How to Be a Strategic Futurist:
An Evolutionary Developmental Perspective
on Accelerating Change
US Army War College
Strategic Leadership 2005
John Smart, President, ASF
Slides: accelerating.org/slides.html
Presentation Outline
1. Introduction
2. Assumptions
3. Two Processes of Change: Evol. and Development
4. Introduction to Accelerating Change
5. Prediction: Expecting the Future
6. Management: Thriving with Change
7. Creation: Making the Future
8. Group Discussion
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© 2005 Accelerating.org
1. Introduction
Acceleration Studies Foundation
Los Angeles
New York
Palo Alto
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ASF (Accelerating.org) is a nonprofit community of 3,100
scientists, technologists, entrepreneurs, administrators,
educators, analysts, humanists, and systems theorists
discussing and dissecting accelerating change.
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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.
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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.
© 2005 Accelerating.org
Brief History of Futures Studies
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1902, H.G. Wells, Anticipations
1904, Henry Adams, A Law of Acceleration
1945, Project RAND (RAND Corp.)
1946, Stanford Research Institute (SRI International)
1962, Arthur C. Clarke, Profiles of the Future
1967, World Future Society, Institute for the Future
1970, Alvin Toffler, Future Shock
1974, University of Houston, Studies of the Future M.S.
1977, Carl Sagan, Dragons of Eden
1986, Eric Drexler, Engines of Creation,
1995, Tamkang U, Center for Futures Studies
1999, Ray Kurzweil, Age of Spiritual Machines
2002, Acceleration Studies Foundation
© 2005 Accelerating.org
Four Types of Futures Studies
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Exploratory (Speculative Literature, Art)
Consensus-Driven (Political, Trade Organizations)
Agenda-Driven (Institutional, Strategic Plans)
Research-Predictive (Stable Developmental Trends)
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The last is the critical one for acceleration studies and
development studies
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It is also the only one generating falsifiable hypotheses
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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.
© 2005 Accelerating.org
Warning: Never Trust a Single Futurist (Including Me)
Never Make Big Decisions Without Using a Futures Network
Each of us sees only a piece of the elephant and is
easily wrong.
A multi-biased network gives you a wider and
deeper map of the possibility space. This will
make you more adaptive, and may make you
more foresighted.
Modern culture spends a lot of time in the past and
present, but very little thinking about personal,
organizational, and global futures.
Learn to fight this increasingly costly bias.
Lesson: Develop your network, map the controversies,
have tolerance for ambiguity, seek good data, notice weak
signals, optimize today but expect emergence. Be skeptical.
Consult the crowd but make your own decisions.
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“You can’t get an unbiased education, so
the next best thing is a multi-biased one.”
 Buckminster Fuller
© 2005 Accelerating.org
Graduate Foresight Programs:
Futures Studies, STS, Roadmapping
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Futures Studies (two U.S. graduate programs)
Science and Technology Studies (30+ U.S. programs)
Tech Roadmapping (five U.S. programs. First PhD
under Mike Radnor at Northwestern in 1998).
Artificial Life, Complexity Science,
Systems Science, Simulation Learning:
All still too early for foresight specializations.
To date only tech roadmapping is falsifiable, and is a
process presently being used for major capital
investment in industry (e.g. ITRS, which began as
NTRS only in 1992).
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Tech Roadmapping is the closest yet to Acceleration
and Development Studies.
© 2005 Accelerating.org
Foresight Development:
Future Prediction, Mgmt, and Creation
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Prediction
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Management
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environmental scanning, competitive intelligence,
networking, scenario development, risk analysis,
hedging, enterprise robustness, planning, matter,
energy, space, and time management systems
Creation
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forecasting methods, metrics, statistical trends, the
history of prediction, technology roadmapping, science
and systems theory, marketing research
personal and entrepreneurial tools for creating
individually preferred futures, research and
development, creative thinking, positive psychology,
social networking, business plan production
© 2005 Accelerating.org
Where are the U.S. College Courses in
Foresight Development?
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Tamkang University
27,000 undergrads
Top-ranked private
university in Taiwan
Like history and
current affairs, futures
studies (15 courses to
choose from) have
been a general
education requirement
since 1995.
Why not here?
© 2005 Accelerating.org
2. Assumptions
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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© 2005 Accelerating.org
The Infopomorphic Paradigm
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The universe is a physical-computational system.
We exist for information theoretic reasons.
We’re here to discover, think/emote, and create.
© 2005 Accelerating.org
The MESTI Universe
Matter, Energy, Space, Time  Information
Increasingly Understood
 Poorly Known
MEST Compression/Density/Efficiency drives
accelerating change.
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© 2005 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.
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© 2005 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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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
© 2005 Accelerating.org
Strategic/Integral Foresight:
Skill Sets and Processes
True
What Is
It/Its
Greeks
Good
What ‘We’ Want
Pronouns
We/He/She/You
Beautiful
What ‘I’ Want
I/Me
Professional Skill Sets
Discovery
Management
Creativity
Universal
Social
Individual
Processes
Development
Convergence
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Statics/Dynamics
Law/Emergence
Evolution
Divergence
© 2005 Accelerating.org
Strategic/Integral Thinking:
Edward De Bono’s Six Thinking Hats
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It/Its
We/He/She/You
I/Me
White
Yellow
Red
(Facts)
(Social Positive)
(Intuition)
Blue
Black
Green
(Process)
(Social Negative)
(Creative)
© 2005 Accelerating.org
Strategic/Integral Maps:
Ken Wilber’s Process/Mgmt Quadrants
Computational Processes
We need foresight in all
quadrants (processes and
management tests).
• All drive change.
• None can be reduced to the others
• There are no others as basic!
Management/Validity Tests
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© 2005 Accelerating.org
Types of Intelligence:
Gardner’s ‘Frames’/ ‘Modules’
Gardner has developed research and
metrics for eight different “frames” or
“modules” of human capacity. A great
way to look at thinking.
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© 2005 Accelerating.org
Types of Intelligence:
Wilber’s ‘Lines/Vectors’
I
Intrapersonal/Self-Identity
 Body/Kinesthetic/Health
 Cognitive/Emotional/Needs
 Creativity/Creative
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It (MEST Mgmt)
Visual/Spatial
 Aural/Musical
 Spatio-Temporal
 Material-Energetic
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We (Social Mgmt)
Interpersonal/Social-Identity
 Linguistic/Social-Narrative
 Moral/Culture/Social-Relation
 Intimacy/Social-Care
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Its
Nature/Systems Info
 Logic/Mathematical Info
 Object Relations/Structure
 Discovery/Predictive
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Meta/Transcendent/Spiritual Attractor
Wilber proposes at least twice as many intelligence lines/dimensions than Gardner.
