Download Development - Acceleration Studies Foundation

Evo Devo, Foresight, and Accelerating Change
John Smart, President, ASF
Association of Professional Futurists
April 2006  Santa Fe, NM
Slides: accelerating.org/slides.html
Presentation Outline
1. Assumption: An Accelerating, Infopomorphic Universe
2. Evo Devo: An Emerging Paradigm for Universal Change
3. Three Foresight Studies:
Futures, Development, and Acceleration
4. Four Foresight Practices (and Domains):
Predicting, Planning, Profiting, Innovating
(Science, Society, Economics, Technology)
5. Five Foresight Systems:
Individual, Social, Organizational, Global, Universal
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Acceleration Studies Foundation
Los Angeles
New York
Palo Alto

ASF (Accelerating.org) is a nonprofit community of 3,000+
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, and
convergent and highly probable scenarios for our common
future, and to use this information now to improve our daily
evolutionary choices.

We suspect key macrohistorical trends include accelerating
intelligence, immunity, and interdependence in our global
sociotechnological systems, increasing technological autonomy,
and the increasing intimacy of the human-machine, physicaldigital interface.
© 2006 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
© 2006 Accelerating.org
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
© 2006 Accelerating.org
1. Assumption:
An Accelerating, Infopomorphic Universe
Systems Theory
Systems Theorists Make Things Simple
(sometimes too simple!)
"Everything should be made as simple as possible, but not simpler."
— Albert Einstein
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
From the Big Bang to Complex Stars:
The Decelerating Phase of Universal Development
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
From Biogenesis to Intelligent Technology:
The Accelerating Phase of Universal Development
Carl Sagan’s
“Cosmic
Calendar”
(Dragons of
Eden, 1977)
Each month
is roughly 1
billion years.
Los Angeles
New York
Palo Alto
© 2006 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
Los Angeles
New York
Palo Alto
Developmental Singularity?
8B yrs: Earth
© 2006 Accelerating.org
The MESTI Universe
Matter, Energy, Space, Time  Information
Increasingly Understood
 Poorly Known
MEST Compression/Density/Efficiency drives
accelerating change.
Los Angeles
New York
Palo Alto
© 2006 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
New York
Palo Alto
© 2006 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
Los Angeles
New York
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
© 2006 Accelerating.org
The Infopomorphic Paradigm
Los Angeles
New York
Palo Alto
The universe is a physical-computational system.
We exist for information theoretic reasons.
We’re here to evolve and develop.
To create, discover, and manage.
To care, count, and act.
To innovate, plan, profit, and predict
© 2006 Accelerating.org
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
Los Angeles
New York
Palo Alto
Le Phénomène Humain, 1955
© 2006 Accelerating.org
De Chardin on Acceleration:
Technological “Cephalization” of Earth
"No one can deny that
a network (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."
Los Angeles
New York
Palo Alto
“Finite Sphericity + Acceleration =
Phase Transition”
© 2006 Accelerating.org
Stock on ‘Metahumanity’:
The Emerging Human-Machine Superorganism
Biologist William Wheeler, 1937: Termites, bees, and other social
animals are “superorganisms.” Increasingly, they can’t be understood
apart from the structures their genetics compel them to construct.
Their developmental endpoint: an integrated cell/organism/supercolony.
Los Angeles
New York
Palo Alto
Metaman: The Merging of Humans and Machines into a Global Superorganism, 1994
© 2006 Accelerating.org
2. Evo Devo: An Emerging Paradigm
for Universal Change
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
Los Angeles
New York
Palo Alto
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
© 2006 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).
Los Angeles
New York
Palo Alto
For more: Wallace Arthur, Jack Cohen, Simon Conway Morris, Rudolf Raff
© 2006 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)
Los Angeles
New York
Palo Alto
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)
© 2006 Accelerating.org
Evolution vs. Development
“The Twin’s Thumbprints”
Consider two identical twins:
Thumbprints
Los Angeles
New York
Palo Alto
Brain wiring
Evolution drives almost all the unique local patterns.
Development creates the predictable global patterns.
© 2006 Accelerating.org
Marbles, Landscapes, and Basins
(Complex Systems, Evolution, & Development)
Los Angeles
New York
Palo Alto
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.
© 2006 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.
Los Angeles
New York
Palo Alto
© 2006 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.
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
“Convergent Evolution”:
Troodon and the Dinosauroid Hypothesis
Dale Russell, 1982: Anthropoid
forms as a standard attractor.
Los Angeles
New York
Palo Alto
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.
© 2006 Accelerating.org
Evolution and Development:
Two Universal Systems Processes
Evolution
Development
Creativity
Chance
Randomness
Variety/Many
Possibilities
Uniqueness
Uncertainty
Accident
Bottom-up
Divergent
Differentiation
Discovery
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.
Los Angeles
New York
Palo Alto
The deepest question is when, where, and how they interrelate.
© 2006 Accelerating.org
Evo-Devo Provides
Physical Reasons for Naturally Observed Polarities
Los Angeles
New York
Palo Alto
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!
© 2006 Accelerating.org
Exercise
Is computer hardware acceleration (Moore’s
law) more evolution or development driven?
Have historical advances been due more to
human creativity or human discovery?
What about software?
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Ray Kurzweil: A Generalized Moore’s Law
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Two Political Polarities:
Innovation/Discovery vs. Mgmt/Sustainability
Evo-Devo Theory Brings Process Balance to
Political Dialogs on Innovation and Sustainability
Los Angeles
New York
Palo Alto
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).
© 2006 Accelerating.org
Punctuated Equilibrium (in Biology,
Technology, Economics, Politics…)
Los Angeles
New York
Palo Alto

