Category Archives: Natural systems

scientific methods & principles for natural systems research

SDG8 side event: Recoupling

2019 UN HLPF side event scheduled Tuesday July 10 2019 1:15 to 2:45 at the UN Millennium Hilton, 3min statement. Further links to natural growth strategy below. – Jessie Henshaw

Thank you for coming.  
Find more of my statement and links at www.synapse9.com/signals

My name is Jessie Henshaw.  I’m a natural systems scientist who developed a fascination with how living systems transform as they develop, such as how our economy once changed by small accumulating steps that got bigger and bigger.  Those ever-increasing rates and kinds of change are the key reason there are natural limits to growth.  Growth is itself an organizational process that pushes economies and their organizations in the direction of increasingly disruptive limits.  

For example, walking down the street by bigger and bigger steps, making more and more progress at first and would lead to losing control, and a painful fall.   Similarly, in the last 250 years, the world economy doubled its annual expansion about 12 times, so our annual expansions today are about the size of the entire world economy of 1920, truly enormous.  

In part, we experience that as universal pressure, for increased economic performance from all people, all organizations, all societies, and of course, all of nature too.  We are also feel surrounded by systems failing to keep up, and in crisis, crying for help, that we find hard to deliver.  So today the true location of the most “vulnerable people” and most “vulnerable regions,” struggling with unmanageable demands, is now truly the whole earth. (to cut for time)

At first, the economy’s growing demands were not overwhelming, and seemed very rewarding for large sectors, having a negligible impact on the earth as a whole too.  Continually multiplying them changed all that.  Now they disrupt every environment and are breaking through all silos of discussion.  Now we see there was no “economic decoupling,” but just detachment from our responsibility.  Now we look around and see an enormous diversity of crises that were not supposed to materialize, and need to decide what to do.  

We need an “economic recoupling” with our responsibilities for the earth and humankind.   An easy first step is to think of your responsibility for steering the economy as equal to your share of the economy.  It may seem small, but in a global economy where it takes the whole world to deliver every product or service, we are similarly responsible for a share of every harm caused too.  

Nature’s integral: joining the multiplication of parts (red) with the refinement of their designs and uses (blue) to prepare for LIFE (green) as the reward in the end

The path ahead I see, for transforming the economy is to change from compound growth to natural growth,  climaxing growth at a peak of resilience and vitality, ready for a secure, enduring and creative life on earth.

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The Economic Path to Natural Growth

PDF slides: https://synapse9.com/_SDinteg/PathToNatGrowth.pdf
2019 Jul 2 Talk 30 min: https://www.youtube.com/watch?v=w5Cz7vc0-c4

Finance serving Life

“Finance Serving Life” introduces an updated version of the transformation journey for global capitalism envisioned by J.M. Keynes. He first described it with a biblical fable he called “The widows cruse” (or “Widow’s cup”) based on the 1 Kings 17 story of Elijah asking for food from a poor widow with scarcely any, just a last bowl of flour and flask of oil. To relieve the poor widow of doubt Elijah tells her that if she shares her scarce provisions it will provide generously for both of them, becoming inexhaustible as long as she is in need.

Keynes’ use of the fable was meant illustrate to the wealthy that if growth ever became unprofitable, they could sustain a healthy economy by spending rather than compounding their profits, and have their profits forever be return to them. It illustrates a true natural economic principle of sustainability, that at natural limits to growth spending the profits from investments will become necessary to keep them profitable. That principle is also observed in living systems that repurpose their surpluses at their limits to growth, from being used for multiplying their parts to perfecting their uses and designs in order to thrive at maturity.

Today we can observe that using profits to continue to multiply the parts and demands of the economy on the earth and humanity have become excessive, in total effect impoverishing rather than enriching the both the human and natural world. In principle, though also depending on how it is done, relieving nature and humanity of escalating demands for increased productivity by wisely spending, rather than reinvesting profits would assure that the same level of profits would become everlasting.

Philanthropy and sustainability are among many such good purposes that those with a “good eye for value” might choose at a time such as the present when compounding profits to multiply the parts and scale of the world economy has become increasingly unsustainable. In macro-economic terms, spending the profits of the economy as it approaches the natural limits of healthy development relieves the natural world from endlessly increasing extractive depletion and disruption, while repurposing the use of profits for perfecting the economy’s systems and their relationships with the natural world, potentially bringing endless vitality to the whole.

One of the fine points observers often miss is that a non-growing world economy, using its profits for perfecting its designs for thriving and caring for the planet, would not become a stagnant “cash-cow.” Like a natural ecosystem it could be a thriving and stable system for continual self-reinvention, maintaining as much creative change, i.e. “creative destruction,” as is comfortable. Maintaining that balance of healthy creativity, avoiding both rapacious growth and stagnation, is then the steering job of the transformed economic system.

People are such wonderful designers of systems they put their minds to, and life offers so very many wonderful examples of successful transitions of this kind, from compound extractive growth to long lived creative stability, it is hoped that now that we are faced with the challenge, we could put our minds to it and figure it out.

The current slide set for presenting the concept more fully as a talk or webinar has the same name “Finance serving Life.”

jlh

The Growing Rate of Climate Change

Showing:

— A presently elevated growth rate of CO2 in the atmosphere directly linked to globalization.

— And resulting likely 1.5 degree C warming by 2030, TEN years earlier than the recent IPCC estimate.

— Plus a fascinating story of diagnostic data science discovery.

Yes, it is a somewhat radical approach,
but is fully data driven, meticulous, and at the high side of the IPCC uncertainties, making it plausible. So it should challenge others to try to confirm or dispute the findings.
Losing 10 years in preparing for 1.5 degrees C also makes this finding, if true, extremely urgent to respond to.

(A Major Edit of a 10/8/18 version, republished 4/8/19 – Jessie Henshaw)

The Path of Atmospheric CO2 – To understand climate change it helps to start with the whole picture, the great sweep of increasing concentration of CO2 in the atmosphere shown in Figure 1, as the main cause of the greenhouse effect. Looking at where it began, you can clearly see the fairly abrupt shift in the trends at about 1780, also about the same time as rapid industrial growth was beginning, seeming to mark the abrupt emergence of fossil fuel industry that the rest of the curve clearly represents.

Look closely at the relatively lazy shapes of pre 1780 variation in CO2 back to 1500 (purple) and how that pattern differs from the abrupt start of the growing rates of increase (green line) after 1780 an how closely it follows the mathematical average growth rate curve (dotted). Note how the trendline threads through the fluctuations in the data starting from 1780.  The way the data moves back and forth *centered on the constant growth curve* is what implies that the organization of the economy for using fossil fuels had an constant growth rate, of 1.48 %/yr. Hopefully that seems rather remarkable to you, but the data is clear, that the global economy has a single organization for behaving as a whole, as a natural system, with a stable state of self-organization in that period.

Figure 1 – The abrupt emergence of climate change with the industrial economy, evident in the constant compound growth of atmospheric CO2 PPM at 1.48 %/yr, from 1780 to WWII, followed by a pause and then the transition to the even higher growth rate 1.90 %/yr, That second growth spurt, continuing to the present, presumably reflect the modern reorganization of the world economy for maximum growth informally called “globalization.”

