camera traps)
Culturally-dependent: Britain vs. S. Africa vs. U.S.
Portable CD Players/local music ($10 at Wal-Mart)
Public access radio and TV stations
Food storage, culinary, and women’s needs
Sports / Youth Fads
© 2004 Accelerating.org
IDAP Technology Processes
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Innovation
Diffusion
Assessment
Policy
“The future is here, it’s just not evenly distributed yet.”
– William Gibson
First to third world diffusion is arguably the greatest
gap. But culture-appropriate assessment processes,
sensitive policymaking, and fostering cultures of
innovation are also important.
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© 2004 Accelerating.org
The Psychology of Exponential Growth
Exponential growth keeps people satisfied.
Benefits are self-reinforcing.
People maintain behavior on non-zero sum interactions,
where the size of the pie and your absolute return
grows even as your percentage decreases annually
(Robert Wright, Non-Zero, 2000)
Citizens turn toward personal and local development,
much less toward nationalism and ideology
(Ron Inglehart, The Silent Revolution, 1976;
Modernization and Postmodernization, 2002)
We can measure this (census and other surveys).
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© 2004 Accelerating.org
The Key Strategic Question
with any Gap Intervention
Not whether we could have been liked better,
won more “hearts and minds” (in Iraq or
among our allies).
The key question is the degree to which new
exponential ecologies (technological,
economic, social) are adopted and persist in
the community.
-- Tools, Markets, Rules
We can measure this (operations research).
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© 2004 Accelerating.org
The Say-Do Development Gap
2,600 Iraqi Development Projects Promised
160 under way presently. (Time, July 2004)
Of all of these, communications has been our
biggest shortcoming (“failure to communicate”).
We wired ourselves superbly (CPOF) but we never
wired in to the populace, or even helped them to wire
themselves, in exponential fashion.
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Example: DARPA/USC ICT Tactical Language project.
Top-down thinking. Avatars vs. Persistent Worlds.
We could have had scores of Iraqi/Arabic youth teaching
our incoming soldiers tactical culture in massively
multiplayer online worlds, and using those worlds for
their own benefit as well. A tipping point among the
youth (like Satellite Television in India, etc.). © 2004 Accelerating.org
Immune Recognition vs. Rejection
The phenomenon of immune recognition (and
immune tolerance) vs. rejection.
The honeymoon period.
Rejection, if no measurable exponential value
within the host network.
We did not pass this test (in fairness, we may
never have passed).
Nevertheless, there were many missed
opportunities for deploying MEV strategy.
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© 2004 Accelerating.org
Tech Immune Systems Example:
Cellphones
An intrinsically defensive asset.
-- Monitorable (location and content)
-- Strengthen personal networks
-- The mean can self-police the extremes (report
scofflaws)
-- Granular privileges (given and revoked)
-- Can be built robustly (dynamo, shoe batts)
-- Chip provides superior ID (address books)
-- Hot button to security radio band
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Palo Alto
© 2004 Accelerating.org
Tech Immune Systems Example:
Firearms for Police
Networked weapons are an intrinsically
defensive asset.
-- Single shot magazines (deterrence)
-- Cameras and microphones (“Black Box”)
-- Cellphone to CENTCOM when safety off
-- The best training possible (on the job)
-- The inevitable future (worldwide buyback of all
non-networked lethals except antiques (eg.
Australia) the emergence of networked nonlethals.
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© 2004 Accelerating.org
What is our ‘control’ study?
How do we know providing Measurable
Exponential Value would have worked in Iraq?
What’s our ‘control’ for the connectivity doctrine?
The Gap’s own history:
Maoist China, Kampuchea, Afghanistan...
Every example of swings away from connectivity
has been unsustainable in space and time.
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© 2004 Accelerating.org
Why the Gap Shrinks
“He who can handle the quickest rate of change
survives.” -- Col. John Boyd, Military Strategist
Time compression is one form of MEST compression.
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Why Eurasia won the sociopolitical, technological,
military, and germ development race (Largest EastWest Axis, earliest domestication of animals, Jared
Diamond, Guns, Germs, and Steel).
Why Europeans decimated the Americas and Pacific
Islanders with a host of crowd infectious diseases,
and not the other way around.
Why the Gap will shrink to next-to-nothing as we
create a transparent global society this century.
© 2004 Accelerating.org
U.S. Army: Development Challenges
and Opportunities
Security Leader
Development Follower
This makes institutional sense. A natural constraint.
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Many development capability options:
 Specialization (Corps of Engineers, etc.).
 Unique Capacities (Fire and weather mgmt, FLEs)
 Competition (Cross services bidding)
 Incentives if under budget and before deadline with
quality (ex: Kowloon Tunnel (Hong Kong), Human
Genome Project, etc.))
 Networks (America’s Army: worldwide devel. recruits)
 Partnerships. Most obvious: USAID (long term
optimists). Many others as well (bottom up). © 2004 Accelerating.org
Professional Futuring Tools
Acceleration Forecasting (M.S.)
 What is accelerating?
 How fast? For how long?
 What human problem does this solve?
 When/how should we implement?
Operations Research (M.S.)
 What are likely optima with present conditions?
 What are the possible MEST efficiencies?
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Developmental Future Studies (M.S.)
 What are the inevitable attractors and TINA trends?
 When will we get to the next phase change, PTE?
 How does this influence present policy and strategy?
© 2004 Accelerating.org
Closing Questions
Six Questions
1. What would you monitor/scan/measure today to see if we are on an
S-Curve or J-Curve of global computational change?
2. What methods would you use to distinguish evolutionary randomness
from developmental trajectory
3. Is the tech singularity coming? What? When? Where? How? Why?
4. What are our control options for accelerating and ever more
autonomous computation?
5. What are better and worse paths of technology development?
6. How do we promote unity, balance, and accelerating compassion in
the transition?
Consider the First and Third World GDP Curves, 1900 to 2000.
A Proposition: The third world curve is largely ours to choose.
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© 2004 Accelerating.org
Action Items
1. Sign up for free Tech Tidbits and Accelerating
Times newsletters at Accelerating.org
2. Attend Accelerating Change (AC2004)
November 5-7 at Stanford, Palo Alto, CA
3. Send feedback to [email protected]
Thank You.
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© 2004 Accelerating.org