“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.”
— 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.
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.
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.
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.
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.
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 proxycurve, 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.
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.
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.
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.
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.
Do comment if this gives you questions or ideas!
[*] Jessie Henshaw consults as HDS natural systems design science, email@example.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.
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.
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.
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.
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.
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.
– The wide implications relations based on fiduciary trust – JLH
Professionals making decisions for others have a duty to act in the client’s best interests, to the best of the fiduciary’s ability, as the basis of trusting the fiduciary’s services.
The law doesn’t limit “best interests” of others to short term financial gain, leaving open all other interests everyone has a right to, such as not being misled, living sustainably, respecting due process and receiving justice.
What has changed in the modern world is that we face more threats and know more about them, so now we can hold our professionals responsible, demanding our universal human interests be respected as their fiduciary duty.
Putting this on the human rights agenda would only take talking and writing about it.
– Current Law: The Fiduciary Duty for investors[i]
“Whenever you are dealing with someone to whom you will entrust your money, such as a registered investment adviser or a bank trust department, it is nice to know that, in the United States, they owe you what is known as a fiduciary duty. This is not to be taken lightly because, under the American legal system, a fiduciary duty is the highest duty owed to another person. It requires the fiduciary (the person with the obligation) to put the interest of the principal (the person to whom they owe the fiduciary duty) above their own.”
“This requirement to act in their best interest includes disclosing any conflicts of interest that may arise so they can be known ahead of time, leveling the playing field. Breaching the fiduciary duty can result in draconian punishments, including being barred from employment in certain fields, being banned from working with certain types of securities, being forced to pay significant civil and criminal penalties, the loss of employment, and, in some cases, felony conviction with accompanying jail time. To put it bluntly, the fiduciary duty has teeth.” [see source for rest of article]
“A “fiduciary duty” is required of a person who manages money, investments, or other property on behalf of another person. When the situation involves a board of directors managing a corporation, the fiduciary duty the board has to the corporation’s shareholders and investors is known as a “business duty.” A person who has a fiduciary or business duty is known as a “fiduciary.”
“A fiduciary duty requires more than the ordinary reasonable care that appears in most personal injury and tort cases. Fiduciary duties are generally split into two categories: the duty of loyalty and the duty of care. In some cases, board members may also have a duty to disclose information. They also have a duty to avoid conflicts of interest.”
“The duty of loyalty requires the person who has it to handle money with the best interests of its owner in mind. The fiduciary must put the owner’s interests before his or her own and may not profit from managing the owner’s assets without the owner’s consent.”
“In a business situation, the duty of loyalty requires the board of directors to run the corporation in the best interests of the shareholders. Directors have a duty not to let their personal interests conflict with those of the corporation.” [see source for rest of article]
Note: there is no limit to what “best interests” a fiduciary needs to serve,
1. There’s only a limit on their ability to serve them, and
2. All “best interests” would require not being misleading
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.
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
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 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. 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
1. See where hidden connecting events shifted the flows??
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:
abandonment of rural communities
as farmers can’t afford sell to feed their own communities
the flight to cities with now skills to sell
the growing refugee and landless migrant populations
growing youth cultures with little to do but to get angry
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.
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.
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.
Preface: The 1964 SEC rules change seems clearly connected, but what really happened to so dramatically change the whole economy at the end of the 60s?? Figure 1 belowshows that something DID abruptly change the whole future of the US economy, in about 1970, causing a permanent great acceleration in societal inequality.Figure 2 below also clearly shows the pattern of trading on the US stock market began to radically change in 1965 too. There’s also other evidence mentioned below on what happened. The Marketplace.org radio program 6/14/06 gave another part of the story for the evident sudden change in the relation between Wall Street and Main Street. They said it was what Milton Freedman wrote in the NY Times in 1970:
The big change began with a professor. At the University of Chicago, economist Milton Friedman (who would later win the Nobel Prize) wrote this in the New York Times Magazine in 1970:
“There is one and only one social responsibility of business — to use its resources and engage in activities designed to increase its profits.”