We know from the absorption of heat radiation by CO2, creating the greenhouse effect, that the CO2 greenhouse effect is heating the earth in relation to its concentration in the atmosphere. What implies that relation is close to linear, making the effect directly proportional to the cause, is shown in the Figure 2. The dashed brown line shows the slope of the relation, closely fitting the actual gradual curve, at least between 300 to 400 PPM, the thresholds that were crossed in 1914 and 2016 respectively, a period of 102 years. Atmospheric CO2 is increasing much faster now, though, so the next increase of 100 PPM, to 500 PPM, will be reached much more quickly rising at its current stable rate of 1.9 %/yr rate. If that rate continues 500 PPM will be reached in only 30 more years, by 2046. That large acceleration is the effect of the current higher exponential rate of increase. Of course, considering the rapid compound acceleration of the cause of climate change, and the alarm people are taking now, quite a lot could happen before 2046.

Figure 2 – The “relative heating” of the the earth to Atmospheric CO2 concentration, indicating temperature change has an approximately linear relation to CO2 (brown line) for the range of concentrations (300 to 400 PPM) over recent times. The triangles indicate concentrations in 1985. (Mitchell 1989, Figure 6 w/ added color)

The Annual PPM Growth Rates – Figure 3 shows the growth of Atmospheric CO2 (green) with the details of its fluctuating annual growth rates, to depict both the constants of the growth curve and it’s irregular growth rate interruptions. The individual interruptions raise lots of interesting questions, but perhaps the most important feature is that they are quiet temporary, as evidence of the constant behavior recovering again and again.

The upper curve shows fluctuating annual growth rates (lt. axis, PPM dy/Y) for the curve below, the CO2 PPM concentrations. The peaks and drops of the growth rate align with the small waves in the concentration (rt. axis). Note that the large drops in the growth rate that seem to snap right back to the the horizontal dashed red lines. That seems to show that they mark processes that absorb and then release CO2 again, as they do not seem to affect the average growth rates of PPM concentrations as a whole, around which the annual fluctuations homeostatically fluctuate.

This diagnostic approach is for raising questions like the above, using the annual growth rate to expose the dynamics of the curve for a somewhat anatomical picture. In this case it’s of the homing dynamics of the global growth system as it first hovers around the rate 1.48 %/yr from 1780 up to WWII, and then shifts to hovering around the higher rate of 1.9 %/yr as it stabilizes from 1971 to 2018. You might think of these two long periods of homeostatic growth rates in CO2 concentration as representing periods of regularity in the causal systems, global economic growth and the carbon cycle response, seen through the lens of atmospheric CO2.

You might think the large departures from the regular trends would be great recessions perhaps, that then “make up for lost time” on recovery. I could not find corresponding recessions, though, and for the great recessions I checked there do not seem to be notable dips in CO2 accumulation. To validate this kind of research one has to go through that kind of thought process for every bump on the curve, either a tedious or exciting hunt for plausible causes than then check out with other data.

What seems most unusual about the big dips in the CO2 growth rate (D1, 2, 3, 4, 5) is that 1) they do not occur after WWII and 2) they rise and fall so sharply and have no lasting effect, seemingly temperature sensitive as well as absorbing CO2 later released. I can’t say whether it is feasible or not, but something like vast ocean plankton blooms might have that effect, absorbing and then releasing large amounts of CO2. There’s also a chance the way the raw data was splined and the growth rates smoothed, to turn irregularly spaced measures into smooth curves, might also have unexpected effects. Whatever phenomenon causing the big dips was, it appears to have been interrupted by the rapid acceleration of warming that followed WWII, as evident in the smooth and uninterrupted rise in most recent and best raw data. Those are at least pieces of the puzzle that might help someone else narrow it down.

Figure 3. Atmospheric CO2 concentration (CO2 PPM)(rt. scale) and its annual growth rates (PPM %/yr)(lt. scale), showing the change in growth constants before and after WWII. The key evidence of these being different organizational states of the world economy (before & after WWII) is regular “homeostatic” (home seeking) reversal of trends departing from the growth constants. It is the post WWII growth constant state of 1.90 %/yr that is preventing normal policy process from intervening in climate change, and needs to be “recentered” on learning from nature rather than overwhelming nature for our survival. 

Comparing the CO2 cause and degree C effect – The main purpose of Figure 4 is to compare the history of earth temperatures (blue, ‘C, lt scale) with the curve of atmospheric CO2 (green, PPM, rt scale). The CO2 PPM data is the same Scripps atmospheric CO2 data and scale we’ve seen below. The temperature data is from the HadCRUT4 records used by the IPCC. In this case the original anomaly data relative to the 1850-1900 average have been converted to absolute ‘C values, using a conditional set point of 14.6 ‘C in 2017. In a way it is as arbitrary a coordinating value as the others people use. It’s chosen here first for being a more familiar scale, but also so that 1780 initial values for PPM and ‘C can be determined as initial values for the greenhouse effect. Those baselines are essential for defining the exponential growth rates of the PPM and ‘C curves. The 14.6 ‘C value was based on an expert’s estimate.

Figure 4

Aligning the curves for Figure 4 lets us look closely to see if any shapes of the cause of the greenhouse effect (PPM) are clearly visible in the shape of the effect, global warming (‘C). Does anything in particular jump out? First might be the differences, one curve quite smooth the other jittery, both having wavy fluctuation patterns too, but of very different scales and periods. The first thing you might ask about is how regularly irregular the ‘C curve is seems to be.  That variation is thought to be mostly due to annually shifting ocean currents, along with weather system changes and the difficulty of measuring the temperature of a complex varying world.  

The ‘C curve (Figure 4) also shows the two ‘Great waves’ (#1 and #2) in earth temperature that appear to be independent of the greenhouse effect. The dotted red line was visually interpolated as the midline of the irregular but seemingly quite constant fluctuating annual temperatures of the HadCRUT4 data. The blue dotted line was added to suggest earlier large waves in earth temperature copied from the shapes in the ancient temperature reconstructions seen in Figure 5. I physically overlaid those reconstructions of ancient temperatures on Figure 4, drawing a continuation of the Figure 4 midline curve that fit the Figure 5 curves.

One might say the minima of the great waves in the ‘C curve display a trend somewhat like the general trend of the PPM curve, say from 1780 to 1980. The one shape that makes the two curves seem really connected, though, is the way the sharply rising PPM curve (the implied cause) and ‘C curve (the implied response) both start following a “hockey stick shape” in the 1980s. It even seems the shape of the ‘C curve interrupts the great waves as it takes off exponentially, breaking a rhythm that seems to go back many centuries. There is a possibility that the great waves represent upper atmosphere standing convection patterns waxing and waning, something that increasing convection intensity could interrupt. Perhaps that would help others find what the great wave cycle, or not. Since theory suggests the trends of both cause and effect have a linear component Figure 6 shows a linear scaling of the PPM curve to see if it and the ‘C curve can fit.

