Transcript Trends&ScenariosASB.7.08(84) - Acceleration Studies Foundation

Adapting to the Future:
Trends and Scenarios in Accelerating Change
Army Science Board - Summer Study
July 2008  Irvine, CA
John Smart, President,
Acceleration Studies Foundation
Slides: accelerating.org/slides
Accelerating Change
A Universal Developmental Process
Acceleration Studies:
Something Curious Is Going On
Acceleration
Studies
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The Developmental Spiral
An unexplained physical phenomenon.
(Don’t look for this in your current
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physics or information theory texts…)
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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
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Classic Predictable Accelerations:
Moore’s Law
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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).
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Ray Kurzweil: A Generalized Moore’s Law
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Emergence Acceleration:
Independent Assessments (Preliminary Data)
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Ray Kurzweil,
2006
Transistor Doublings (2 years)
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Courtesy of Ray Kurzweil and KurzweilAI.net
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Processor Performance (1.8 years)
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Courtesy of Ray Kurzweil and KurzweilAI.net
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DRAM Miniaturization (5.4 years)
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Courtesy of Ray Kurzweil and KurzweilAI.net
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Dickerson’s Law: Solved Protein Structures
as a Moore’s-Dependent Process
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Richard Dickerson,
1978, Cal Tech:
Protein crystal
structure solutions
grow according to
n=exp(0.19y1960)
Dickerson’s law predicted 14,201 solved crystal
structures by 2002. The actual number (in online
Protein Data Bank (PDB)) was 14,250. Just 49 more.
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Macroscopically, the curve has been quite consistent.
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A Few Tech Capacity Growth Rates Are Almost
Independent of Socioeconomic Cycles
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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 is the main
dynamic here. Not many intellectual
or physical resources are required to
keep us on the accelerating
Age of Spiritual Machines, 1999
developmental trajectory.
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“Acceleration is a rigged game.”
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Henry Adams, 1909:
Our First “Singularity Theorist”
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Adam’s final
Ethereal Phase
would last about
four years, and
"bring Thought to
the limit of its
possibilities."
(Singularity
1921-2025)
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Macrohistorical Singularity Books
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The Evolutionary Trajectory, 1998
Trees of Evolution, 2000
Singularity 2130 ±20 years
Singularity 2080 ±30 years
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Macrohistorical Singularity Books
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Why Stock Markets Crash, 2003
The Singularity is Near, 2005
Singularity 2050 ±10 years
Singularity 2045 ±20 years
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MEST Compression:
A Developmental Process
The Engine of Accelerating Change
The MESTI Universe
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Matter, Energy, Space, Time  Information
Increasingly Understood
 Poorly Known
MEST Compression/Density/Efficiency is the ever
decreasing MEST resources required for any
standard physical process or computation. The engine
of accelerating change. “More, Better, with Less.”
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MEST Compression Creates a “Paradise of
Resources” for Leading Edge Computation
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Our machines are stunningly more MEST efficient
with each new generation.
Our main candidates for future computational
technology (nanomolecular and quantum computing,
reversible logic, etc.) require little or no energy.
We are all moving to increasingly energy efficient,
sustainable, and virtual cities.
Weight of GDP per capita goes down in all developed
Service Economies.
Global energy intensity (energy consumption per
capita) has been flat for almost three decades in the
developed world.
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Physics of a “MESTI” Universe
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Physical Driver:
 MEST Compression/Efficiency/Density
Emergent Properties:
 Information Intelligence (World Models)
 Information Interdepence (Ethics)
 Information Immunity (Resiliency)
 Information Incompleteness (Search)
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An Interesting Speculation in Information Theory:
↑ Entropy = ↑ Negentropy
Loss of Energy Potential fuels gain of Information
Potential. A hidden metapotential is conserved.
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From the Big Bang to Complex Stars:
The Decelerating Phase of Universal Development
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From Biogenesis to Intelligent Technology:
The Accelerating Phase of Universal Development
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Carl Sagan’s
“Cosmic
Calendar”
(Dragons of
Eden, 1977)
Each month
is roughly 1
billion years.
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A U-Shaped Curve of Change:
Inner Space to Outer Space to Inner Space Again
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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
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Eric Chaisson’s “Phi” (Φ):
A Universal Moore’s Law Curve
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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)
Eric Chaisson, Cosmic Evolution, 2001
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Inner Space and Outer Space
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“I ask you to look both ways. For the
road to knowledge of the stars is
through the atom., and the important
knowledge of the atom has been
reached through the stars.”
Stars and Atoms, 1928
The fundamental constants of nature,
such as the mass of the proton and
the charge of the electron, may be a
"natural and complete specification
for constructing a Universe."
