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