Figure 5 – NOAA (2007) 1300 to 2007 Northern Hemisphere record of temperature reconstructions. Measured from a 1881-1980 baseline. This it taken from a longer history keeping the units and adding a title and dates 1780 and 1880 (brown). That is the period after the greenhouse effect began before it was visible in the records of earth temperature. The red line shows an old NOAA speculation that warming developed earlier and slower than found here.

Scaling CO2 PPM to Make a ‘C Proxy – The reason to scale PPM to emulate the dynamics of ‘C curve is simple. The ‘C fluctuation is so erratic the variety of curves to predict its future is rather extreme, so people have been generally using a straight line. An exponential curve is not a straight line, though. So the quite regular shapes of the PPM curve, including its clearly measurable growth constants, 1.48 % before and 1.9% currently, do make it a prime candidate as a useful proxy. Even if the trend has a clear direction now we of course have to allow for increasing uncertainty over time. Adding to that are the plans for dramatically cutting CO2 despite a world economy dramatically increasing its production, a tug of war that could be interrupted by actual war or other economic downturn.

Where the current stable growth rate of climate change seems headed, knowing the PPM curve should be linearly proportional to the greenhouse effect, we experimentally scale CO2 PPM see if it fits the ‘C curve in a logical way (Figure 6).

Scaling the PPM curve to fit the ‘C curve makes a PPM’C proxy curve, hoping to fit the midline of the highly irregular ‘C curve from 1980 to the present. Both the units and the baseline are not determined, though, to produce the proxy curve in PPM’C = A*PPM + B, using a linear scale factor A and a baseline B. A third determinant is then finding a optimal fit between the very different earlier shapes of the curves. So basically I tried lots of things, and found my initial assumptions were mostly wrong. Initially I made the mistake of trying to fit the PPM’C curve to the midline of the earlier ‘Great waves’, and tried several ways until it was clear they were all wrong.

Then I realized those earlier great waves were really not related to the greenhouse effect. So my greenhouse effect projection might better be interpreted as coming up under the earlier systems, like it actually looks. That was purely a graphic device at first. Then when I adjusted the PPM’C curve to pass under the ‘Great Waves’ I set it to go through the miline of local fluctuations instead of the Great Wave departures. Suddenly the fit of rapid growth period became as perfect as I could ask for. I spent some time trying to figure out why, studying all the loose ends, in the end resolving that’s what the data seemed to say. That PPM’C curve then becomes the hypothesized most likely “real” rate of greenhouse effect climate change, and offering a much more narrowly regulated way for projecting its future. 

Figure 5 shows both the best fit scaling of the PPM’C proxy curve (dark green dashed line), and its extension to 2050 at its presently stable growth rate of 1.90 %/yr (dashed light green line). Yes there are various uncertainties, but the threat of climate change so far has seemed to be from underestimating, not overestimating, and the findings do appear to be well within the IPCC uncertainties given the difficulty of projecting the temperature data directly.

I think it means that reaching 1.5 ‘C by 2030 is a much more probable estimate of the current trend than reaching 1.5 ‘C by 2040.

Figure 6 – The PPM’C curve scaled to closely fit the HadCRUT4 data and then projected at the homeostatically stabilized growth rate of observed in atmospheric CO2. How long this projection might hold depends on how robust the global natural and economic systems driving the growth rate in atmospheric CO2.

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The Economy as a Whole – How great a new threat this acceleration in atmospheric CO2 pollution and its greenhouse effect are seems to rest on just how stubborn the global homeostatic regulating systems observed are. That could really change the climate mitigation picture, and help explain why there has been only negative progress in slowing CO2 pollution. So far is seems to have been neglected, with negotiation over mitigating climate change not seeming to take into account the organizational inertia and persistence of the global economic system as a whole.

Figure 7 shows a group of major indicators of the global economy that were selected for having constant growth rates from 1971 (the earliest data for some) to 2016. The GDP PPP curve in trillions of 2016 dollars is growing the fastest, and each of the other curves was indexed to GDP in 1971 in proportion to their relative growth rates. For example, since total economic energy use is growing at about 2/3 the rate of world GDP that variable was scaled to 2/3 of GDP at 1971. This device displays the steady relation between them called “coupling.” That the same proportionality of the growth curves is constant throughout it indicates each of these curves reflects the behavior of the same system. What seems to cement the view that the global economic system appears to be behaving as a whole is the visual evidence that the data of each of these series, like the CO2 PPM data we discussed at length before, seems to fluctuate homeostatically about the growth constant.

What physically coordinates the economy’s coordinated relationships between different sectors displayed here as growth constants seems likely to be cultural constants of each cultural institution, or “silo” of the world economic culture. Every community seems to develop its own expected way for things to work and change and seems to become the way the different sectors end up coordinating their ways of working with each other. That all of this is organized primarily around the use of the exceptionally versatile resource of fossil fuels then indicates that a deeper reorganization of the economy than a swapping of one set of technology for another will be involved. It should suggest to any reader just how very much of the world economy would need to be reorganized, and to be reminded that the last times the world economy was sufficiently disrupted to be reorganized were during WWII an the 1930s.

This topic is also the subject of a longer research paper. Science review drafts are likely to be available later in April 2019.

Figure 7. The global economy working remarkably smoothly as a whole system of coordinated parts, seemingly much like theory says it should, but most people don’t see because they don’t look at the behavior of the system as a whole.
Figure 8 – Smoothed annual growth rates of recent world energy use and CO2 emissions, showing close coupling of their fluctuations with relatively insignificant trend.
Figure 9 – Log Plot of Figure 7 variables with a 1780 to 2020 time scale. The backcasting of their exponential constants displays the convergence with the backcast GDP trend of four of them at ~1935 and with two others (blue circles) at ~1920. The effect implies the stable coordination of the parts of the global economic growth system established by the 1970’s was in the 1920s and 30s.

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A draft paper Coupling of Growth Constants and Climate Change has full details on the data sources, methods and references:

Data Sources:

  1. Atmospheric CO2 PPM 1501-2015: OurWorldInData.org 
    https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions 
    as well as from the Scripps source directly:
    (Scripps, 1958 to present)(Macfarling Meur 2006)  
    http://scrippsco2.ucsd.edu/data/atmospheric_co2/icecore_merged_products 
    “Record based on ice core data before 1958, and yearly averages of direct observations from Mauna Loa and the South Pole after and including 1958.”
  2. HadCRUT4 earth temperatures 1850-2017 – Rosner:   https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions
  3. The world bank was my source for GDP PPP and for from 1990 to 2016
    – https://data.worldbank.org/indicator/NY.GDP.MKTP.PP.CD?end=2016&start=1990
  4. World Food Production – 1961-2016 FAO:
    http://www.fao.org/faostat/en/#data/QI
  5. World Meat Production – 1961-2016 Rosner – OurWorldInData: https://ourworldindata.org/meat-and-seafood-production-consumption
  6. Modern CO2 Emissions – 1971-2016, Archived IEA CO2 data extended with WRI CO2 emissions: https://www.wri.org/resources/data-sets/cait-historical-emissions-data-countries-us-states-unfccc
    – Because the latest economic CO2 emissions data is 2014 not 2016 as for other data, the trend of atmospheric CO2 was used to project the economic emissions data for the last two missing data points, showing no anomalous direction. https://www.co2.earth/annual-co2
  7. BP offered energy data in MtOe in its “Statistical Review of World Energy – all data 1965-2017”
    – https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/downloads.html
  8. The IEA news item statement that CO2 flattened for 2016 and 2017 was used, just to show how little effect it would have if true
    – https://www.iea.org/newsroom/energysnapshots/global-carbon-dioxide-emissions-1980-2016.html

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Work in progress…
Below this line is old text that may be edited in pending updates.