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 © 2006 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
Los Angeles
New York
Palo Alto
Result: No Apparent Limits to the Acceleration of Local Intelligence,
Interdependence, and Immunity in New Substrates Over Time
© 2006 Accelerating.org
3. Three Foresight Studies:
Futures, Development, and Acceleration
Three Fundamental Foresight Studies:
Futures, Development, and Acceleration



Los Angeles
New York
Palo Alto
Futures Studies
– “Possible” change (scenarios, alternatives)
Development Studies
– “Irreversible” change (emergences, phase
changes)
Acceleration Studies
– “Accelerating” change (exponential growth,
positive feedback, self-catalyzing,
autonomous)
All three are evo-devo compliant models of
accelerating change.
© 2006 Accelerating.org
Development Studies I:
Irreversible and Progressively Emergent
Historical Examples (Discuss):
 The Wheel
 Electricity
 Democracy
 Emancipation
Future Scenarios (Discuss):
 Public Transparency / End of Anonymity
 The Conversational User Interface
 The Metaverse
 The Valuecosm
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Development Studies II:
Irreversible and Cyclically Emergent
Historical Examples (Discuss):
 Individuation vs. Conformity (Pendulum)
 Plutocracy vs. Democracy (Pendulum)
 Materialism, Idealism, Conflict Resolution (Cycle)
 Quaternary Generations (Cycle)
 Guns (Japanese and Chinese history.
Nonlethals today.)
 Warfare (Archaic Age rise, Empires Age peak, 21st
Century rise and fall)
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Development Studies III:
The S Curve (Logistic Growth)
Los Angeles
New York
Palo Alto
Four Classic Phases:
Emergence, Growth, Maturing, Saturation
Fifth Developmental Phase:
Senescence/Death (and Replacement)
© 2006 Accelerating.org
Exercise: Identify
the Logistic Phase
Los Angeles
New York
Palo Alto
Current Year if Date Not Given:
 Air Transportation
 World Population (1960)
 World Population (2000)
 MOS Computing Price/Performance
 Copper Twisted Pair Communication Price/Performance
 Novel Rock Songs
 Internet Users
 Bacterial Growth on introduction to new media
 Rabbit Population Growth on introduction to Australia
 Ocean Pollution
 Global Energy Intensity (Gigajoules/capita used annually)
 Global CO2 Production
 Global Digital Divide (Between 1st and Emerging World)
 Global Education Divide
 Global Economic Divide
 Global “Power” Divide
© 2006 Accelerating.org
Acceleration Studies:
Something Curious Is Going On
Unexplained.
(Don’t look for this in your physics or information theory texts…)
Los Angeles
New York
Palo Alto
© 2006 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).
© 2006 Accelerating.org
Transistor Doublings (2 years)
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2006 Accelerating.org
Processor Performance (1.8 years)
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2006 Accelerating.org
DRAM Miniaturization (5.4 years)
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2006 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.
Los Angeles
New York
Palo Alto
Macroscopically, the curve has been quite consistent.
© 2006 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.
Conclusion: Human-discovered,
Not human-created complexity here.
Not many intellectual or physical
resources are required to keep us on
the accelerating developmental
trajectory.
Los Angeles
New York
Palo Alto
“MEST compression is a rigged game.”
Age of Spiritual Machines, 1999
© 2006 Accelerating.org
IT’s Exponential Economics
Los Angeles
New York
Palo Alto
Courtesy of Ray Kurzweil and KurzweilAI.net
© 2006 Accelerating.org
Macrohistorical Singularity Books
Los Angeles
New York
Palo Alto
The Evolutionary Trajectory, 1998
Trees of Evolution, 2000
Singularity 2130 ±20 years
Singularity 2080 ±30 years
© 2006 Accelerating.org
Macrohistorical Singularity Books
Los Angeles
New York
Palo Alto
Why Stock Markets Crash, 2003
The Singularity is Near, 2005
Singularity 2050 ±10 years
Singularity 2050 ±20 years
© 2006 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.
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Acceleration Studies: 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.
Los Angeles
New York
Palo Alto
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
© 2006 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.
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
The Developmental Spiral