The coincident magazine article almost fits the data…, but when did a single comment by an economist suddenly change the world? Never of course. So I think it was some deep change in the rules of business, that may have been made possible by the SEC rules change of 1964. That the break was so sudden indicates pent up pressure for it that was suddenly released. The smoking gun is that the bottom 95% of household income levels suddenly went from growing together with the whole economy, to splitting apart. It reflects some kind of fairly sudden reprogramming of business. We were just computerizing everything, and standardizing new business and stock market accounting methods, so that would have to be somehow connected. The new definition of business value as the “bottom line” was being standardized at the time, along with maximizing “shareholder value”. Those changes would seem to have served anyone being paid in proportion to profits, shareholders, stock traders, executives… and to disadvantage everyone else. [1/1/2018]
For those less familiar with my work, I study an evolutionary development form of physics, using explanatory principles of physics to ask leading questions about how complex systems rapidly reorganize and change form, perhaps the most inexplicable thing nature does. The clue is that it is generally associated with the rapid expanding organization process of growth. Other scientific methods treat it only as a numerical shape, but there is much more going on. Much can’t be explained, but what can be firmly predicted is that any growth process produces a crescendo of change, that will upset its own process and cause it to change form. We should all learn to study that transition.
In the figure below, the economy as a whole is shown continuing to grow as before, while the various levels of household income suddenly split apart.
Whatever the change, it would clearly be catastrophic for the resilience of wage earning communities. The question remains whether what kind of culture change is exhibited in the data. Was it as I’ve suggested made possible and facilitated by the comprehensive SEC and Congressional revision of the stock exchange rules in 1964. Outwardly the SEC’s purpose was to bring the markets into the modern world, to make it more convenient, secure and efficient. Other things were happening too, seen in the trading data (2) in how suddenly after the rule changes were passed the behavior of the NY Stock market dramatically changed. There was an immediate wave of high volume trading unlike the past, seemingly ushering in the culture of fast and high volume trading for “playing the markets” we’ve seen since. It notably also included a redefinition of business value for the sake of the markets, redefined to be a single number, “the bottom line”, introducing the widespread use of the term to represent a new way of market savvy business.
If you think about how it might effect businesses, to be graded every month as succeeding or failing to make the “grade” set by market prediction of business value, it’s clear what a force it might become. For CEO’s and board rooms across America would be forced to make decisions favoring the expectations of the market. I have not found it yet, but my view is the some center of business thinking was discovering how much profit could be squeezed out of the economy if business was managed by computer for that purpose, and that was the pent up pressure that needed rules for rapid trading, ready to go as soon as they were in place. It would change business and investor decision making like school teachers required to “teach to the test”. As we know that raises grades an hollows out the student’s education. Here driving American businesses to meet the numbers, to please Wall Street set for “maximize profit at any cost” was very costly. Driving stock price increases with continual forced “efficiency” and “productivity” gains naturally drains a system’s resilience, as a real kind of enslavement. It requires endless cuts that dismantle what had previously been thought of as “good business”.
Prior study since 2010:
My first notes on the subject were in 2010. Your can find lots of examples of complexity itself being a natural limit to growth, and I initially associated this change in how the economy worked with the rapidly emerging complexities of life. We all experience life as a growing struggle, an escalating “rat race” of new complications, and a constant search for simpler answers. Clear evidence is found in the sudden rise in use of the phrase “information overload”, from the late 60’s on. At the same time there has been slowing use of the word “complex”, I think indicates the complexity of things stopped being of as much interest. Those issues are discussed in: Complexity too great to follow what’s happening… ?? Then in 2012 I realized 1970 was also when computers started being used to manage business complexity, as the first “killer app” of computing really. The global effects would include giving business management a growing information advantage over others, telling them what can be cut and remain profitable, and making business financial analysis based purely on numbers rather than judgement, and somewhat incontestable, as discussed in: Computers taking over our jobs and our pay?
These preliminary studies still seem valid, but fairly incomplete. They didn’t really explain why the change occurred in 1970, or why so sharply. That is what the SEC rules change of 1964 now helps to provide. It appears that the implied “fitness function” of business was redefined to advantage the stock markets and executives, and hollow out the economy for everyone else, in effect violating all of Isaac Asimov’s laws of robotics, as the first big thing we thought of doing with automation.