Fundamental Theory, 1946
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Sir Arthur Stanley Eddington
Mathematician and Physicist
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Accelerating Ephemeralization and Our
Increasingly ‘Weightless’ Economy
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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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This trend has also been called “virtualization,” “weightlessness,” and
Matter, Energy, Space, Time (MEST) compression, efficiency, or density.
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MEST Compression and Inner Space:
The Final Frontier?
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Mirror Worlds, David Gelernter, 1998.
Real structures in spacetime (very large and very small) are:
• Computationally very simple and tractable (transparent)
• A vastly slower substrate for evolutionary development
• Rapidly encapsulated by our simulation science
• A “rear view mirror” on the developmental trajectory of
emergence of universal intelligence
versus
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Non-Autonomous ISS
Autonomous Human Brain
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Recognizing the Levers of Nano and Infotech
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"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…)
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Disruptive MEST Compression in Nanospace:
Holey Optical Fibers for Microlasers
Acceleration
Studies
Foundation
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.
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MEST Compression Regularly Disrupts
Efficiency/Cost/Capacity Curves
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Toshiba Li-Ion Nanobattery
80% recharge in 60 seconds
Two orders of magnitude
jump in capacity.
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
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Our Electric Future: Coal & Natural Gas Gen.,
Nanobatteries, and Plug-In Hybrid Vehicles
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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.
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“Driving Toward an Electric Future,” John Smart, 2006
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Smart’s Laws of Technology
Acceleration
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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).
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Acceleration Mechanics:
Exponential Growth, S, B & J Curves,
Phase Change Singularities
Anatomy of Accelerating Change
The S Curve (Phases BG-MS)
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Example: Logistic Population Growth
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Global Population Saturation
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Trends in Transportation Speed
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Exploring and Shaping International Futures, Hughes & Hillebrand, 2006, p. 37
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Saturation Example:
Total World Energy Use
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DOE/EIA data shows total world energy use growth rate peaked in the
1970’s. Real and projected total consumption 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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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.
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Global Energy Consumption per Capita
Saturation (Energy Intensity)
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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.[1]
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Alternative measure: In recent decades, global energy consumption has
been growing increasingly slower than GDP (1%  1.5%  ??).[2]
1. Energy Needs, Choices, and Possibilities: Scenarios to 2050, Shell Intnat’l, 2001;
2. Exploring and Shaping International Futures, Hughes and Hillebrand, 2006, p. 29.
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The B Curve (Phases BGM-SDR)
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Example: Environmental Impact of Individuals
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Jim Dator’s Four Futures (GBAS)
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The Key Images/Stories/Components of Emergent Change
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First cited in: Perspectives in Cross-Cultural Psychology, Jim Dator, Academic Press, 1979
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The J Curve (Phases LEH)
DRIVER:
Intelligence (Negentropy)
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ENGINE:
MEST Compression
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HyperbolicAppearing
Phase
(Not to Scale)
DYNAMIC:
Evolutionary Development
CONSTRAINT:
First-Order Components
are Growth-Limited Hierarchical
Substrates (S and B Curves)
Some aspects of post-emergence
and post-limit systems can’t be
understood or guided by presingularity systems
HP
= Emergence Singularities
EP = Exponential Point (Knee)
HP = Hyperbolic Point (Wall)
Second-Order
Hyperbolic Growth
Exponential-Appearing
Phase
with Emergence Singularities
and a Limit Singularity
EP
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Examples:
Chaisson’s Phi
Sagan’s Cosmic Calendar
Linear-Appearing Phase
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World Economic
Performance
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GDP Per Capita in
Western Europe,
1000 – 1999 A.D.
This curve looks
quite smooth on a
macroscopic scale.
Note the “knee of the
curve” occurs circa
1850, at the Industrial
Revolution.
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A Saturation Lesson:
Biology vs. Technology
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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 Historic Limits to Computation 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
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Punctuated Equilibrium in Biology,
Economics, Politics, Technology…
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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 (Evo or Devo)
80% Equilibrium (Evo or Devo)
Suggested Reading:
For the 20%: Clay Christiansen, The Innovator's Dilemma
For the 80%: Jason Jennings, Less is More
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Lesson: Maintaining Equilibrium is
Our 80% Adaptive Strategy
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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, better, 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.