It’s a powerful technique for understanding complex systems, such as the world economy, that behave smoothly as a whole.   The most important observation is just that.  The system as a whole and these whole system indicators are not separate variables, and the smoothness of the curves shows the system as a whole behaving smoothly as a whole over time. 

From our local views of the world that often does not seem to be at issue, though it really is the main force behind all the changes everyone is struggling to adapt to.  Individual businesses, cities and countries generally have a quite irregular experience, as their roles in the whole continually change.  What the smoothness of the curves and the change in the system as a whole really means is that the world economy is working the just the way it is (financially) supposed to.   It is being globally competitive the way money managers manage it, and continually reallocating resources and business to where they will be best utilized, resulting in most every part having somewhat irregular experience to make the whole behave smoothly.   The uniformity of these global indicators also says is that their origins all point back to ~1780, when modern economic growth began.   We have reasonable measures US economic growth from ~1790, …and so went the world!  

Smooth exponential curves and the systems generating them are, of course, among the things of nature with inherent “shelf lives”, relying on systems of developing organization of multiplying scale and complexity, certain to cross thresholds of transformative change.   In nature, growth systems generally develop to one of two kinds of transformation, stabilization or destabilization, the crashing of a wave that doesn’t last for example or the thriving business that can last for generations.  What characterizes the difference for the emerging systems that last is that, while becoming strong with compound growth (like the systems that don’t last also do), they become responsive and refine their systems to stay strong.   In economic terms that’s remaining profit seeking they “internalize their externalities” to mature toward a peak of vitality rather then failure.   It’s a choice made in mid-stream.

Understanding what will make that difference in outcome for our global growth system will partly come from people getting a better understanding of how we got here, as shown in the Figures 1, 2, 3 & 4.   The growth of technological civilization relies on ambition, creativity and resources, and methods that we could potentially change.  How economic growth is largely managed by the application of business profits to multiplying business developments, what makes GDP to grow.   If our decisions were to internalize our externalities that is also one of the things that might change, without really changing human ambitions, creativity or resources.

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JLH

Only Healthy Cultures make Healthy Economies

Announcing the publication of
6/28/18

Culture, Finance-for-Development & tPPPs

Jessie Henshaw*

A less technical synopsis,
7/12/18

I’ve been observing the UN SDGs as a natural systems scientist since 2013 when I saw with some surprise that the one topic both Country delegates and Civil Society groups could agree on was the wording of the ideals for global development.  Even when the Co-Chairs, Ambassadors Korosi, and Kamu, began persistently asking for the discussion to turn to means and methods it never did.  Ideals are wonderful, but the strains the SDGs are responding to are still growing, as the global disruption of human cultures by the growing intrusions of the economies of the world powers continues.  That’s a problem not yet to be studied and discussed.  Why?  Partly to be “diplomatic” and partly not having a model for human cultures as living social organisms that carry all our shared ways of knowing living.   Still we need a way to discuss the rapidly growing strains on human and ecological cultures caused by accelerating economic growth, a global cultural sickness.

As growth presses the limits of the earth and challenges the world to ever faster rates of change, the damage to nature and human society is more and more lasting.   That’s a conclusion you can reach from many directions I think.  The communities the SDGs aim to help seem mainly deeply rooted old cultures that are now “failing to thrive.”  That is a living systems problem, not a numbers problem, as the SDGs were designed to solve.  Failing to thrive is more like a “lack of meaning in life” dilemma, requiring a different approach.  It’s also a symptom that one can use to map the problem worldwide and begin to look at its real dimensions.

Our accumulated ways of knowing and living  are stored only in our cultures

Failure to thrive seems to hit both indigenous cultures worldwide and communities within economies where “creative destruction” is leaving lasting scars, like rural flight or outsourcing that hollows out a region.  One example is the deeply alienated culture giving support to Donald Trump in the US, distressed by the world changing so much around them.  There are also non-thriving local cultures in North, Central, and South Africa, as well as in the Middle East and North, Central, Southern and Eastern Asia, as well as in Oceana, Australia, North and South America.  It’s not “the same old thing,” but a truly accelerating global plight, seeming to be of all the cultures that didn’t welcome or were disrupted by the intrusive growth of the world powers.

Human cultures are truly the crown jewels of humanity, though, where most of our gifts come from and are on display.  They are the unique individual species of the human ecology.  If you think about it, there is no other place on earth for the safekeeping of all our ancient accumulated ways of knowing and living. Each culture either crafts its separate way of knowing and living or branches off from another.   They are our most important gift, evidently now absorbing a great deal of abuse.

With each culture being its own “knowledge system” it keeps people from making sense of any other culture, or even our own.   If you trace the evidence, it does check out.  We get the large part of our ways of understanding things during early childhood, by what you might call ‘osmosis’.  Some say it’s “too close for us to see,” or that our mental way of seeing is functionally like a camera and its lens, that are never visible in the pictures they take.  Cultures also have a deceptive “cellular design.”  Their ways of knowing and living are internally shared, and not experienced from the outside.   Even with extended immersion, an outsider does not develop a native feeling for another culture’s roots.

The great challenge we face today is that growth is an ever faster process of expansion and change, *doubling* its demands on the earth and humanity every 20-30 years.   That radical rate of increasing demands is what eventually overwhelms the adaptability and resilience of people and the earth.  Living things are being pushed to keep mechanically doubling numerical returns for culture-blind investors, as if the earth was unoccupied.

That’s how the English occupied North America, a hundred years after the first settlements rapid expansion began with importing slave labor then a wave of settlers swept across the rest of the continent, as if it were unoccupied.  Elsewhere the economic powers built systems for globally harvesting resources, placing overseers where needed to manage their access, as if there was no one else there.  Today it continues with how global capitalism still relates to the world, measuring its success in rates of accelerating expansion alone, as if no one is here.  What’s most surprising perhaps, is how very effective our cultural blinders are in hiding our blindness to our own and other cultures from us.  That is, hidden until you have an indicator like the glaring disruptiveness of ever more sudden change.

So what would relieve our fast growing societal distress?    There’s a new business model expressly for responding to it, to use biomimicry for how nature builds thriving ecologies.   If interested there’s a longer discussion article on how healthy cultures are the foundations of healthy economies and the business model for nourishing our cultures, that I refer to as “True Public-Private Partnerships” (tPPPs) discussed more in the essay  Culture, Financing for Development and tPPPs.