I’ve mapped the ones that I think are justified to his quadrants, above.
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Wilber also proposes all lines follow a developmental vector, that the higher levels of
all lines look spiritual, and that the spiritual line is a convergent intelligence attractor
that continually seeks to look meta (above, beyond) all the other lines.
© 2005 Accelerating.org
Vectors of Development:
Sequential Growth Stages
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Stages are probability functions, not discrete “levels” of development. They are
sequential and directional, but you can regress with abnormal trauma or deterioration.
© 2005 Accelerating.org
Gilligan’s Stages
of Female Moral Development
Stage
Sample Question:
Is abortion a woman’s right?
Universal Care
“Yes, sometimes” (birth
defects, etc.)
(integral, weighted, plural)
(culture, conformity, code)
“No” (against dominant
culture/code/convention)
Selfish
“Yes” (my body, my choice)
Care
(ego, individual)
Stages are probabilities, but they are sequential and directional.
This is reasonably good research.
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Carol Gilligan
© 2005 Accelerating.org
Debser’s Stages
of Cultural Development
Stage
Sample Belief System
Integral
“Many things change the world.”
Rational
“Science changes the world.”
Mythic
“Other’s power changes the world.”
Magic
“My wishes change the world.”
Archaic
“Nothing/work changes the world.”
Some stage conceptions have a lot less evidence at present,
but seem good candidates for further research.
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Eugene Debser
© 2005 Accelerating.org
Maslow’s Hierarchy of Self-Needs
Smart’s Hierarchy of Socioeconomics
Biological Learning Stages
Self-Transcendence
(Religion & Death)
Technological Learning Stages
Bio-Transcension?
Digital Twin IT Society
Valuecosm IT Society
Network IT Society
/ Property
Manufacturing Society
Agricultural Society
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© 2005 Accelerating.org
3. Two Processes of Change:
Evolution and Development
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
© 2005 Accelerating.org
Evolution vs. Development
“The Twin’s Thumbprints”
Consider two identical twins:
Thumbprints
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Brain wiring
Evolution drives almost all the unique local patterns.
Development creates the predictable global patterns.
© 2005 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.
© 2005 Accelerating.org
How Many Eyes Are
Developmentally Optimal?
Evolution tried this experiment.
Development calculated an operational optimum.
Some reptiles (e.g. Xantusia vigilis, and certain skinks)
still have a parietal (“pineal”) vestigial third eye.
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© 2005 Accelerating.org
How Many Wheels are Developmentally
Optimal on an Automobile?
Examples: Wheel on Earth. Social computation device.
Diffusion proportional to population density and diversity.
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© 2005 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.
© 2005 Accelerating.org
Political Polarities:
Innovation 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 (Maoism).
Evolutionary generativity (innovation) without
sustainability creates chaos, entropy, a destruction that
is not naturally recycling/creative (Anarchocapitalism).
© 2005 Accelerating.org
4. Introduction to Accelerating Change
From the Big Bang to Complex Stars:
“The Decelerating Phase” of Universal ED
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© 2005 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.
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© 2005 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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Developmental Singularity?
8B yrs: Earth
© 2005 Accelerating.org
Punctuated Equilibrium (in Biology,
Technology, Economics, Politics…)
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Eldredge and Gould
(Biological Species)
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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 © 2005 Accelerating.org
Different Kinds of Accelerations:
Efficiency vs. Transformation
Business Week’s First Edition, October 1929:
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IBM has an ad for “electric sorting machines.”
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PG&E has an ad announcing natural gas
powered factories in San Francisco.
Could we have predicted that one of these
technologies would continually transform itself
while another would experience accelerating
efficiencies but, on the surface, be
unchanged?
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© 2005 Accelerating.org
Lesson: Maintaining Equilibrium is Our
80% Adaptive Strategy
While we try unpredictable evolutionary strategies to
improve our intelligence, interdependence, and
resiliency, these won’t always work. What is certain is
that successful solutions always increase MEST
efficiency, they “do more with less.” Strategies to
capitalize on this:
 Teach efficiency as a civic and business skill.
 Look globally to find resource-efficient solutions.
 Practice competitive intelligence for MEST-efficiency.
 Build a national culture that rewards refinements.
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Examples: Brazil's Urban Bus System. Open Source
Software. Last year’s mature technologies. Recycling.
30 million old cell phones in U.S. homes and businesses.
© 2005 Accelerating.org
A Saturation Lesson:
Biology vs. Technology
How S Curves Get Old
Resource limits in a niche
Material
Energetic
Spatial
Temporal
Competitive limits in a niche
Intelligence/Info-Processing
No Known or Historical Limits to Information Acceleration
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
© 2005 Accelerating.org
The Technological Singularity Hypothesis
Each unique physicalcomputational substrate
appears to have its own
“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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© 2005 Accelerating.org
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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© 2005 Accelerating.org
Something Curious Is Going On
Unexplained.
(Don’t look for this in your physics or information theory texts…)
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© 2005 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
© 2005 Accelerating.org
Four Pre-Singularity Subcycles?
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A 30-year cycle, from 1990-2020
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A 20-year cycle, from 2020-2040
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CUI personality capture (weak uploading),
Mature Self-Reconfig./Evolutionary Computing.
2050: Era of Strong Autonomy
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CUI network, Biotech, not bio-augmentation,
Adaptive Robots, Peace/Justice Crusades.
A 10-year cycle, from 2040-2050
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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.
© 2005 Accelerating.org
Macrohistorical Singularity Books
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The Evolutionary Trajectory, 1998
Trees of Evolution, 2000
Singularity 2130 ±20 years
Singularity 2080 ±30 years
© 2005 Accelerating.org
Macrohistorical Singularity Books
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Why Stock Markets Crash, 2003
The Singularity is Near, 2005
Singularity 2050 ±10 years
Singularity 2050 ±20 years
© 2005 Accelerating.org
“Unreasonable” Effectiveness and
Efficiency: Wigner and Mead
The Unreasonable Effectiveness of Mathematics in the
Natural Sciences, Nobel Laureate Eugene Wigner, 1960
After Wigner and Freeman Dyson’s work in 1951, on symmetries
and simple universalities in mathematical physics.