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Seeing MEST Efficiency and Compression
Everywhere in the World
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Barter > Coins > Paper Money > Checks > PayPal
Cities (>50% of world population circa 2005)
Working in Offices (or telecommuting with coming
videophone virtual offices)
Wal-Marts, Mega-Stores, 99 Cent Stores (Retail
Endgame: Wal-Mart #1 on Fortune 500 since 2001)
Flat-Pack Furniture (Ikea)
Big Box Retail (Home Depot, Staples)
Supply-Chain & Market Aggregators (Dell, Amazon,
eBay)
Local community/Third Space (Starbucks)
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De Chardin on Acceleration:
Technological “Cephalization” of Earth
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"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."
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Finite Sphericity + Acceleration =
Phase Transition (“Singularity”)
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Likely Network Society Developments:
Staggered Closing of Global Divides
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Digital divide is already closing fast. 77% of
the world now has access to a telephone*.
Innovation leader: Grameen Telecom
Education divide may close next (postConversational Interface, post-2020)
Income divide may close next. Developed
world plutocracy is still increasing, but slower
than before. We’ve been “rationalizing” global
workforce wages since 1990’s*.
Power divide is likely to close last. Political
change is the slowest of all domains.
*World Bank, 2005
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The IA-AI Convergence of ‘Metahumanity,’
a Human-Machine Superorganism
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Biologist William Wheeler, 1937: Termites, bees, ants, and other social
animals are parts of “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.
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Metaman: The Merging of Humans and Machines into a Global Superorganism, 1994
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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.
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Understanding Process Automation
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Perhaps 80% of today's First World
paycheck is paid for by automation
(“tech we tend, not the arms we bend”).
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 “taxing the
machines” are the final job descriptions
for all human beings.
Long-Term: Everyone becomes a service
provider, “famous to 15 people”.
Termite Mound
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The Conversational Interface (CI):
Circa 2015-2020 Developmental Attractor
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Codebreaking follows
a logistic curve.
Collective NLP may
as well.
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Date
1998
2005
2012
2019
Avg. Query
1.3 words
2.6 words
5.2 words
10.4 words
Platform
Altavista
Google
GoogleHelp
GoogleBrain
Average spoken
human-to-human
query length is
11 words.
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Why Will We Want to Use An Avatar/Agent
Interface (“Digital Twin”) in 2020?
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Nonverbal and verbal language
in parallel is a more efficient
communication modality.
Ananova, 2002
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“Working with Phil” in Apple’s
Knowledge Navigator Ad, 1987
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Circa 2015-2025: The Symbiotic Age
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A 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.”
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Personality Capture
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In the long run, we become seamless with our machines.
No other credible long term futures have been proposed.
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“Technology is becoming organic. Nature is becoming
technologic.” (Brian Arthur, SFI)
© 2007 Accelerating.org
Your “Digital You” (Digital Twin)
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“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 should
feel like only growth, not death.
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We wouldn’t have it any other way.
Greg Panos (and Mother)
PersonaFoundation.org
© 2007 Accelerating.org
Valuecosm 2040:
Our Plural-Positive Political Future
Acceleration
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
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Microcosm (Gilder), 1960’s
Telecosm (Gilder), 1990’s
Datacosm (Sterling), 2010’s
Valuecosm (Smart), 2040’s
- 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
© 2007 Accelerating.org
Evolutionary Development:
In Biology, Physics, and Beyond
A New Paradigm for Change
Simplicity and Complexity
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Universal Evolutionary Development is:
Simple at the Boundaries, Complex In Between
Simple Math
Of the Very Small
Simple Math
Of the Very Large
(Big Bang,
Quantum Mechanics,
Chemistry)
(Classical Mechanics,
General Relativity)
Complex Math
Of the In Between
(Chaos, Life, Humans,
Coming Technologies)
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Ian Stewart, What Shape is a Snowflake?, 2001
© 2007 Accelerating.org
The Meaning of Simplicity
(Wigner’s ladder)
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Complex systems
are evolutionary.
Simple systems
are developmental.
Evolution
Development
Non-Pattern
Pattern
Variety
Uniformity
Symmetry
Breaking
Symmetry and
Supersymmetry
Chaotic Math
Simple Math
The universe is painting complex local evolutionary pictures, on a
simple universe-wide developmental scaffolding.
The picture (canvas/intelligence, in the middle) is
mathematically complex (Gödelian incomplete),
and trillions of times evolutionarily unique.
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The framework (easel/cosmic structure, very large,
& paint/physical laws, MEST structure, very small)
is uniform, and simple to understand.
© 2007 Accelerating.org
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Replication & Variation
“Natural Selection”
Adaptive Radiation
Chaos, Contingency
Pseudo-Random Search
Strange Attractors
Evolution
Complex Environmental Interaction
Evolutionary Development:
The Left and Right Hands of Change
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’
© 2007 Accelerating.org
RVISC Life Cycle of
Evolutionary Development
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
Replication
Spacetime stable structure, transmissible partially by internal
(DNA) template and partially by external (universal
environmental) template. Templates are more internal with time.