Los Angeles
New York
Palo Alto
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
© 2006 Accelerating.org
“NBICS”: 5 Choices for Strategic Technological
Development





Los Angeles
New York
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.
© 2006 Accelerating.org
“Unreasonable” Effectiveness and Efficiency of
Science and the Microcosm: 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.
Los Angeles
New York
Palo Alto
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.
© 2006 Accelerating.org
Understanding the Lever of Nano and 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)
Los Angeles
New York
Palo Alto
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…)
© 2006 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.



Los Angeles
New York
Palo Alto
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. © 2006 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”
Los Angeles
New York
Palo Alto
This trend has also been called “virtualization,” “weightlessness,” and
Matter, Energy, Space, Time (MEST) compression, efficiency, or density.
© 2006 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”)

“The future’s already here. It’s just not
evenly distributed yet.” ― William Gibson
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
An Electric Future: Natural Gas, Nanobatteries, and
Plug-In Hybrid Electric Vehicles
Natural gas, already 20% of US energy consumption,
is the fastest growing and most efficient component.
Nanobatteries recharge 80% in 60 seconds,
keep 99% of their duty after 1,000 cycles.
180+ mpg Prius.
34 miles on battery only.
Nanobatteries can make electric car recharging as fast as gas tank
filling, and tomorrow's power grids will be much more decentralized
than today's gasoline stations, supporting even greater city densities.
Los Angeles
New York
Palo Alto
“Driving Toward an Electric Future,” John Smart, 2006
© 2006 Accelerating.org
Understanding Process Automation





Los Angeles
New York
Palo Alto
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
© 2006 Accelerating.org
Oil Refinery (Multi-Acre Automatic Factory)
Los Angeles
New York
Palo Alto
Tyler, Texas, 1964. 360 acres. Run by three operators,
each needing only a high school education.
The 1972 version eliminated the three operators.
© 2006 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)

“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 we knew
on the farms and the assembly line.”  Tsvi Bisk
Los Angeles
New York
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
© 2006 Accelerating.org
World Economic
Performance
GDP Per Capita in
Western Europe,
1000 – 1999 A.D.
This curve looks
quite smooth on a
macroscopic scale.
Los Angeles
New York
Palo Alto
Notice the “knee of
the curve” occurs at
the industrial
revolution, circa
1850.
© 2006 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
© 2006 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)
© 2006 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
© 2006 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?
Los Angeles
New York
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)
© 2006 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, and
other continually emigrating (“brain drain”) nations.
Los Angeles
New York
Palo Alto
Future of Philanthropy, GBN, 2005
© 2006 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
© 2006 Accelerating.org
Networking Books
Los Angeles
New York
Palo Alto
Linked, Albert-Laszlo Barabasi, 2003
Six Degrees, Duncan Watts, 2003
© 2006 Accelerating.org
The New Paradigm: Out of (Individual) Control.
The Wisdom of the (Well Organized) Crowd.
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Back to the Greek Future



Greece built an enviable empire on the backs
of human slaves.
21C humanity is building an even more
enviable one on the backs 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
© 2006 Accelerating.org
4. Four Foresight Practices (and Domains)
Predicting, Planning, Profiting, Innovating
(Science, Society, Economics, Technology)
Systemic (Integrated) Foresight:
Greeks, Pronouns, Skill Sets and Processes
True
What Is
It/Its
Los Angeles
New York
Palo Alto
Greeks
Good
What ‘We’ Want
Pronouns
We/He/She/You
Beautiful
What ‘I’ Want
I/Me
Discovery
Universal
Foresight Skill Sets
Management
Social
Processes
Creativity
Individual
Development
Convergence
Statics/Dynamics
Law/Emergence
Evolution
Divergence
© 2006 Accelerating.org
Integral Maps:
Ken Wilber’s Process 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
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Systemic Thinking:
Edward De Bono’s Six Thinking Hats
Los Angeles
New York
Palo Alto
It/Its
We/He/She/You
I/Me
White
Yellow
Red
(Facts)
(Social Positive)
(Intuition)
Blue
Black
Green
(Process)
(Social Negative)
(Creative)
© 2006 Accelerating.org
Types of Intelligence:
Gardner’s Eight ‘Frames’/ ‘Modules’
Gardner has developed research and
metrics for eight different “frames” or
“modules” of human capacity.
A promising way to look at thinking.
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Integral Intelligence:
Gardner’s ‘Frames,’ Wilber’s ‘Lines’
 Meta/Integral/Spiritual (Attractor)
I (Innovating)
Intrapersonal/Self-Identity
 Body/Kinesthetic/Health
 Cog-Emot/Needs/Self-Care
 Creativity/Innovating/Vision