F=ma
F=-(Gm1m2)/r2
E=mc2
W=(1/2mv2)
Commentary on the “Unreasonable Efficiency of Physics
in the Microcosm,” VSLI Pioneer Carver Mead, c. 1980.
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In 1968, Mead predicted we would create
much smaller (to 0.15 micron) multi-million
chip transistors that would run far faster and
more efficiently. He later generalized this
observation to a number of other devices.
© 2005 Accelerating.org
Example: Holey Optical Fibers
Lasers today can made cheaply only in some
areas of the EM spectrum, not including, for
example, UV laser light for cancer detection
and tissue analysis. It was discovered in 2004
that a hollow optical fiber filled with hydrogen
gas, a device known as a "photonic
crystal," can convert cheap laser light to the
wavelengths previously unavailable.
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Above: SEM image of a photonic crystal fiber. Note periodic
array of air holes. The central defect (missing hole in the middle)
acts as the fiber's core. The fiber is about 40 microns across.
This conversion system is a million times (106) more energy
efficient than all previous converters. These are the kinds of
jaw-dropping efficiency advances that continue to drive the
ICT and networking revolutions.
Such advances are due even more to human discovery (in
physical microspace) than to human creativity, which is why
they have accelerated throughout the 20th century, even as we
remain uncertain exactly why they continue to occur. © 2005 Accelerating.org
Understanding the Lever of ICT
"Give me a lever, a fulcrum,
and place to stand and I
will move the world."
Archimedes of Syracuse
(287-212 BC), quoted by
Pappus of Alexandria,
Synagoge, c. 340 AD
“The good opinion of mankind, like the lever of
Archimedes, with the given fulcrum [representative
democracy], moves the world.” (Thomas Jefferson, 1814)
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The lever of accelerating information and communications
technologies (in outer space) with the fulcrum of physics
(in inner space) increasingly moves the world.
(Carver Mead, Seth Lloyd, George Gilder…)
© 2005 Accelerating.org
Our Historical Understanding of
Accelerating Change
In 1904, we seemed nearly ready
to see intrinsically accelerating
progress. Then came mechanized
warfare (WW I, 1914-18, WW II,
1939-45), Communist oppression
(60 million deaths). 20th century
political deaths of 170+ million
showed the limitations of humanengineered accelerating progress models.
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Today the idea of accelerating progress remains in the
cultural minority, even in first world populations. It is viewed
with interest but also deep suspicion by a populace
traumatized by technological extremes, global divides, and
economic fluctuation.
Zbigniew Brzezinski, Out of Control, 1993
© 2005 Accelerating.org
Acceleration Quiz
Q: Of the 100 top economies in the world, how
many are multinational corporations and how
many are nation states?
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© 2005 Accelerating.org
Acceleration Quiz
Q: Of the 100 top revenue generating entities in
the world, how many are multinational
corporations and how many are nation states?
76 MNC’s and 24 Nations.
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GBN, Future of Philanthropy, 2005
© 2005 Accelerating.org
Acceleration Quiz
Q: How many of the lowest net-worth Americans
would it take to approximate Bill Gate’s net
worth? (296 million Americans in 2005)
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© 2005 Accelerating.org
Acceleration Quiz
Q: How many of the lowest net-worth Americans
would it take to approximate Bill Gate’s net
worth?
Roughly 110 million Americans in 1997,
when his net worth was $40 billion. At $30
billion presently (2005), Mr. Gates ranks
roughly as the 60th largest country, and the
55th largest business. When MSFT went
public in 1986, Bill was worth $230 million.
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NYU economist Edward Wolff (See also Top Heavy, 2002)
© 2005 Accelerating.org
Acceleration Quiz
Q: Disney and Sony (respectively) produce and
launch one new product every _________?
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© 2005 Accelerating.org
Acceleration Quiz
Q: Disney and Sony (respectively) produce and
launch one new product every _________?
Three minutes for Disney.
Twenty minutes for Sony.
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Elizabeth Debold, What is Enlightenment?, March-May 2005
© 2005 Accelerating.org
World Economic
Performance
GDP Per Capita in
Western Europe,
1000 – 1999 A.D.
This curve looks
quite smooth on a
macroscopic scale.
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Notice the “knee of
the curve” occurs at
the industrial
revolution, circa
1850.
© 2005 Accelerating.org
Oil Refinery (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.
© 2005 Accelerating.org
Understanding Process Automation
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Perhaps 80% 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 progress.”
Human contribution (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
© 2005 Accelerating.org
Automation and Job Disruption
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 Economy.
America lost about 2 million industrial jobs, mostly to China.
 China lost 15 million ind. jobs, mostly to machines. (Fortune)
 Despite the shrinking of America's industrial work force, the
country's overall industrial output increased by 50% since
1992. (Economist)
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“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)
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"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
© 2005 Accelerating.org
Back to the Greek Future
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Greece built an enviable empire on the back
of human slaves.
21C humanity is building an even more
enviable one on the back of our robotic
servants.
Expect machine emancipation, too.
“The more things change, the more some things
stay the same.”
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Three Hierarchical Systems
of Social Change

Technological (dominant since 1950!)
“It’s all about the technology” (what it enables, how
inexpensively it can be developed)
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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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New York
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.
© 2005 Accelerating.org
5. Prediction: Expecting the Future
Smart’s Laws of Technology
1. Tech learns ten million times faster than you do.
(Electronic vs. biological rates of evolutionary development).
2. Humans are selective catalysts, not controllers, of
technological evolutionary development.
(Regulatory choices. Ex: WMD production or transparency,
P2P as a proprietary or open source development)
3. The first generation of any technology is often
dehumanizing, the second is indifferent to humanity,
and with luck the third becomes net humanizing.
(Cities, cars, cellphones, computers).
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Humans are Prediction Systems
“Our brain is structured for constant forecasting.”
Jeff Hawkins,
Inventor, PalmPilot,
CTO, Palm Computing
Founder, Redwood Neurosciences Institute
Author, On Intelligence: How a New
Understanding of the Brain will Lead to the
Creation of Truly Intelligent Machines, 2004
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
The Prediction Wall and
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 Futures Studies.
Los Angeles
New York
Palo Alto
(Kahn & Wiener, 1967).