The new business model begins like any business, organism, or culture does, with a period of innovating and vigorous growth, making profits to expand its systems.  When the environment responds with increasing resistance or stiffening competition, the new strategy is to choose when and how to switch from maximizing profits for growth to maximizing long-term profitability to pay it forward.  That’s done by refining systems to operate in smooth harmony with each other and their world.  It’s a more gradual process but would produce more integrated development and be more profitable in the end, to combine human ingenuity and natural design.

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Do comment if this gives you questions or ideas!

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[*] Jessie Henshaw consults as HDS natural systems design science, sy@synapse9.com, offering insight into nature’s processes of negotiating change.  She uses natural systems thinking strategies (NST) with “action research” (AR) and architectural “pattern language” (PL) methods of collaborative developmental design.  The start is from recognizing that organizational processes in nature follow a familiar arc, beginning with bursts of innovation, and then refinement, leading to a final release (IRR).  That is not unlike how we all do home or office projects, in stages of immature then maturing growth then release, also seen in reproduction.  The system produced is first “framed out” with innovations then “filled in” with refinements and “delivered” as the release when ready.  Her current related research article is on how our Systems Thinking co-evolvolves with our Systems Making.

 

JLH

Evidence of Decoupling Still Zero.

The Growing Effort to Decouple GDP from Energy use and CO2,
is having no apparent effect,
raising serious questions about the nature of our plan.

The graph below (Figure 1) shows the 46-year record of world GDP PPP, Energy, and CO2, during which their growth rates have been in constant proportion to each other, called their “coupling.” The things to read are 1) the lack of accumulative departure from the steady trends, and 2) how closely the exponential trend lines (dotted) follow the data.

It shows that the long trend still holds despite both big efforts and bigger promises that accelerating growth using more efficient processes would separate the expanding economy from its impacts.  Focusing so much on the “positive” completely disguised the big picture, though, that in 46 years there has been no accumulative effect at all.  So there’s a lot to explain, yes, but the graphs below show persistent regular behaviors of the economy as a whole resilient system, a problem not yet faced at all.

Figure 1. Coupled Growth Trends of World GDP, Energy & CO2, showing how the three move together at proportional growth rates, as parts of a whole system.

That energy use and CO2 emissions are now still growing at the same rate as 40 years ago is strong evidence that none of the sustainability measures such as exceptional efficiency gains said to decouple the economy from its impacts, have had any effect at all.

The irregularly fluctuating curves below (Figure 2) show the annual rates of coupling if world Energy and CO2 growth rates to World GDP (PPP).  The scale at the left shows their locally averaged growth rates as a fraction of the locally averaged GDP growth rates (to somewhat smooth the curves) going below zero once.  The important thing is to notice is that the fluctuations vary around nearly horizontal trendlines.

It’s as if the economy is guided by an “invisible hand” keeping the fluctuations symmetric to the near constant trend.  It says the fluctuations have been adding up to no effect.  The likely cause of this is how a competitive economy naturally works.  Technology and resources are supposed to be treated as being fungible assets, to be constantly reallocated to maximize profits.  In the data, that functional coupling between the physical and financial systems of the economy is shown working rather smoothly, replacing less with more profitable assets to maximize the growth of profits for the whole.  That stable coupling of managed assets to growth is then an apparent natural emergent property of the system as a whole, as a partnership between human cultures and the financial world’s effort to maximize growing profits.

Figure 2. Regular fluctuations of Energy and CO2 coupling with GDP, have repeatedly been claimed to be evidence of rapid decoupling… ignoring how very regularly the periods of apparent decline were followed promptly by reversals, as if irregular waves of water seeking the average level. 

 How the world community came to say that “sustainable development” would reverse this stable natural relationship between the economy and its resource uses is described in more detail in April 2014 in The Decoupling Puzzle. Small fluctuations do keep causing excitement for both devoted climate deniers and sustainability advocates, though, each picking out brief trends seeming to affirm their hopes, like the five periods of apparent rapid decline in CO2 to GDP coupling shown here.  The real evidence is that the local fluctuations never seem to result in a change in the direction of the whole, like ripples on a pond that always level out.  The latest dip in the CO2 coupling trend has been claimed as a sign of turning the corner by the IEA, clearly unaware of the consistent pattern of that metric repeatedly fluctuating around a near-zero trend.

Added perspective on the global data is gained by plotting the ratio of GDP to Economic Energy energy, the amount of wealth produced with a unit of energy.  We call that variable “Economic Energy Efficiency,” the amount of economic wealth generated per unit of energy.  Having its growth rate = 1/3 the GDP rate implying that improving efficiency contributes 1/3 of the value of energy to the world economy, growing Energy use contributing 2/3 if the value.  That ratio demonstrates a general case of Jevons famous observation that in a growth economy efficiency results in growing rather than declining resource use and impacts.  Any way one reasons it, what is crystal clear is that in the last 46 years strenuous effort to use efficiency for sustainability have had the opposite of the intended effect, recreating the original problem rather than solving it.

Figure 3 The share of GDP growth contributed by Economic Energy Efficiency proves Jevons principle that in a growth economy efficiency multiplies energy use and all its accumulative earth impacts.


So we need to be suspicious of the world policy to maximize growth at any cost.  The costs are rapidly swelling not shrinking.  The other coupled impacts of growth also causing how people live being forced to change ever faster creating major disruptions and dissension all over the world is one of the biggest, though even the NGOs are very slow in recognizing.  In nature, growth is how all kinds of natural systems begin, but those we admire for their perfection turn to refining their designs before they climax rather than, driving their growth to the point of being torn apart of being exhausted.

That’s the trick.  Maximizing growth might seem logical as a way for societies to keep up with social distress and debts, but now it’s accelerating them.  So now we need to balance the attraction of short-term profits and connect them all the unbalanced disruptive changes that now surround us.  We talk lightly about replacing people with robots, for example, overlooking that the robots only work for the banks.  That’ll make people and governments ever more indebted and incapable of responding to climate change, for one problem.  And that chain of consequences goes on and on, that is as long as we keep ignoring how natural growth systems that avoid the problem work.  More disruption is not the solution, only moderation.

There’s an alternative business model that could serve as a general design for growth without disruption, one that switches to paying the profits forward once any debts have been paid back.  Once understood, that is what would achieve truly integrated, thriving and self-limiting development, as biomimicry of ecosystem designs.  It is discussed in more detail in the article linked from my next post, Culture, Finance-for-Development, and tPPPs.

Use biomimicry for how nature uses growth to build thriving and enduring systems.

It would be a way for businesses large or small to begin to experiment with how nature succeeds in creating beautiful, thriving, and purposeful systems.  It’s a fairly simple formula.  It’s also a practice we all know well for how to successfully relate to other people and how to successfully complete business or home projects.  It starts with building up innovations to then select what to refine for making the result resilient and purposeful in its environment.  If we approached every new relation or project by piling on new experiments with no turn toward refining something to last in the end, all the effort would go to waste in the end.