It (MEST Mgmt - Profiting)
Visual/Spatial
 Aural/Musical
 MEST/Thing-Care
 Decisionmaking/Adapting

We (Social Mgmt - Planning)
Interpersonal/Social-Identity
 Linguistic/Social-Narrative
 Intimacy/Social-Care
 Moral/Cultural/Social-Relation

Its (Predicting)
Nature/Systems
 Logical/Mathematical
 Object Relatns/Structure-Care
 Discovery/Predictive/Counting

Wilber proposes additional intelligence lines/dimensions on top of Gardner’s. I’ve
mapped nine I recognize to his quadrants above. They fit nicely.
Los Angeles
New York
Palo Alto
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 tries to look meta (above, beyond) all the other lines.
© 2006 Accelerating.org
Integral Foresight Development: Wilber, De Bono,
Gardner, Ichazo, Jenkins, Jung, Myers-Briggs, Smart
 Meta/Integral/Spiritual (Attractor)
 The Peacemaker (9) (Types A and B)
 INTJ, ESFP (Integral Types)









Los Angeles
New York
Palo Alto
I (Innovating)
It (MEST Mgmt - Profiting)
Subjective Self
Objective Self
Intrapersonal/Self-Identity
Body/Kinesthetic/Health
Cog-Emotional/Needs/Self-Care
Creativity/Innovating/Visioning
The Individualist (4) (Type A)
The Enthusiast (7) (Type B)
“I” Introverted Orientation
“F” Feeling Function
INFP, INFJ, ISFP









Visual/Spatial
Aural/Musical
MEST/Thing-Care
Decisionmaking/Adapting (Z & NZ)
The Challenger (8) (Type A)
The Loyalist (6) (Type B)
“J” Judging Process (Think or Feel)
“S” Sensing Function
ESTJ, ISTJ, ESFJ, ISFJ
We (Social Mgmt - Planning)
Its (Predicting)
Subjective System
Objective System









Interpersonal/Social-Identity
Linguistic/Social-Narrative
Intimacy/Social-Care
Moral/Cultural/Social-Relation
The Achiever (3) (Type A)
The Helper (2) (Type B)
“E” Extroverted Orientation
“N” Intuition Function
ENFP, ENFJ, ENTP, ENTJ









Nature/Systems
Logical/Mathematical
Object Relations/Structure-Care
Discovery/Predictive/Counting
The Reformer (1) (Type A)
The Investigator (5) (Type B)
“P” Perceiving Process (Intuit or Sense)
“T” Thinking Function
INTP, ESTP, ISTP
Wilber’s Four “Quadrants”
Smart’s Four “Foresight Skills”
Gardner’s Eight “Intelligences”
(Multiple Intelligences)
Wilber’s Nine Additional
“Developmental Lines”
(Smart’s Interpretation)
Ichazo/Naranjo’s (Enneagram)
Nine “Personality Types”,
(Subtyped by Jenkin’s
Type A/Type B Classifiers
Myers-Briggs Sixteen
Personality Types
(Jung’s 4 Mental Functions,
2 Orientations, and 2 Processes).
Fourteen of the sixteen M-B types
weight to one of the four quadrants
by possessing both its function and
its orientation or process. Note that
there are eight M-B “manager”
(the most prevalent), three
“creator” types, three “discoverer”
types, and two “integral” types.
This seems a good reflection of
these skills and prevalence in the
general population.
© 2006 Accelerating.org
Four Foresight Domains:
Technological, Social, Economic, Scientific
I (Individual/Self)
Creativity-Driven Futures
Technological
Innovating
We (Social/Kinship)
Consensus-Driven Futures
Social
Planning
Los Angeles
New York
Palo Alto
It (Organizational/Contractual)
Agenda-Driven Futures
Economic
Profiting
Its (Global/Species)
Research-Driven Futures
Scientific
Predicting
© 2006 Accelerating.org
Four Essential Foresight Practices:
Innovating, Planning, Profiting, and Predicting