© 2005 Accelerating.org
Classic Predictable Accelerations:
Moore’s Law
Los Angeles
New York
Palo Alto
Moore’s Law derives from two predictions in 1965 and 1975 by Gordon
Moore, co-founder of Intel, (and named by Carver Mead) that
computer chips (processors, memory, etc.) double their complexity
every 12-24 months at near constant unit cost.
This means that every 15 years, on average, a large number of
technological capacities (memory, input, output, processing) grow by
1000X (Ten doublings: 2,4,8…. 1024). Emergence!
There are several abstractions of Moore’s Law, due to miniaturization
of transistor density in two dimensions, increasing speed (signals
have less distance to travel) computational power (speed × density).
© 2005 Accelerating.org
Ray Kurzweil: A Generalized Moore’s Law
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Transistor Doublings (2 years)
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2005 Accelerating.org
Processor Performance (1.8 years)
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2005 Accelerating.org
DRAM Miniaturization (5.4 years)
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2005 Accelerating.org
Dickerson’s Law: Solved Protein Structures
as a Moore’s-Dependent Process
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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New York
Palo Alto
Macroscopically, the curve has been quite consistent.
© 2005 Accelerating.org
Many Tech Capacity Growth Rates Are
Independent of Socioeconomic Cycles
There are many natural cycles:
Plutocracy-Democracy, Boom-Bust,
Conflict-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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Palo Alto
Conclusion: Human-discovered,
Not human-created complexity here.
Not 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
© 2005 Accelerating.org
IT’s Exponential Economics
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2005 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
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Angus Maddison’s
Phases of Capitalist Development, 1982*
Network/Services/KM Society
Society of Intangible Needs (“Weightless Economy”)
Network 1.0
“McJobs” & Service
65% of Jobs, 2000’s
Network 2.0
New Middle Class
40% of Jobs, 2030’s
Network 3.0
Consolidation Again
15% of Jobs, 2060’s
Manufacturing/Information Society
Society of Tangible Needs (“Property Economy”)
Manufacturing 1.0
Exploitive Jobs
50% of Jobs, 1900’s
Manufacturing 2.0
New Middle Class
35% of Jobs, 1950’s
Manufacturing 3.0
Offshoring/Globalizing
14% of Jobs, 2000’s
Agricultural Society
Society of Basic Needs (“Food/Shelter Economy”)
Los Angeles
New York
Palo Alto
Agriculture 1.0
Subsistence Jobs
80% of Jobs, 1820’s
Agriculture 2.0
Family Farms
50% of Jobs, 1920’s
Agriculture 3.0
Corporate Farms
2% of Jobs, 1990’s
*Also Pentti Malaska’s Funnel Model of Societal Transition, 1989/03
© 2005 Accelerating.org
Network Economy 1.0
Q: Which is a larger monetary flow in Latin America today,
the bottom-up green or the top-down purple column?
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Palo Alto
Remittances
(From Guest Workers in
U.S. and Canada)
Foreign Direct
Investment
(Corporate)
NGO’s
(Nonprofit Contribs)
Government Aid
(IMF, WB, G8, USAID)
© 2005 Accelerating.org
Network Economy 1.0
Q: Which is a larger monetary flow in Latin America today,
the bottom-up green or the top-down purple column?
Remittances
(From Guest Workers in
U.S. and Canada)
Foreign Direct
Investment
(Corporate)
NGO’s
(Nonprofit Contribs)
Government Aid
(IMF, WB, G8, USAID)
A: Remittances, since 2003. This may be a permanent
shift. Shows what could happen in Africa, Russia, other
emigrating (“brain drain”) nations.
Los Angeles
New York
Palo Alto
Future of Philanthropy, GBN, 2005
© 2005 Accelerating.org
The Voluntary Future
Lifetime hours trends:
1880
1995
2040
Total Available (after eating, 225,900
sleeping, etc.)
298,500 321,900
Worked to earn a living
182,100
122,400 75,900
Balance for Leisure and
Voluntary Work
43,800
176,100 246,000
Prediction: Great increase in voluntary activities. Culture,
entertainment, travel, education, wellness, nonprofit service,
humanitarian and development work, the arts, etc.
Los Angeles
New York
Palo Alto
Source: The Fourth Great Awakening and the Future of Egalitarianism,
2000, Robert Fogel (Nobel-prize-winning economist, founder of the field of
cliometrics, the study of economic history using statistical and
mathematical models)
© 2005 Accelerating.org
Many Accelerations are:
1) Underwhelming or 2) Logistic (“S” curves)
Some Underwhelming Exponentials:
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Palo Alto
Productivity per U.S. worker hr has improved 500%
over 75 years (1929-2004, 2% per yr)
Business investment as % of U.S. GDP is flat at 11%
over 25 years.
Nondefense R&D spending as % of First World GDP
is up 30% (1.6 to 2.1%) over 21 years (1981-2002).
Technology spending as % of U.S. GDP is up 100%
(4% to 8%) over 35 years (1967-2002)
BusinessWeek, 75th Ann. Issue, “The Innovation Economy”, 10.11.2004
© 2005 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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New York
Palo Alto
© 2005 Accelerating.org
So What Stopped the Growth?
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Palo Alto
© 2005 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 OPEC (1973)
2. Stunning energy efficiency of each new
generation of technological system
3. Saturation of human population and
human needs for tech transformation
Royal Dutch/Shell notes that energy use
declines dramatically proportional to
per capita GDP in all cultures.
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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New York
Palo Alto
Expect such MEST efficiencies in energy technology to be multiplied
dramatically in coming years. Technology is becoming more energyeffective in ways very few of us currently understand.
© 2005 Accelerating.org
Global Energy Use Saturation:
Energy Consumption Per Capita
When per capita GDP reaches:
• $3,000 – energy demand
explodes as industrialization
and mobility take off,
• $10,000 – demand slows as the
main spurt of industrialization is
completed,
• $15,000 – demand grows more
slowly than income as services
dominate economic growth and
basic household energy needs
are met,
• $25,000 – economic growth
requires little additional energy.
Later developers, using
“leapfrogging technologies”,
require far less time and energy
to reach equivalent GDP.
Los Angeles
New York
Palo Alto
Energy Needs, Choices, and Possibilities: Scenarios to 2050, Shell Intnat’l, 2001
© 2005 Accelerating.org
Longer Term Example:
Solar Energy
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New York
Palo Alto
Twenty to fifty year development horizon.
5-10% efficiencies at present. Need 50%.
Need good, cheap energy storage systems.
