Kevin Kelly, out of control, 1994
p.364
The simulation system was not classified; the results were published in the open literature.
p.364
U.S. Military Central Command in Florida
I find the predictive scenarios spooky, strange, and instructional rather than diabolical.
p.364
Wargaming Center, Maxwell Air Force Base, Alabama
Global Game room, Naval War College, Newport, Rhode Island
“sand box” table set-ups, Army's Combat Concepts Agency, Leavenworth, Kansas
TACWAR, JESS, RSAC, SAGA
p.364
Gary Ware, an officer at Central Command
a small cell of military futurists
The simulation was code-named Operation Internal Look.
p.365
TACWAR, the main computerized war-gaming simulator
p.365
Ware's simulation forecast a fairly brief 30-day war if anything this unlikely should occur.
p.365
At first, the upper echelons of the Pentagon had no idea they already owned a fully operational, data-saturated simulation of the war. Turn the key and it would run endless what-ifs of possible battles in that zone. When word of the prescient simulation surfaced, Ware came out smelling like roses. He [Gary Ware] admitted that “If we had to start from scratch at the time of the invasion we would have never caught up.”
p.365
In the future, standard army-issue preparedness may demand having a parallel universe of possible wars spinning in a box at the command center, ready to go.
p.365
By running those simulations in many directions the team quickly learned that airpower would be the decisive key in this war. Further refined iterations clearly showed the war gamers that if airpower was successful, the U.S. would be successful.
p.365
This confidence led to the heavy air campaign.
p.366
tomorrow will be mostly like today
p.367
Theodore Modis, 1992 book, Predictions
Invariants, Growth Curves, Cyclic Waves
p.367
cooking, traveling, cleaning
If new activities (say airplane flight instead of walking) are reformulated into elemental dimensions for analysis (how much time is spent in daily moving), the new behaviors often exhibit a continuous pattern with the odd that can be extrapolated (and predicted) into the future. Instead of walking a half hour to work, you now drive a half hour to work. In the future, you may fly a half hour to work.
p.367
Tracing an invariant optimization point can often alert us to a clean pocket of predictability.
p.367
Among them are a lifespan that can be plotted as an S-shaped curve: slow birth, steep growth, slow decline.
p.368
Modis is intrigued by the 56-years economic cycles discovered by economist N. D. Kondratieff.
(Kevin Kelly, out of control, 1994, filename: ooc-mf.pdf )
____________________________________
Fernand Braudel [Civilisation matérielle, économie et capitalisme], 1992 [ ]
p.613
On the other hand, the graphs quite emphatically concur about the Kondratieff cycle which follows: it begins in 1791, peaks in 1812 and reaches its lowest point in 1851. [takes about 19 years to peak, and about 40 years reach the lowest point, 19 + 40 = 59 years Kondratieff cycle]
We may conclude that the British industrial revolution experienced two movement, roughly between 1781 and 1815, a first and second wind so to speak, the first a rather difficult period, the second easier. In very broad terms, this was also the rhythm experienced by France and the rest of the continent.
(The perspective of the world, 1992, 909.08 Braudel, )
(Fernand Braudel [Civilisation matérielle, économie et capitalisme. English], civilization and capitalism, 15th - 18th century, volume III, the perspective of the world, translation from the French, by Siân Reynolds, 909.08 Braudel, [p.82, pp.86-87, p.613] )
____________________________________
Peter F. Drucker, Innovation and entrepreneurship, 1984
p.4
The Russian economist Nikolai Kondratieff was executed on Stalin's orders in the mid-1930s because his econometric model predicted, accurately as it turned out, that collectivization of Russian agriculture would lead to a sharp decline in farm production. The “50-year Kondratieff cycle” was based on the inherent dynamics of technology. Every 40 years, so Kondratieff asserted, a long technological wave crests. For the last 20 years of this cycle, the growth industries of the last technological advance seem to be doing exceptional well. But what look like record profits are actually repayment of capital which is no longer needed in industries that have ceased to grow.
pp.4-5
This situation never lasts longer than 20 years, then there is a sudden crisis, usually signaled by some sort of panic. There follow 20 years of stagnation, during which the new, emerging technologies cannot generate enough jobs to make the economy itself grow again--and no one, least of all government, can do much about this.*
*Kondratjeff's long-wave cycle was popularized in the West by the Austro-American economist Joseph Schumpeter, in his monumental look Business Cycles (1939). Kondratieff's best known, most serious, and most important disciple today--and also the most serious and most knowledgeable of the prophets of “long-term stagnation”--is the MIT scientist Jay Forrester.
p.5
The industries that fueled the long economic expansion after World War II--automobiles, steel, rubber, electrical apparatus, consumer electronics, telephone, but also petroleum†--perfectly fit the Kondratieff cycle.
† Which, contrary to common belief, was the first one to start declining. In fact, petroleum ceased to be a growth industry around 1950. Since then the incremental unit of petroleum needed for an additional unit of output, whether in manufacturing, in transportation, or in heating and air conditioning, has been falling--slowly at first but rapidly since 1973.