Variation
Ability to encode “requisite variety” of adaptive responses to
environmental challenges, to preserve integrity, create novelty.

Interaction (Complex, Spacetime Bounded)
Early exploration of the phase space favors natural selection, full
exploration (“canalization”) favor developmental selection.

Selection (“Natural/Evolutionary” Selection)
Information-producing, randomized, chaotic attractors.

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Convergence (“Developmental” Selection)
MEST-efficient, optimized, standard attractors.
© 2007 Accelerating.org
How Many Eyes Are
Developmentally Optimal?
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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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How Many Wheels on an Automobile are
Developmentally Optimal?
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Examples: Wheel on Earth. Social computation device.
Diffusion proportional to population density and diversity.
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“Convergent Evolution” (Universal Development):
Troodon and the Dinosauroid Hypothesis
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Dale Russell, 1982: Anthropoid
forms as a standard attractor.
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.
© 2007 Accelerating.org
Evolution and Development:
Two Universal Systems Processes
Acceleration
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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
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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 deepest question is when, where, and how they interrelate.
© 2007 Accelerating.org
Evo vs. Devo Political Polarities:
Innovation vs. Sustainability
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Evo-Devo Theory Brings Process Balance to
Political Dialogs on Innovation and Sustainability
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).
© 2007 Accelerating.org
Rise and Fall of Complex Societies
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
Mesopotamia, “Cradle of Civilization” (Modern
Iraq: Assyrians, Babylonians, Sumerians)
6000 BC – 500 BC. Mineral salts from
repeated irrigation, no crop rotation decimated
farming by 2300 BC). Fertile no more.
© 2007 Accelerating.org
Rise and Fall: Nabatea
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Petra (Nabateans), 400 BC – 400 CE (Jordan:
trading experts, progressively wood-depleted
overirrigated, and overgrazed (hyrax burrows)
Rock Hyrax
(burrows are
vegetation
time capsules)
Jared Diamond, The Third Chimpanzee, 1994
© 2007 Accelerating.org
Rise and Fall: Anasazi
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Chaco Canyon and Mesa Verde (Anasazi), 800 – 1200
CE (New Mexico, Colorado: trading, ceremonial, and
industry hubs, wood depleted (100,000 timbers used in
CC pueblos!), soil depleted (Chaco and Mesa Verde).
No crop rotation. Unsupportable pop. for the agrotech.
Pueblo Bonito, Chaco Canyon, NM
Cliff Palace, Mesa Verde, CO
© 2007 Accelerating.org
Dominant Empire Progression-Combustion
(Phase I: Near East-to-West)
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Hellennistic (Alexander)
Egyptian (New Kingdom)
Babylonian
Spanish
Austria
Germany
British
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Roman
French
© 2007 Accelerating.org
Empire Developmental Progression:
(Phase II: America to Asia)
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Japan
(Temporary: Pop density,
Few youth, no resources.
East Asian Tigers
(Taiwan
Hong Kong
South Korea
Singapore)
American
India
China
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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
© 2007 Accelerating.org
China Inc: The Next Economic Frontier
Acceleration
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
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Annual average GDP growth of 9.5%
(Some urban areas up to 20%!)
Largest global producer of toys,
clothing, consumer electronics.
Moving into cars, computers,
biotech, aerospace, telecom, etc.
1.5 billion hard workers “greatest
natural resource on the planet.”
High savings, factory wages start at
40 cents/hour
45,000 Taiwanese Contract Factories
20,000 European Contract Factories
15,000 U.S. Contract Factories
© 2007 Accelerating.org
Online Economy: Growing Even Faster than China
Acceleration
Studies
Foundation