© 2005 Accelerating.org
Accelerating Ephemeralization and the
Increasingly Weightless Economy
In 1938 (Nine Chains to the Moon), poet and polymath
Buckminster Fuller coined "Ephemeralization,” positing
that in nature, "all progressions are from material to
abstract" and "eventually hit the electrical stage."
(e.g., sending virtual bits to do physical work)
Due to principles like superposition, entanglement,
negative waves, and tunneling, the world of the quantum
(electron, photon, etc.) appears even more ephemeral than
the world of collective electricity.
In 1981 (Critical Path), Fuller called ephemeralization, "the invisible chemical,
metallurgical, and electronic production of ever-more-efficient 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”
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Palo Alto
This trend has also been called “virtualization,” “weightlessness,” and
Matter, Energy, Space, Time (MEST) compression, efficiency, or density.
© 2005 Accelerating.org
The Symbiotic Age
Coevolution between Saturating Humans
and Accelerating Technology:
 A time
when computers “speak our language.”
 A time when our technologies are very
responsive to our needs and desires.
 A time when humans and machines are
intimately connected, and always improving
each other.
 A time when we will begin to feel “naked”
without our computer “clothes.”
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
The Start of Symbiosis: The Digital Era
With the advent of the transistor (June 1, 1948), the
commercial digital world emerged.
New problems have emerged (population, human rights,
asymmetric conflict, environment), yet we see solutions
for each in coming waves of technological globalization.
“The human does not change, but our house
becomes exponentially more intelligent.”
We look back not to Spencer or Marx and their
human-directed Utopias, but to Henry Adams,
who realized the core acceleration is due to
the intrinsic properties of technological systems.
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New York
Palo Alto
Michael Riordan, Crystal Fire, 1998
© 2005 Accelerating.org
An ICT Attractor:
The Conversational User Interface (CUI)
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New York
Palo Alto
Google’s cache (2002)
As we watch Windows 2004
become Conversations 2020…
Convergence of Infotech and Sociotech
© 2005 Accelerating.org
Why Will You Use An
“Agent Interface” in 2020?
Ananova, 2002
Los Angeles
New York
Palo Alto
“Working with Phil” in Apple’s Knowledge Navigator Ad, 1987
© 2005 Accelerating.org
Social Software, Lifelogs
Gmail preserves, for the first time, everything we’ve ever
typed. Gmailers are all bloggers (who don’t know it).
Next, some of us will 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.
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
The Valuecosm
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New York
Palo Alto
Microcosm, Telecosm (Gilder)
Datacosm (Sterling)
Valuecosm (Smart)
Recording and Publishing DT Preferences
Avatars that Act and Transact Better for Us
Mapping Positive Sum Social Interactions
Much Potential For Early Abuse (Advice)
Next Level of Digital Democracy (Holding
Powerful Plutocratic Actors Accountable)
Early Examples: Social Network Media
© 2005 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.”
Successive approximation, seamless
integration, subtle transition.
When you can shift your own conscious
perspective between your electronic and
biological components, the encapsulation
and transcendence of the biological may
begin to feel like only growth, not death.
Los Angeles
New York
Palo Alto
We wouldn’t have it any other way.
Greg Panos (and Mother)
PersonaFoundation.org
© 2005 Accelerating.org
Personality Capture
In the long run, we become seamless with our machines.
No other credible long term futures have been proposed.
Los Angeles
New York
Palo Alto
“Technology is becoming organic. Nature is becoming
technologic.” (Brian Arthur, SFI)
© 2005 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?)
Los Angeles
New York
Palo Alto
• Coming: Linguistic User Interface (LUI)
Persuasive Computing, and
Personality Capture
© 2005 Accelerating.org
Human-Competitive Machine Intelligence:
Automated Trading Comes of Age
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New York
Palo Alto
As of 2005, automated computer trading models
(algorithmic, black box, and program trading) now
execute more than half of all U.S. stock trades.
From 2003 to 2005, Banc of America Securities LLC
let go of half their human traders, while increasing
trading volume 160%.
All major brokers are spending
millions on this technology.
Minor brokers coming next.
We are now seeing the
beginning of the AI Age in the
financial community.
BusinessWeek, 4.18.2005
© 2005 Accelerating.org
Robo sapiens
“Huey and Louey”
AIST and Kawada’s HRP-2
(Something very cool
about this algorithm…)
Los Angeles
New York
Palo Alto
Aibo Soccer
© 2005 Accelerating.org
Ubiquitous Sensing, Geospatial Web, and
Accelerating Public Transparency
David Brin’s “Panopticon”
The Transparent Society, 1998
Hitachi’s mu-chip:
RFID for paper
currency
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
MEST Compression as a Developmental
Attractor: Don’t Bet Against It!
Balloon Satellites: Disruptive Tech?
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.
Los Angeles
New York
Palo Alto
Q1: Which apps have been
discussed?
a.
Border monitoring
b.
City monitoring
c.
Urban broadband
d.
Early warning radar
Q2: Why are satellites presently
failing against the wired world?
Latency, bandwidth, launch costs.
MEST compression always wins.
© 2005 Accelerating.org
Tomorrow’s Fastspace:
User-Created 3D Persistent Worlds
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Los Angeles
New York
Palo Alto
Future Salon in Second Life
Streaming audio for main speaker, chat for others.
Streaming video added 2005.
Cost: $10 for life + fast graphics card ($180)
© 2005 Accelerating.org
U.S. Transcontinental Railroad:
Promontory Point Fervor
Built mostly by hardworking immigrants
The Network of the 1880’s
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
IT Globalization (2000-2020):
Promontory Point Revisited
The more things change,
the more some things
stay the same.
The 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.
Los Angeles
New York
Palo Alto
Consider what this means for the goals of U.S. business and
education: Global management, partnerships, and collaboration.
© 2005 Accelerating.org
Information Age:
Staggered Closing of Global Divides
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Los Angeles
New York
Palo Alto
Digital divide is already closing fast. 77% of
the world now has access to a telephone*.
Innovation leader: Grameen Telecom
Income divide may be closing the next
fastest. First world plutocracy still increasing,
but we are already “rationalizing” global
workforce wages in the last decade*.
Education divide may close next (post-LUI)
Power divide likely to close last. Political
change is the slowest of all domains.
*World Bank, 2005
© 2005 Accelerating.org
Our Generation’s Theme
First World Saturating
Third World Uplifting
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Empire Progression
(Note the West-Far East Trajectory)
Japan
(Temporary: Pop density,
Few youth, no resources.