Innovating/Creating (I)
Thinking and acting by personal preferred futures

Planning/Negotiating (We)
Thinking and acting by social consensus plans

Profiting/Adapting (It)
Thinking and acting by objectively measurable results

Predicting/Discovering (Its)
Thinking and acting by statistically predictive forecasts
Los Angeles
New York
Palo Alto
© 2006 Accelerating.org
Exercise: Categorize these Foresight Practices
(Innovating, Planning, Profiting, or Predicting)
sci-fi and utopian studies
budgeting
accounting and finance
business intelligence
scenarios and creative thinking
roadmapping
social and environmental impact
marketing research
individual visioning
management by consensus
business IT (ERP, CRM, etc.)
soft sciences and systems theory
social networking
collective visioning
innovation
Los Angeles
New York
Palo Alto
command leadership
enterprise planning
management by meas. results
forecasting and trends
sci-tech R&D
conflict resolution
risk management and insurance
management by forecast
entrepreneurship
strategic planning
scanning
history of prediction
community building
statistics and actuarial science
hard sciences
© 2006 Accelerating.org
Four Essential Foresight Practices:
Innovating, Planning, Profiting, and Predicting




Los Angeles
New York
Palo Alto
Innovating/Creating (I)
Management by personal preferred futures: command leadership,
sci-fi and utopian studies, visioning, creative thinking, scenarios,
entrepreneurship, innovation, sci-tech R&D
Planning/Negotiating (We)
Management by social consensus: social networking, collective
visioning, conflict resolution, community building, strategic planning,
roadmapping, enterprise robustness and resilience planning
Profiting/Adapting (It)
Management by measurable results: accounting, finance,
budgeting, measured economic, social, and environmental benefits,
risk mgmt (insurance), hedging, business IT (ERP, CRM, etc.)
Predicting/Discovering (Its)
Management by forecast (soft to hard): scanning, marketing
research, business intelligence, soft sciences and systems theory,
history of prediction, forecasting, statistical trends, actuarial
science, hard sciences
© 2006 Accelerating.org
5. Five Foresight Systems: Individual,
Social, Organizational, Global, Universal
Five Foresight Systems:
Individual, Social, Organizational, Global, Universal
All (Universal/Metascientific) [Transcendence] (Attractor)
Physics-Driven Futures
I (Individual/Self)
Creativity-Driven Futures
Technological
 Innovating
 Creating
(introverted, feeling)
 Caring [Love/Beauty]

It (Organizational/Contractual)
Agenda-Driven Futures
Economic
 Profiting (Measuring)
 Managing-Politics-Law-Etc.
(judging, sensing)
 Acting [Wealth/Progress]

We (Social/Kinship)
Consensus-Driven Futures
Social
 Planning (Negotiating)
 Managing-Politics-Law-Etc.
(extroverted, intuiting)
 Acting [Peace/Unity]

Los Angeles
New York
Palo Alto
Its (Global/Species)
Research-Driven Futures
Scientific
 Predicting
 Discovering
(thinking, perceiving)
 Counting [Truth/Knowledge]

© 2006 Accelerating.org
Three Fundamental Foresight Studies:
Futures, Development, and Acceleration

Acceleration Studies (Universal System Attractor)
I (Individual/Self)
Creativity-Driven Futures
Technological
 Innovating


It (Organizational/Contractual)
Agenda-Driven Futures
Economic
 Profiting

Futures Studies (Evolutionary)
We (Social/Kinship)
Consensus-Driven Futures
Social
 Planning


Los Angeles
New York
Palo Alto
Its (Global/Species)
Research-Driven Futures
Scientific
 Predicting

Development Studies (Developmental)
Question: Which is unlike the others? The universal system grows asymptotically
via science and technology, and secondarily via economic and social change. All five
(individual, kinship tribe, contractual tribe, species, universe) may be astrobiologically
developmental.
© 2006 Accelerating.org
Four Types of “Futures Studies”
–
–
–
–
Los Angeles
New York
Palo Alto
Exploratory/Creativity-Driven (Speculative Literature, Art)
Consensus-Driven (Political, Trade Organizations)
Agenda-Driven (Institutional, Strategic Plans)
Research-Driven (Stable Developmental Trends)

The last is the critical one for acceleration studies and
development 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 ASF seeks to address.
© 2006 Accelerating.org
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
© 2006 Accelerating.org
Discussion