(Peter F. Drucker, Innovation and entrepreneurship : practice and principles, Claremont, California, Christmas 1984, )
____________________________________
Theodore Modis., Prediction : society's telltale signature reveals the past and forecasts the future, 1992.
p.148
The resulting graph, Figure 8.1, presents a picture of regular oscillations. It is so regular that a harmonic waves ── a sinusoidal ── with a fifty-six-year (56-year) time period can be made to pass very closely to most points.
p.149
This periodicity in energy consumption was first observed by Hugh B. Stewart.1 On several occasion before and after Stewart, economists and others have pointed out many human activities that oscillate within a period of fifty [50] to sixty [60] years.2
p.156
[the existence of economic cycles]
A more contemporary scholar, Joseph A. Schumpeter, tried to explain the existence of economic cycles by attributing growth to the fact that major technological innovations come in clusters.10
An extended list of references on long economic waves can be found in an article by R. Ayres.11
p.156
N. D. Kondratieff
1926
From economic indicators alone Kondratieff deduced an economic cycle with a period of about fifty [50] years. His work was promptly challenged. Critics doubted both the existence of Kondratieff's cycle and the causal explanation suggested by Schumpeter. The postulation ended up being largely ignored by contemporary economists for a variety of reasons. In the final analysis, however, the most significant reason for this rejection may have been the boldness of the conclusions drawn from such ambiguous and imprecise data as monetary and financial indicators.
p.156
indicators, like price
inflation and currency fluctuations
monetary indicators
p.156
Concerning cycles with a period of fifty-six years I have cited examples in this chapter that are based on physical quantities. Energy consumptions, the use of machines, the discovery of stable elements, the succession of primary energy sources and basic innovations have all been reported in their appropriate units and not in relation to their prices. The cycles obtained this way are more trustworthy than Kondratieff's economic cycle. In fact, in the case of energy sources, prices indeed folowed the same cycle by flaring up at the end of each boom.
p.156
fifty-six-year economic cycle
p.169
We then compared these natural-growth curves to the fifty-six-year {56-year} cycle of energy consumption, which coincides with the economic cycle. We observed a remarkable correlation between the time these growth curves approach their ceiling and the valleys of the economic cycle.
p.169
recession coincides with saturation of these technologies.
p.170
saturation coincides with economic recession.
p.176
Nakicenovic on the U.K. Wholesale Price Index documented since the sixteenth (16th) century.
p.177
A periodic oscillation recorded over five centuries (500 years)
Figure 9.4
The U.K. Wholesale Price Index smoothed over a rolling 25-year period with respect to a 50-year moving average. This procedure washes out small fluctuations and reveals a wave. The periodicity turns out to be 55.5 years.*
p.224
Once growth is complete, the level reached reflects an equilibrium. Its signature becomes an invariant or constant that, despite erratic fluctuations,
(Prediction : society's telltale signature reveals the past and forecasts the future / Theodore Modis., 1. forecasting., 2. creation (literary, artistic, etc.)
3. science and civilization., CB 158.M63, 303.49--dc20, 1992
, )
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James Gleick., The information : a history, a theory, a flood, 2011
pp.332-333
This is what science always seeks: a simple theory that accounts for a large set of facts and allows for prediction of events still to come.
(The information : a history, a theory, a flood / James Gleick., 1. information science--history., 2. information society., Z665.G547 2011, 020.9--dc22, 2011, )
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Kevin Kelly, out of control, 1994
p.368
In an expectation game, accurate predictions offer no opportunity for money-making if everyone shares the prediction.
([ In term of predict ability, within a given condition and situation, there are pockets of predict ability going forward to about 1 week, using data from the present and the past. Beyond one week, things become fuzzy. Prediction should be kept private, whether they turn out to be true or not. After a period of time, it should not matter so much to reveal the prediction if (overtaken by events - OBE). However a public revelation could served as data point for whose who are engaging in the forecasting activity. Should there be active information manipulation - disinformation, misinformation, deception - and/or active [travel method] modification - like delay, traffic jam, accidents, lockdown, sickness [like pneumonia] - then predict ability becomes less reliable. Because the active operation creates signal that would not have been there if there was no operation. The additional signal would influence the prediction - how much is unclear - it depends on the type of signal. ])
(Kevin Kelly, out of control, 1994, filename: ooc-mf.pdf )
____________________________________
travelled, schedule, sickness [pneumonia]
p.40
in the summer of 1956, he and Loftus travelled to Alaska and Japan to visit strategic warning sites and local COMINT intercept and analysis sites.
In September returned to Europe for a long visit ── traveling across western Europe through the winter to various COMINT locations.
He developed pneumonia in Paris and was forced to delay his return until February 1957.125
source:
John Schutte, ‘Andrew W. Marshall and the Epistemic Community of the Cold War’, 2015, http://www.au.af.mil/au/aupress/digital/pdf/paper/dp_0016_schutte_casting_net_assessment.pdf
dp_0016_schutte_casting_net_assessment.pdf
Schutte, John M., 1976
Casting net assessment : Andrew W. Marshall and the epistemic community of the cold war / John M. Schutte, Lieutenant Colonel, USAF.
1. Marshall, Andrew W., 1921─ 2. United States. department of defense. director of net assessment ── biography. 3. united states. department of defense ── officials and employees ── biography. 4. rand corporation ── biography. 5. united states ── forecasting. 6. military planning ── united states ── history ── 20th century. 7. military planning ── united states ── history ── 21st century. 8. united states ── military policy. 9. strategy. 10. cold war.
title: Andrew W. Marshall and the epistemic community of the cold war.
UA23.6.S43 2014
355.0092 -- dc23
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