East Asian Tigers
(Taiwan
Hong Kong
South Korea
Singapore)
American
India
China
Los Angeles
New York
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
© 2005 Accelerating.org
A Prediction:
The Sputnik of Networking 2.0 Society
Los Angeles
New York
Palo Alto
Sputnik
Humbot
U.S.-Surpassing
Space/Defense Tech
Human-Surpassing
Security/Warfighting Tech
© 2005 Accelerating.org
MEST Compression/Capacity Metric
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New York
Palo Alto
How proficient can the Humbot be vs. a
human soldier?
Running down a perp, through any terrain,
and bringing him in. The Robocop objective.
Network of 1,000 mesh sensors monitoring a
square mile for the bot.
Teleoperated or semi-autonomous.
“Shock and Awe on a Somalian Streetcorner”
© 2005 Accelerating.org
Will the DoD Make the Humbots of 2030?
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New York
Palo Alto
It won’t be Europe or Japan (Post-Military)
Could be Taiwan/China/India/Korea or some
collaboration thereof. Will Japan license IP?
When (not if) will soldiering be consolidated to
1/5 the numbers we see today? 2050? 2090?
Will the U.S. still be the #1 provider of world
security?
Will we partner intelligently or try to go it
alone?
The lead is ours to keep or lose.
© 2005 Accelerating.org
Strategic Proposal:
Innovate, Collaborate, “Fight for 40%”
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New York
Palo Alto
IBM-Lenovo (Chinese Computer Company)
laptop deal. IBM retains 18% ownership.
Is this a true innovation partnership?
Can make the deal so independent that it
must be.
Technology interdependence leads
corporate interdependence which then leads
political interdependence (last) today globally.
Not usually the reverse.
© 2005 Accelerating.org
6. Management: Thriving with Change
We Have Two Options:
Future Shock or Future Shaping
“We need a pragmatic optimism, a cando, change-aware attitude. A balance
between innovation and preservation.
Honest dialogs on persistent problems,
tolerance of imperfect solutions. The
ability to avoid both doomsaying and
paralyzing adherence to the status quo.”
― David Brin
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Automation Development Creates
Massive Economic-Demographic Shifts
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Palo Alto
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”)
© 2005 Accelerating.org
S-Curves and Creative Destruction
New Old Europe (Network 1.0) Spain’s Recent Creation of TwoTier Workforce. “McJobs” Under
Newly Creatively Destructive
40). (20  5% Unemployment)
Ireland, New E.U. (10 on flat tax)
Los Angeles
New York
Palo Alto
New Asia (Network 1.0)
Very High CD Index
Taiwan, Hong Kong, China,
Korea, Singapore, Malaysia,
India, Vietnam, etc.
United States (Network 0.8)
50% CD Index
50% of top 25 companies no
longer top after 25 years.
We are IT-challenged vs. Asia
Japan (Network 1.0)
Old Europe (Mfg 3.0)
Low/Very Low CD Index
Germany (13% unemployment)
Italy (11% unemployment)
France (10% unemployment)
© 2005 Accelerating.org
Taiwan’s Example
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Palo Alto
Taiwan requires university undergraduates to
take courses in Futures Studies.
Taiwan owns 46,000 contract factories in
China (mutually assured economic
destruction).
Taiwan has become the IT hardware
manufacturing capital of the world.
Taiwan has the highest degree of economic
creative destruction in the world.
© 2005 Accelerating.org
Our Greatest Strategic Interest:
Managing Globalization
“America has had 200 years to
invent, regenerate, and calibrate
the balance that keeps markets free
without becoming monsters. We
have the tools to make a difference.
We have the responsibility to make
a difference. And we have a huge
interest in making a difference.
Managing globalization is… our
overarching national interest today
and the political party that
understands that first… will own the
real bridge to the future.”
Los Angeles
New York
Palo Alto
Thomas Friedman, The Lexus and
the Olive Tree: Understanding
Globalization (2000).
© 2005 Accelerating.org
Globalization Eras
Globalization I: 1800’s – WWI
Mechanism:
Industrial Revolution, cheap transportation
Backlash Ideologies:
Communism, Socialism, Fascism
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Globalization Eras
Globalization II: 1980’s – Present
Mechanism:
Information Revolution, cheap communications
Backlash Ideologies:
Fundamentalism, civil disobedience, crime, ecoactivism
Examples: Sem Teto, Hugo Chavez
Los Angeles
New York
Palo Alto
© 2005 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:
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Palo Alto
 Network Memes and Traditions like Free Markets,
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)
© 2005 Accelerating.org
Technological Globalization: Losers
Some of the longer term losers:
 Non-Network Memes and Traditions like
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)
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Technological Globalization: Uncertains
Most elements of modern society are evolutionary,
meaning they remain ‘indeterminate’ actors which may or
may not become winners. Their fate depends 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)
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Globalization Management
Backlash forces have to be kept in check by:
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Global tech innovation and diffusion
Global economic growth
Global political
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Palo Alto
accountability
transparency
fair policies
minimal government (maximizing tech and
economic development)
security
© 2005 Accelerating.org
How can the U.S. Military Globalize?
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Palo Alto
America’s Army (Promote Foreign Players)
Inderdependent Intel Community
More Guest Soldiers/Exchanges
International & Joint Wargames
Global Arms Trade Oversight
Develop and Install “Security Franchises”
Global R&D Funding for Security Enabling
Factors (Networked Weapons, Sensors,
Autonomy/DARPA Grand Challenge)
© 2005 Accelerating.org
The Pentagon’s New Map
A New Global Defense Paradigm
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Shrinking the Disconnected Gap
The Computational “Ozone Hole”
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Interdependency/Development Metrics
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Gap Countries
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Child and Infant Mortality Rates (Lagging Indicators)
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Infrastructure
Information Access (Culturally Appropriate)
Core Countries
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Palo Alto
“The primary global currencies by which the “quick and
privileged” negotiate change with the “slower and deprived”
(Pete Lantz)
Tech, Econ, Cultural Exchange Bandwidth
Guest Worker Programs/Visa Reform
© 2005 Accelerating.org
Immunity/Security Metrics
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Core and Gap
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Degree of Transparency
Sensor Ubiquity
Redundancy/Robustness
Authentication/Secure Public ID
Responsiveness (to catastrophe)
Example: How rapidly can bombsites be cleaned up?
Rebuilt? Value in differential responsiveness?