The Rules That Wrecked the Economy
It takes a little time to explain the evidence, here showing the long record of US GDP growing by leaps and bounds for 120 years. Overlaid are Household income levels, scaled to equal GDP at 1970 so their proportional changes are displayed. Household incomes are seen perfectly tracking GDP from the 1940’s to about 1970, and then start to dramatically fall behind. It shows the economy completely stopped “lifting all boats” in 1970, completely disproving the endlessly promoted business lobby idea that how to cure the “malaise” was to give the rich more money. Households suffered from the having to manage the ever faster growing complexity of life, but without the growing resources. It might not have been intentional, but these trends do seem to literally display 40 years of US households being increasingly devalued, cheated out of the economic value they created, even as investors were cheated too, by businesses being driven to develop unsustainably, only becoming a great public issue now.
The next figure shows the behavior of the stock market at the time when the SEC rules bringing “efficiency” to fast trading and market manipulation by traders, a 14 year record of NYSE trading frequency beginning at 1960. You can clearly see how the strongly pattered trading followed right after the rules were implemented, as a dramatic change from the sleepy manner of trading before. You might also be curious about the 40 year record, from 1960 to 2000.
When you see a genuine behavior change like how the trading volume suggests a “sleepy” market from 1960 to 1965 followed by a market of manic movements thereafter, it means people have really changed what they’re doing. I’m not completely sure how well my hypotheses about that behavior change will hold up, what it was and what effect it had. I have a rather good record on a number of other things, though, so I think they’re at least rather close.
I would love to have help going more deeply into how the culture change involved took place. The SEC annual report mentions a number of meetings that might have been involved, and getting those notes might be very valuable. The documents I found most useful so far are a 30 pg excerpt from the SEC Annual Report of 1964 and a NY Times article reporting demand for “the bottom line” . The latter interestingly reports on the woes of bankers, as if not sure of how businesses defined their values, as an argument for reducing the value of businesses to a single number in a quarterly report. I think that way of redefining the value of businesses shows a clear “spin” favoring the fast trading culture about to emerge. It quite neglected the possible effect on the lasting values of businesses, that seems to have been the mainstay of Wall Street thinking before.
Work to be done includes
updating the data from original sources
more detailed study of the 1964 SEC rules and their adoption, amendments, and “side agreements”.
studying why the rules were a pivotal “breaking point” for a rapid large scale culture change in how American businesses are managed and how the new style trading cause business practice to change
No doubt there would be grand scale malfeasance discovered, and perhaps prosecutable criminality too. As what happened is really culture-wide, I think finding criminality would depend on when the original meaning of “fiduciary duty” was lost, that would be the basis of requiring financial managers act in the interest of the people they make decisions for. The main crime seems to be self-destructive, a culture change. The ideal policy would be to guide people to understanding their own errors and learn how to follow a new path. New York City, like all the “money centers”, is directly implicated in needing to find a new way to make money, for example. For 50 years money centers have depended on maximizing the extraction of wealth, not securing the future of wealth, and so have relied on promoting disruptive innovations with no heed to what was disrupted… No fury seems adequate to express the stupidity of that, What is does indeed come down to is finding that those money centers will shortly “be out of a job” unless they become as creative at helping to put the world back together as they were at ripping it apart.
Added work to do includes:
further studying the very special problems of societal manias…. as that is what we see here. What sort of “policy” can one have for societies taking the wrong path, having wandered SO far from creating a world to live in that can last.