From 1996 to 2006, total internet users have gone from 36
million to 1 billion, or from 1% to 16% of the world's
population. We've still got a lot of user growth ahead of us.

From 1996 to 2006, U.S. online retail e-commerce
(business to consumer), perhaps the most useful proxy for
the growth of virtual world economies, has grown from 5
million to a projected $95 Billion for 2006, with a current
projected marginal growth rate of 12% per year. GDP per
capita of online worlds like Norrath (Everquest) are 4X
higher than China’s.

In 2004, Internet penetration in China was still less than
6% of the urban population in 2004, yet by that time China
already had the single largest population of online gamers.

Key Point: Think of the Metaverse Economy as the
future, even more (much more!) than “China as the future.”
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Angus Maddison’s
Phases of Capitalist Development, 1982
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Services/Network/Information 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
Products/Manufacturing 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
Resources/Agricultural Society
Society of Basic Needs (“Food/Shelter Economy”)
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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
See also Pentti Malaska’s Funnel Model of Societal Transition, 1989/03
© 2007 Accelerating.org
Acquiring Foresight
An Emerging Discipline
Evo Devo Perspective:
Areas of Accelerating Innovation, 1929-2004
Acceleration
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“The Microcosm” (the “ICT” domain)
Materials Science (“Substrates”)
 Synthetic Materials
 Transistor (Bell Labs, 1948)
 Microprocessor
 Fiber Optics
 Lasers and Optoelectronics
 Wired and Wireless Networks
 Quantum Wells, Wires, and Dots
 Exotic Condensed Matter
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BusinessWeek, 75th Ann. Issue, “The Innovation Economy”, 10.11.2004
© 2007 Accelerating.org
Evo Devo Perspective:
Areas of Accelerating Innovation, 1929-2004
Acceleration
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“The Microcosm” (the “ICT” domain)
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Systems and Software
 Television (1940’s)
 Mainframes (1950’s)
 Minicomputers (1970’s)
 Personal Computers (1980’s)
 Cellphones/Laptops/PDAs (1990’s)
 Embedded/Distributed Systems (2000’s)
 Pervasive/Ubiquitous Systems (2010’s)
 Cable TV, Satellites, Consumer, Enterprise, Technical
Software, Middleware, Web Services, Email, CMS,
Early Semantic Web, Search, KM, AI, NLP…
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BusinessWeek, 75th Ann. Issue, “The Innovation Economy”, 10.11.2004
© 2007 Accelerating.org
Evo Devo Perspective:
Areas of Accelerating Innovation, 1929-2004
Acceleration
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“The Macrocosm” (the “human-ICT” domain)
Defense and Space (“Security-oriented human-ICT”)
 Aircraft carriers, nuclear weapons, ICBMs, cruise
missiles, lunar landers, nuclear powered
submarines... (major open problems (security))
Manufacturing (“Engineering-oriented human-ICT”)
 Lean manufacturing, supply-chain management,
process automation, big-box retailing, robotics…
(major open problems (rich-poor divide))
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BusinessWeek, 75th Ann. Issue, “The Innovation Economy”, 10.11.2004
© 2007 Accelerating.org
Evo Devo Perspective:
Areas of Accelerating Innovation, 1929-2004
Acceleration
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“The Macrocosm” (the “human-ICT” domain)
A 501(c)(3) Nonprofit
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Agrotech/Biotech/Health Care (“Bio-oriented human-ICT”)
 Green revolution, antibiotics, pharmaceuticals,
transplants, medical imaging, prosthetics,
microsurgery, genomics, proteomics, combinatorial
chem, bioinformatics… (“accelerating regulation”)
Finance (“Capital-oriented human-ICT”)
 Venture capital (American R&D, 1946), credit cards
(Bank of America, 1958), mortgage derivs (1970’s),
mutual and hedge funds, prog. trading, microcredit…
Transportation and Energy (“Infrastructure human-ICT”)
 Jet aircraft, helicopters, radar, containerized shipping
 Nuclear power, solar energy, gas-powered turbines,
hydrogen (“accelerating efficiencies (hidden change)”)
© 2007 Accelerating.org
Evo Devo Perspective:
Areas of Accelerating Innovation, 1929-2004
Acceleration
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“The Macrocosm” (the “human-ICT” domain)
Social and Legal (“Fairness-oriented human-ICT”)
 Civil rights, social security, fair labor standards, ADA,
EOE, tort reform, class actions, Miranda rights,
zoning, DMV code, alimony, palimony, criminal law
reform, penal reform, education reform, privacy law,
feminism, minority power, spousal rights, gay civil
unions... (“accelerating refinements” (vs. disruptive
changes), consider E.U. vs. U.S. vs China.)
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BusinessWeek, 75th Ann. Issue, “The Innovation Economy”, 10.11.2004
© 2007 Accelerating.org
Evo Devo Perspective: A 2030 Vision
Acceleration
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Please Entertain this Proposition:
“Human-ICT” computational domains are saturating.
“Tech-Microcosmic” ICT is not.
Human population flatlines in 2050 (“First World effect”). 2nd order
deriv. of world energy demand is negative. ICT acceleration
continues.
Defense, Security, Space, Finance, Social, Legal, Agrotech,
Biotech, Health Care, Finance, Transportation, Energy and
Envirotech all will look surprisingly similar in 2030, but with major
ICT extensions.
We see evolutionarily more and better of the above, but now global,
not local. Meanwhile Condensed Matter Physics, the Nanoworld,
and Cosmology have continued to surprise us.
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ICT (Sensors, Storage, Communication, Connectivity, Simulation,
Interface) will look, and feel, powerfully different, year by year.
© 2007 Accelerating.org
Leading the Future
Creating, Discovering, and Managing
We Have Two Options:
Future Shock or Future Shaping
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“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
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MEST Compression Implication:
Three Hierarchical Systems of Social Change
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
Technological (dominant since 1920-50)
“It’s all about the technology” (what it enables in society, in
itself, how easily it can be developed)