Iraq provides an opportunity to run the experiment.
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Interdependence/Development Metric:
Measurable Exponential Value (MEV)
Gap Examples (Iraq):
 Communications (cellphones)
 Lighting (digital solid state)
 Energy (centralized scale, subsidized deflationary
prices; decentralized storage and generation)
Example: Donkey cart generators
 Food storage, culinary, and women’s needs
 Sports / Youth Fads
 Portable CD Players/local music ($10 at Wal-Mart)
 Security (networked cameras; camera traps)
Culturally-dependent: Britain vs. S. Africa vs. U.S.
 Public access radio and TV stations
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
“Planning the Peace” in Iraq:
The Say-Do Development Chasm
2,600 Iraqi Development Projects Promised
160 under way by mid-2004 (Time, July 2004)
Of all of these, communications may have been our
biggest lost MEV opportunity (public forum and
exchange).
We wired ourselves superbly (CPOF) but by end of 2004
we still had not wired into the populace, or even
helped them to wire themselves, in exponential
fashion. Can do one-to- many (low power radio/TV) if
one-to-one (cellphones) is too risky for initial
deployment.
Los Angeles
New York
Palo Alto
© 2005 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.
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
DARPA R&D Ideas
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Networked Lethal and Nonlethal Weapons
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Tele-Operated and Autonomous Control
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Security and Logistics
Mesh Sensors/Camera Traps
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Los Angeles
New York
Palo Alto
Converting Offensive to Inherently Defensive
Security Assets
Border/Interior Security
© 2005 Accelerating.org
Interagency Cooperative R&D Ideas
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Firefighting (10’s of Billions/year)
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Microwave Military Sats (10’s of Billions/year)
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New York
Palo Alto
Only the DoD has the munitions for firebreaks at
will. Legal and jurisdictional barrier to overcome.
More legal and jurisdictional barriers. Expanding
the concept of National and International Security.
© 2005 Accelerating.org
Hurricane Control:
New DoD/NASA/NOAA Security Mission?
Hurricane Ivan: $11B in property
damage. 11 named storms in 10
months in 2004, 7 caused
damage in U.S.
NOAA expects decades of
hurricane hyperactivity.
Ross Hoffman, use Solar Powered Satellites (SPS’s).
In 1968, Peter Glaser, microwave-relay SPS’s for
power on earth, tuned away from climate. These would
be tuned to water vapor (like microwave oven). Low
pressure centers disruptible by atmospheric heating.
Very sensitive to hi pressure side steering. Cyclones,
monsoons, blizzards, possibly even tornados.
Los Angeles
New York
Palo Alto
Research: Russian mylar mirrors, 1993, 1999 (failed).
23 m mirror (above), 5 km light circle on the ground.
Arrays would raise surface temp. several degrees.
“Controlling Hurricanes,” Scientific American, 10.2004
© 2005 Accelerating.org
Underground AHS/TBM :
DARPA/Army Corps Project?
May be significantly cheaper than air taxi transport. TBMs growing
exponentially. No visual blight, safe, reclaim surface real estate. 10X
present capacity under our cities. Requires IV’s and ZEV’s (2025+)
Los Angeles
New York
Palo Alto
“Underground Automated Highway Systems: 2030 Vision,” John Smart, 2005
© 2005 Accelerating.org
Tech Roadmappers Carefully Watch
Efficiency/Cost/Capacity Curves
Toshiba Li-Ion Nanobattery
80% recharge in 60 seconds
99% duty after 1,000 cycles
Reliable at temp extremes
Cost competitive
What Might This Enable?
New consumer wearable
and mobile electronics
 Military apps
 Plug-in hybrids at home and
filling stations (“90% of an
electric vehicle economy”)
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“The future’s already here. It’s just not
evenly distributed yet.” ― William Gibson
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Tools for Networking 1.0:
Social Network Analysis
Note the linking nodes in these “small world”
(not scale free) networks.
Los Angeles
New York
Palo Alto
“Chains of Affection,” Bearman & James Moody, AJS V110 N1, Jul 2004
© 2005 Accelerating.org
Networking Books
Los Angeles
New York
Palo Alto
Linked, Albert-Laszlo Barabasi, 2003
Six Degrees, Duncan Watts, 2003
© 2005 Accelerating.org
Create Your Own Network:
Consider Ben Franklin’s Junto
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Met every Friday. The group invented:
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Broad Interests, Narrow Tasks.
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the first subscription library in North America
the most advanced volunteer fire department
the first public hospital in Pennsylvania,
an insurance company, a constabulary,
improved streetlights, paving
the University of Pennsylvania.
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Scientist
Inventor
Businessman
Statesman
© 2005 Accelerating.org
Social Networking:
Implications for Leaders
Los Angeles
New York
Palo Alto
How to Maximize Adaptation:
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Find the informal (hidden) structure of the landscape. (Data
Mining)
Broad Landscape: Community of Interest (Generalized)
Deep Landscape: Community of Practice (Specialized)
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How connected are you in these landscapes? (Network
Analysis)
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How many close neighbors do you have in your small worlds
network? Optimized to your personal bandwidth? (Efficiency)
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How many of your neighbors are bridging links to the whole
system? (Network Analysis)
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This will determine how rapidly feed forward and feedback can
propagate to you across the entire landscape.
(Robustness, Scanning, Ability to Influence Change)
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Reorganize your network! Be near the center of the topics you
care about. Be broad and selectively deep.
© 2005 Accelerating.org
The NBIC Report and Conferences
Converging Technologies for Improving Human Performance:
Nanotechnology, Biotechnology, Information Technology and Cognitive Science
Edited by Mike Roco and William Sims Bainbridge,
National Science Foundation, 2002 (NSF/DoC Sponsored Report)
www.wtec.org/ConvergingTechnologies/
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
“NBICS”: 5 Choices for Strategic
Technological Development
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Palo Alto
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 spend lots of R&D or marketing money on a
still-early technology in any field.
Infotech examples: A.I., multimedia, internet, wireless
It is almost as easy to spend disproportionate amounts on
older, less centrally accelerating technologies.
Every technology has the right time and place for
innovation and diffusion.
First mover and second mover advantages.
© 2005 Accelerating.org
U.S. Innovation/Competitiveness/Acceleration
has flagged in recent years
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Palo Alto
China surpassed the U.S. this year as the largest recipient of
foreign direct investment.
In 2002, US Corporate R&D declined by $8 billion, largest
percentage drop since 1950.