To start you study the similarity between nature’s way of building things to perfection and how we do our own home or office projects! They all take place in “three acts.” The first act is for “innovating, the second for “refining, and the third act the “release” of the finished product into its waiting environment (IRR).  You see the same three acts in the birth cycle, and in the start-up of new businesses too, as well as the formation of new cultures and most every other kind of individual development.  The trick is really to pay attention to the inspiration that starts it off, as something to fulfill.  That lets you anticipate and move smoothly between the stages of emerging development, first adding up more innovations, then refining the ones worth keeping to the end.  It’s what comes most naturally when we can see the whole effect.

_________________

When you can see the whole it’s easy to recognize the point when adding more innovations begins to work against getting something finished, called a “point of diminishing marginal returns.” Of course on a home or office project what tells you it’s time to shift to finishing what you started is just sensing what can you finish while you have time and resources.  For anything measurable, like wealth, the point of diminishing marginal returns is when it becomes more profitable to put efforts into getting things to market rather than try more experiments.  To apply it to the world all you do is ask: “What is our real plan here?” and look around for how to perfect what we started, and at the right time stop taking on more and more that we probably won’t be able to finish.  It’s a matter of shifting to pursuing achievable goals rather than hanging on to thinking ever bigger with no end in sight.  Reaching for the right goal doesn’t necessarily make the work easy, of course, particularly for big personal, community or business projects.  It just makes the work a lot better, and the end something fulfilling and rewarding.

I discuss that as a way to measure truly lasting success for the UN’s 2030 Agenda and its Sustainable Development Goals, instead of just “more, faster” the ways the UN’s goals are like the goals of business-as-usual, discussed in more detail in Culture, Finance-for-Development and PPPs.

JLH


Analysis Notes:

  • The global GDP PPP curves show IEA data from 1971 to 2008 spliced to overlapping World Bank Data from 1990 to 2016.  The curves for global Energy are from BP statistics, and the Global CO2 curves show data from WRI.
  • The Energy and CO2 curves were each scaled to the GDP curves in proportion to their average growth rates for a graphically clear and honest comparison.
  • dy/Y is the ratio of the change in a measure over the total, like an interest rate or growth rate measures.  I get smoother curves by blending a bit, using a center-weighted 5 point bracket.

Data Sources:

  1. The world bank was my source for GDP PPP and for from 1990 to 2016
    https://data.worldbank.org/indicator/NY.GDP.MKTP.PP.CD?end=2016&start=1990
  2. World Meat Production – 1961-2016 Rosner – OurWorldInData: https://ourworldindata.org/meat-and-seafood-production-consumption
  3. World Food Production – 1961-2016 FAO: http://www.fao.org/faostat/en/#data/QI
  4. WRI has a very nice set of data on CO2 “Total GHG Emissions Including Land-Use Change and Forestry – 1990-2014” from the CAIT Climate Data Explorer – http://cait.wri.org/historical.
    – Because the latest economic CO2 emissions data is 2014 not 2016 as for other data, the trend of atmospheric CO2 from CO2.earth was used to project the economic emissions data for the last two missing data points, showing no anomalous direction. https://www.co2.earth/annual-co2
  5. Atmospheric CO2 PPM 1501-2015                    
    OurWorldInData.org:
    https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions
    From Scripps source directly: (Scripps, 1958 to present)(Macfarling Meur 2006)
     http://scrippsco2.ucsd.edu/data/atmospheric_co2/icecore_merged_products
    Record based on ice core data before 1958, and yearly averages of direct observations from Mauna Loa and the South Pole after and including 1958.”
  6. BP offered energy data in MtOe in its “Statistical Review of World Energy – all data 1965-2017”
    https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/downloads.html
  7. The IEA news item statement that CO2 flattened for 2016 and 2017 was used, just to show how little effect it would have if true
    https://www.iea.org/newsroom/energysnapshots/global-carbon-dioxide-emissions-1980-2016.html

UN SDG’s and HLPF – the whole-system thinking needed

Setting Our Whole system goal,
Making the Earth our good home.

Much of my effort over the past five years fosuces on working with civil society organizations at the UN on the world sustainable development goals (SDG’s).   This year, needing to take care of other business, I’m sitting out.    It may be ironic, of course, as the challenges of implementing the UN 17 separate goals probably makes:

more and more participants think of how the goals need to all work together,
and can’t individually be achieved without the ‘nexus’ of the whole. 

Ultimately my years at the UN was mostly spent identifying the widespread absence of systems thinking in the SDG’s, watching somewhat painfully as the UN spent all its time creating lists of separate goals, as if unaware of their interlinkage. The interlinkage most neglected of course was that of *MONEY*, our main tool and problem.   So my writing of that time may be a little out of date.   I can tell that much of the systems thinking I found so absent before still is, however.

I have lots of other writings on how “systems thinking” for our world needs to become “systems making”, the next step toward true “homemaking on planet earth”.   Finding how societies can make their good homes on earth is the answer.   Like ecologies of other kinds do, we can invent our way out of the deepening trap we now find our world economy in, using nature as a guide.

I got fairly frequent applause at the UN,  enough to know people are listening, but to my knowledge no one ever followed up on my carefully  reasoned recommendations, and no one ever asked me to be on a panel discussing them either.   So here I’ve collected some of my old lists of observations on the process, and reiterate my offer to help people understand the guiding patterns of natural system design that I’ve spent my life studying.

A Youtube of one of my interventions for last year’s HLPF gets right to the heart of the matter too!

A good Youtube – Impacts Uncounted 2016 UN HLPF S4

 

Notes on how the “UN Development Goals… leave out the Common Needs”(1)

  1. The SDG’s Omit:
    1. how the centers of power can become foundations for a sustainable future
    2. what habits keep people entrapped in the web of ever growing economic inequity.
  2. It also fails to use systems biomimicry to help us design a world that works.
  3. They also ignore the need for a “soft landing” for the whole system, for
    a. creating a stable world commons…
    b. not just to giving competitive edges to the disadvantaged
  4. They don’t aim to “internalizing all externalities” like the “World SDG” offers.
  5. They also generally omit ideals for the earth as a whole, to make it our good home.
  6. and blindly continues to promoting compound global growth
    a. when we are already pressing hard the global natural limits,
    b. not looking to relieve of the strains but add to them.

 

Here are other short posts on the systems thinking to bring into the UN’s discussion to guide us toward the long term goal of making Earth our good home:

  1. https://synapse9.com/signals/2013/07/01/un-devel-goals-omit-common-needs/
  2. https://synapse9.com/signals/2013/04/27/missing-ecological-thinking/
  3. https://synapse9.com/signals/2013/05/05/whole-culture-led-not-tech-driven/
  4. https://synapse9.com/signals/2013/12/05/un-owg5-missing-topics/

 

JLH

Why is an economic tornado always on the road straight ahead?