Economic (dominant 1800-1950’s, secondary now)
“It’s all about the money” (who has it, control they gain with it)

Political/Cultural (dominant pre-1800’s, tertiary now)
“It’s all about the power” (who has it, control they gain with it)
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Developmental Trends:
1. The levels have reorganized, to “fastest first.”
2. More pluralism (a network property) on each level.
Pluralism examples: 50,000 Internat’l NGO’s, rise of
the power of Media, Tort Law, Insurance, lobbies, etc.
© 2007 Accelerating.org
IP as an Innovation Rate Regulator:
Lessons of Bose and Microvision
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Innovation diffusion prevented due to overly restrictive IP policy
(often due to philosophy of a single individual controlling the corporation).
© 2007 Accelerating.org
The Leader’s Challenge:
Choosing “Plural Positive” Futures
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Pluralistic
Positive-Sum
Differentiated
“Both/And”
versus
versus
versus
versus
Examples:
Calculator Use
Computer/TV Use
Metaverse Use
Automated Cars
Digital Twins
AND
AND
AND
AND
AND
Plutocratic
Zero-Sum
Homogeneous
“Either/Or”
Math Skills
Social/Study Skills
Reading Skills
Driving Skills
Self-Empowerment
© 2007 Accelerating.org
Wikipedia breeds Futurepedia: A Foresight Vision
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+
Prediction Markets, Delphi, and
the Wisdom of Foresighted Crowds
© 2007 Accelerating.org
A Closing Visual:
Collectively Piloting Spaceship Earth. Or Not.
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© 2007 Accelerating.org
Discussion