Five countries (Japan, South Korea, Sweden, Finland, Israel)
spend more GDP on R&D than the U.S.
Foreign owned companies and foreign born inventors now count
for nearly half of all U.S. patents, with Japan, Korea, and Taiwan
accounting for more than one fourth.
Federal R&D funding is now 1/2 of its 1960's peak of 2% of GDP.
Total scientific papers by American authors peaked in 1992 and
have been flat ever since.
Services are the fastest growing sector of many technology
companies, yet much of our service sector, now more than half the
U.S. economy, traditionally does little R&D on business process
design, organization, and management.
Innovate America, NII, Council on Competitiveness, 2004
© 2005 Accelerating.org
National Innovation Initiative
Recommendations (sample)
Talent
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New York
Palo Alto
Investment
Politics
Expedited, expanded
sci-tech immigration
3% of federal R&D for
“innov. accel.” grants
Cabinet-level or NEC
interagency group
National sci-tech
scholarship fund, tax
credits to contributors
3% of DoD budget
must go back to scitech, 20% of this at U’s
New innovation
metrics, national
innovation agenda
Portable graduate tech
fellowships similar to
NSF fellowships
Develop “services
science” as a new
academic discipline
National innovation
scorecard, prizes.
Better patent office.
Matching funds for
postsecondary MS
programs in tech and
innovation
Reward ten regional
“innovation hotspots”
with 5 yrs of funding
Improved IP, tort law,
intangible disclosure
law.
Our Biggest Opportunity: Innovation partnerships with the 3 billion
new workers who weren’t in the global economy ten years ago.
Innovate America, NII, Council on Competitiveness, 2004
© 2005 Accelerating.org
7. Creation: Making the Future
Some Tools for Making the Future
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Education
Investment
Literacy / Environmental Awareness
– Technological
– Business
– Political
– Social
Foresight
Innovation/R&D
Competition (fair, creatively destructive)
Leadership
– Local Commitment
– Global Perspective
Activism
© 2005 Accelerating.org
Education Questions
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Palo Alto
How do we best educate our ourselves, our
employees, our community, our children?
How do we learn “on demand” when we need
it?
How do we learn when to act locally, and
when to act globally?
When to learn individually vs. collectively?
© 2005 Accelerating.org
New Business IA/Social Network Idea:
24/7 Affordable Tech Education
From Geek Squad to Global Computer Helpers
80 million smart, underemployed tech workers, working
at a salary of $1,400/year (China, India)
+ 140 million U.S. labor force (2000).
+ Exponentiating capabilites of our IT systems
+ Commodity communications costs
+ PC transparency software (Gotomypc)
+ Trust (Privacy)
= 24/7 Tech Education
Los Angeles
New York
Palo Alto
How soon? Watch Dell…
© 2005 Accelerating.org
Developmental Windows

In 2005, India is seeing a grassroots
movement to get schools to teach English in
first grade (vs. fourth grade). Three to six is a
developmental window for effortless language
acquisition. Mandarin or Hindi for your child?
Zerotothree.org
Los Angeles
New York
Palo Alto
What will tomorrows for-profit daycare chains be like?
© 2005 Accelerating.org
Investment Questions
Are you practicing socially responsible and
technologically responsible (acceleration
aware) investing?
Supporting companies, products and services that are
increasingly:
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Global
Intelligent
Interdependent
Immune/Transparent
Efficient
Innovative
© 2005 Accelerating.org
Literacy Questions
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New York
Palo Alto
Are you computer, web, and communications
savvy?
Do you use social network media (blogs, web
communities, etc.)?
Do you subsidize online and technological
innovation (leading, not bleeding edge)?
Are you reading and interpreting what’s going
on in the world?
See ASF Community Directory
(accelerating.org/community.html)
© 2005 Accelerating.org
Foresight Questions
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Palo Alto
Do you take time to consider the past,
present, and future of your personal and
professional life?
Do you use strategic planning, scanning,
competitive intelligence, trend extrapolation,
forecasting, scenario generation, or other
futures tools?
Do you read the opinions of key future
thinkers in your areas of professional interest?
Are you supporting the emergence of a
professional futures community?
© 2005 Accelerating.org
Innovation Questions
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New York
Palo Alto
Are you thinking about innovation across the
spectrum (products and services, offline and
online)?
Do you know which of your employees,
business partners, and customers is the most
innovative, all else equal? Do you reward that
in your business model?
Are you working with a global and virtual
innovation team?
© 2005 Accelerating.org
Innovation:
Idea Market/IdeaShare/ShouldExist
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Palo Alto
A shareware ideas bank
Idea Contests/Forums/Blogs
“I release this to the public domain.”
Reputation and budgetary rewards
Unleashing individual ingenuity
Improving innovation and entrepreneurship
Can you set up one for your org?
© 2005 Accelerating.org
Leadership Questions
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New York
Palo Alto
Are you sharing your future visions or
keeping them quiet?
Are you getting critiques and feedback, and is
this changing your perspective?
Are you responding respectfully, adequately,
yet concisely to your critics?
Are you looking for others who also want to
work toward a common vision?
Is this a mutual appreciation society or is your
group affecting real change?
Are you tolerant of parallel, pluralist
approaches?
© 2005 Accelerating.org
Good Leadership Attributes

The best are passionate about 1) creating
community, and 2) making it easy for users to find
their voice.
Stephen Covey,
The Eighth Habit, 2004
“Find your voice and
inspire others to find theirs.”
Los Angeles
New York
Palo Alto
Slow to criticize, ego-minimizing, always striving
to be nice, modeling good behavior, empathic, yet
responsive to communication problems.
© 2005 Accelerating.org
Digital Activism:
Skype (Internet Telephony)
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Seeing the Extraordinary Present
“There has never been a time more
pregnant with possibilities.”
- Gail Carr Feldman
Los Angeles
New York
Palo Alto
© 2005 Accelerating.org
Carpe Diem
"In a time of change, it is learners who
inherit the future. The learned find
themselves well equipped to live in a world
that no longer exists." — Eric Hoffer
Los Angeles
New York
Palo Alto
"Twenty years from now you will be
more disappointed by the things you
did not do than those you did do. So
throw off the bowlines. Sail away from
the safe harbor. Catch the trade winds
in your sails. Explore. Dream.
Discover. Give yourself away to the
sea of life." — Mark Twain
© 2005 Accelerating.org
8. Group Discussion:
Promise and Problems