I also can’t help returning to a central subject of collective organization I’ve studied my whole professional career, the seeming fate of economies to bring periods of high cooperation to an end with total disaster.   The main cause could of course be said that no one in particular is at fault.   But there is science enough to identify who could intervene, and do something about it.

My previous post was on the work of  Ernst Ising, the physicist who solved a range of collective behavior problems, and how pattern language design science might address the question of what kinds of environments are required for emerging local phenomena.   Why economic collapse is always on the road straight ahead for our form of highly cooperative modern  economies is one such subject I’d like find physicists using Ising’s work on with.

One might wonder about what keeps driving our highly cooperative world economy toward escalating conflict.

All of humanity seems driven by a “rat race” toward extremes of destructive competition all the time, unable to escape, with most everyone feeling they are reacting in their own defense.   That’s not a model for a safe and secure world.

Could we possibly trace how the economic forces, like those driving everyone to achieve rapid growth in economic productivity, and so for the earth and humanity, creating circumstances ripe for triggering grand economic collapses.   If we can identify the system doing that we could identify interventions well in advance, to engage a “general protection fault” to avoid the usual mad collective collapse.

Why is an economic cyclone ALWAYS on the road straight ahead

 

I for one think it boils down to demanding people do impossible things, demanding of our society to do impossible things, like continually doubling the speed at which we collect and use energy and expand our control of the earth.   That can only end in tragedy, like it has for economies again and again. Why economies are driven to it, to be ever more productive at ever faster rates, follows unavoidably from their organization for maximizing compound returns from investment, making ever more from ever less.   Like being forced to “make bricks without straw”, the regular investment of profits in escalating to create ever more daunting competition ultimately compels cooperation in cheating.   In the end that unavoidably disrupts the order, as one of the natural outcomes of pointlessly taking the compounding of returns to its natural limit.

We could do something else if we understood the problem…

 

jlh

The duality required for collective organization.

An interesting global question is, to me, raised by Ernst Ising’s work in physics – (see the arxiv pre-print on his life and work if interested. https://arxiv.org/pdf/1706.01764.pdf)

Ising’s main work in the 1920’s was deriving a mathematical explanation for ferromagnetism, the ability of atoms in certain solid metals to develop aligned spins, and exhibit permanent magnetic fields in there surroundings as a result.   The part of that might be of interest from a pattern science viewpoint is how his model has been successfully applied to numerous collective phenomena, both other emergent collective atomic behaviors like magnetism as well as emergent collective macroscopic behaviors like the emergence of organization in crowds.

Ising’s general equation

The math, honestly, is beyond me, but there’s an interesting assumption in the work that might be discussed from a pattern science perspective, that the math rests on treating such phenomena as arising from purely local interactions.

Ising Said: “So, if we do not assume [ ] that [ ] quite distant elements exert an influence on each other [ ] we do not succeed in explaining ferromagnetism from our assumptions.  It is [thus] to be expected that this assertion also holds true for a spatial model in which only
elements in the nearby environment interact with each other.”

What I suspect is that there’s more of a wave/partical type duality present, involving both local and contextual interaction
in bringing about collective organization.

In the collective phenomena we observe there is certainly has a strong local character, whether it’s snowflake formation, ecologies, social movements or probably also the punctuated equilibria of emerging species.  All such collective phenomena seem to arise in relatively small centers and then spread mysteriously.  They also seem to require specially primed and fertile environments, as global conditions that are receptive to the local accumulation of collective designs.

So my question is who else is talking about this pattern of nature.    Is this raised in Christopher Alexander’s “The Nature of Order” or other pattern language writings?   Is it raised in the work of anyone else writing in the pattern language field?  More specifically, does it need to be understood to know how to describe the contexts we work in, perhaps such that a calm and receptive and so fertile context is needed to be a good host for pattern designs to flourish?

___________________

jlh

Is Science Coming Full Circle??

A change in natural science is emerging along with “computing”
turning away from using theory & equations as a guide,
toward using data pattern recognition for
naturally occurring systems revealed in the data to be a guide.

Preface

Note: About 20 Years ago algorithms were developed for selectively extracting differentiable continuities from raw data, making a major step beyond “splines” for true mining of natural continuities from noisy data without regression.    The result was quite successful forensic pattern recognition of  discovered natural systems, their forms and behaviors.   Combined with a general systems “pattern language” based only on the constraint of energy conservation, that pattern mining has provided a very productive alternative to AI for investigating naturally occurring forms and designs.  The one unusual leap for applying scientific methods was to use it to capture the great richness of natural textures available from studying uniquely individual cases and forms found in nature.   That is what overcomes the worst faults of studying individual cases, and so instead greatly enriches theory with directly observed phenomenology.  The rudimentary tools successfully developed have been proven useful again and again with subjects such as illustrated below.  10/21/16

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A long central principle of modern science, relying on defining nature with the information we can find, is considered here by way of  eight examples of how important it is for science to also rely on doing the opposite, looking for patterns in the information we are missing somehow.   Doing much the reverse lets us use the information we have to ask better questions about what nature is hiding from us.  

It’s such an odd and obvious mistake to stubbornly treat nature as our data, as Neils Bohr and Popper insisted on and the QM community has maintained.   Being limited to analysis and data creates a large blind spot for science, made unable by that limitation to learn from observation, and to see clearly how very different the “data world” (what fits in a computer) is from the “material world” (what doesn’t). The puzzles of found in natural patterns, turning up in ‘bigdata and various pattern sciences seems to be putting all of these matters into question again.    

So I may take some unfair advantage, perhaps, by making a little fun of that prior arbitrary constraint on scientific inquiry, insisting that nothing we have no data for can exist.   That of course is almost everything when it comes down to.  It’s no joke, though, that our data is decidedly inferior for defining nature.  Here and elsewhere I tend to allow that nature defines itself, as I certainly don’t do it.

The “Impacts Uncounted” article mentioned describes a simply enormous worldwide neglect in economic accounting, a huge mismeasure of lasting business environmental impacts.   It’s caused by the traditional insistence on trusting the data at hand and refusal to look for what data is going uncounted, as if the fact that we can only study the data we have means nature is not being misrepresented by it, a curiously deep concern for understanding the scientific method.  In reality there is more to life than the data we have.   Treating “science” as whatever our data defines, then, actually means “flying blind” regarding all the kinds and scales of phenomena going unmeasured, the difference between nature and data going unseen.  For accurate accounting, even older scientific principles need to apply, such as defining units of measure in relation to the whole system or “universe” for that measure, not just the part easy to measure, and so “Impacts Uncounted” is the effect of counting the global impacts of business using local measures, as is today standard around the world, a big mistake.  

So these 8 examples are “data visualizations” that neatly expose where important data is very much missing, as a guide to where to go and look.   Those hiding places exposed as gaps in the data turn our attention to phenomena of perhaps another kind or another scale, or on another plane with material influence perhaps.  That is then what needs to be discovered and looked into. to really understand what the measures display and the systems or events they refer to.    That the data available, then, always points to phenomena beyond the scope of the data to define is both the oldest and perhaps now the newest of deep scientific principles for interpreting what we see.

Is science coming full circle…?  The answer seems to be YES!

 

Persistent patterns in data generally reflect complex natural forms of design, complex and complicated well beyond what data can define.  So we present data in a way to helps show someone what’s missing.

Data from a natural source is generally biased and incomplete as a result of how it’s collected, and a “proxy” for various things other than what it is said to measure. So not really knowing what it measures, it is best studied as being another way of sampling an undefined universe, to become meaningful by discovering its boundaries

Patrick Ball’s HRDAG[1] methods demonstrate comparing sources for death records in conflict environments, using the differences and overlaps to reveal the true totals. My own research shows environmental impacts of business are undefined, lacking a common denominator to make them comparable as shares of the same universe.  Correcting the mismeasure appears to increase the impact scale of business by several orders of magnitude[2].  In both cases characterizing the universe the original data is implicitly sampled from serves as common denominator for making the original data meaningful.

For discussing basic explanatory principles of physics used for forensic systems research[3]

1.   See where hidden connecting events shifted the flows??

test sext
[The missing data is about the unstable states, the markers of whole system change in design]
Continue reading Is Science Coming Full Circle??

Regions Left Behind

The discussion of the UN’s  Sustainable development Goals (SDG’s) focuses on the poor, and “Leaving No One Behind”.   That overlooks that it’s most often the growth of the world economy that made older parts of the economy outmoded, and leaving whole communities behind as the world economy moves on to what’s more profitable.  This discussion illustrates more of the detail, how innovative change like the “green revolution” thought to be for feeding the poor.   It would quite predictably also leave more and more agricultural communities behind, …as everyone has increasingly seen in their own regions… like in my own home region of New York State, exhibiting common symptoms of being economically left behind you see around the world:

  1. abandonment of rural communities
  2. as farmers can’t afford sell to feed their own communities
  3. the flight to cities with now skills to sell
  4. the growing refugee and landless migrant populations
  5. growing youth cultures with little to do but to get angry
  6. or that are fighting over resources degraded by over use

And that’s only one of the kinds of distressed communities unable to keep up with the competition ans the most profitable invest their profits in becoming more profitable and more and more people can’t keep up.

A natural pattern of the growth systems is using profits to develop innovations that are more profitable, which of course also multiplies the disruption of the ways of life being displaced..., that we've called
1. & 2. A natural pattern of the growth systems is using profits to develop innovations that are more profitable, which of course also multiplies the disruption of the ways of life being displaced…, that we’ve called “externalities”, as if they didn’t matter, and don’t get counted. It leaves more an more communities behind at the limits though.

These all actively leave whole societies of suffering people behind in a way that is not reversible.   It’s the real predictability of ever escalating competition causing all these uncounted impacts of how we invest money in growth for the wealthy, that undermining the sustainability traditional economies.   That’s the real quandary here, it so very predictable.    What DO development planners think about, not to ask who the latest innovation will put out of business.   Well, to do real sustainable design, we’d need to add that question to the list, what will our “killer app” put out of business?    It’s always a trade-off when you “create jobs” of any kind, that there will be jobs lost elsewhere with a very high probability.

Conceptually the lasting profitability option is fairly simple, gradual stabilizing of the whole system profit as the profitability of growth stops growing as fast, leading to a steady state creative living.

The Lasting Creative Spira, so familiar in life, only requiring that investment not be compounded as growing innovation meets diminishing lasting returns.
3. The Lasting Creative Spiral, so familiar in life, only requiring that investment not be compounded as growing innovations meet diminishing lasting returns.

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For the big picture of how we got the math wrong…

The economic impacts we don’t count turn out to be the great majority of disruptive earth and societal impacts we experience (seeImpactsUncounted ).  They even have a name, the “externalities” incurred as liabilities of obtaining services by paying someone else to deliver the goods.   So those are actually internal to the operating necessities for running a business, only external to the accounting we’ve been doing.   Counting them is actually just ruled out for SD accounting, by a “stroke of a pen”, as effects that decision makers don’t feel responsible for, and have no direct control over.   Those include impacts of financial decisions, for investing in disruptive innovations, also excluded from the discussion of impacts by the stroke of a pen.

Some impacts of finance are easily measured and some not, so to fully understand the problem takes sorting through what is accountable and what is not, develop different ways of assigning shares of responsibility.    Certainly the ones that are measurable should be counted.  They’re mostly counted globally, like soil and water depletion and lots of other things.   They’re just not at present assigned to anyone’s responsibility.  Doing so proportional to share of world GDP would be both scientifically correct and perfectly fair.   So a study group would pick one or two such questions at a time to see what can be learned.

Another concern is how the continual compounding of profits forces everyone in the economy struggle to keep up with financial demands for ever increasing productivity and competition…  what the phrase “the rat race” technically refers to.   It’s why we all seem forced to to run ever faster to stay in one place.   That’s of course not really sustainable, but very hard to know how to measure.   Still, it’s a very real kind of suffering and accumulative culture change, and connected to the escalating competition in the economy that leaves ever more people and communities behind, a kind of “destructive creation”.

In figures 1 & 2 illustrate how regions are left behind, using the example of how once thriving agricultural communities of New York State collapsed, leaving long term economic damage behind.   The question is where did the money go that once invested in productive farming in the region.   The costs were left behind as the money fled to create the extractive industrial farming of the mid-west and elsewhere, mining water and fossil fuel resources very unsustainably, to grow corn, wheat and soy where it wouldn’t thrive naturally.  Of course, much of this is only observable in hind sight and not really manageable, but the costs to society clearly also do escalate.   That makes it imperative we take responsibility and do what’s right.    The driver is making more profits, for investing in even more competitive businesses, using “disruptive innovation” that also leavea ever more others behind somewhere too.

For many decades people have more often called that effect of disruptive innovations “creative destruction”, accepting that to make more money and increase the economy’s products, you have to destroy the economy’s old ways of making products.     The hard question is when to change from calling that  “creative destruction” to calling it “destructive creation”.    The programming of the economy to always grow that process seems to assure ever stiffer competition for everyone, all the time.    It’s so constant we might just take it for granted,… but as a continual culture change for pushing everyone to face ever stiffer competition for how they live, it’s certainly not sustainable.   As you push the limits then… it seems to naturally leave more and more people and environments behind, and be really more destructive than productive.

How that escalates is illustrated below, alongside the map of New York State, roughly showing the area of Central NY farming communities that vanished in the 50’s to 70’s, giving in to the competition from industrial farming.    We could count the region’s lasting economic and cultural damages, perhaps.   We can also see that the global corollary is of larger scale and seeming leaving more and more behind around the globe all the time.   We can see it was no one’s political decision, nor is there anyone else at direct fault.  We can see that kind of change is quite irreversible once it has happened.    We’d only know if we counted it, and attributed the costs to our financial decisions to profit that way.   As societal collapses are not reversible, we’d really need a more holistic way of measuring our impacts, to understand the costs of how we make money for our future.

Its SO predictable!

What would make people care??

What would let them notice??