If you think of money as physical energy, money being what we use to release our use of it, you can think of the global economy as a rocket ship. The problem of course is our culture having settled on operating civilization that way, as a rocket ship, programmed to only accelerate and never land. Our main societal “business plan” is to multiply our energy use, investing to accelerate our fuel consumption as fast as humanly possible, forever. Of course to do that some money and energy are reserved for keeping people somewhat happy, but if the policy is for maximizing growth rates every other purpose is secondary. So here’s the question, how do we change course when changing course is nowhere in the plan? Do we shove the drivers out of the vehicle? Do we hope to explain to them the use of the gas peddle, steering and breaks? There may be equivalents in the rocket ship already, but the driver seems utterly unaware of them conceptually. It’s a lot to explain, and a lot to learn,
collecting our understanding of real scope of the problem
The ancient legal principle of “fiduciary duty” is a deep principle of professional practice requiring professionals to act in the interests of those they serve, and another example of selective redefinition for for managing money. There probably is a clear history of successive misleading revision, with a legal paper trail to follow for how it came to be turned on its head to serve mainly the self-interests of trader paid for their extraction of short term profits, not for serving the interests of the people whose money they traded. I appears that legal opinion now holds it to actually prohibited for traders to consider anything than short term financial returns as the interests of investors, even though no one is served by that except traders and CEO’s who are paid in % of short term earnings. That is the complete opposite of the original intent, of course. So the redefinition of “fiduciary” seems to have come from cultural blinders like those that produced the SEC rules of 1964 too.
Another, even clearer example I’ve noticed, I also spent a lot of time thoroughly documenting. It’s how all manner of scientific principles are being willfully ignored in managing the world survival project called “sustainability”.
One certainly can’t fault anyone stumbling through this confusing time, making sincere efforts to learn about how our very complex world can come to work again. We’re in a period of unprecedented permanent change in who we are, not planned by anyone it seems. That said there are also large systematic errors one can find in the efforts people are making, related to persistent influence of money. One very consequential case is in efforts to reduce environmental impacts that businesses are responsible for use, using widely circulated very unscientific rules for counting them. The standard for environmental accounting instruct people to measure the global impacts of their use of the economy as what is recorded locally. How that “slipped” by so many world institutions and communities is what’s shocking.
People are just told never to count the impacts of using money (even though that’s the main thing causing all our global impacts). If you’re not allowed to count the impacts of money it limits your view to your boundary local observations. So sustainable cities don’t count the resources consumed from outside the city. The same applies to national measures of sustainability, like Sweden not counting the external energy consumption for either the majority of their income and consumption. that happens to be outside its national borders. I’ve published and written on this extensively, and tying it all together in my UN proposal for scientific method for steering world sustainable development, a World SDG. It starts out very simple, learning to do the math right at least, and leads to giving people a full understanding of what our money pays for.
I’ve also studied fairly deeply how all these confusions could arise. Is there something wrong with our minds if our effort to hold onto reality is fraught with difficulty? What would allow the meanings of important words to unexpectedly change, largely unnoticed? The line between the words that are and are not prone to radical change is between definitions we get from experience and ones we get from other people. Most words directly refer to natural patterns of life and our own experience of them. They really can’t lose their root meanings as new variations on their meanings accumulate over time. The problem is with words defined conceptually, social agreements and things like the economy that we can’t really observe, and so only understand abstractly. Being unable to distinguish between those terms of conceptual thinking and words for natural experience, we tend to trust what ever usage of any kind is current in our immediate cultures. So in the money world, or in any social or professional or religious community too, people may be making up new abstract meanings for convenience that may drift widely from one group to the next, and over time, and not be noticed.
That inability to distinguish between natural and conceptual meanings seems to spill over as part of all our problems. We rely on natural and scientific language for grounding our idea in the patterns of nature, but we’re at risk if we can’t check the wandering meanings of our other languages. At present though, the scientific meanings of natural language are not being taught, and our scientific thinking is limited to the classroom, lab or office. We might try to find how to use scientific principles to check what we’re told to believe, and may wonder if conflicting interests have distorted.
That’s more or less what I’ve done, collected some things I see how to go back to nature any time to double check, to help show were work is needed to get the story straight! ;-)
Short version Voted a Top Comment on the Forbes article
“The Stock Market And Bernie Sanders Agree — Break Up The Banks” , a more full story follows.
The reality of the matter is as embarrassing as it could be. If you trace it all back to origins… it’s our very own greed causing the whole mess, our demanding that Wall Street produce ever faster growing **unearned income** for our investments.
That’s what is now backfiring on us as the serious scientists all always said it would. The earth is not an infinite honey pot… is the big problem our not so big hearts and minds have in grasping the consequences of our own choices. We simply failed to notice the consequences, or listen to those saying “beware of what you ask for”.
The truth is WE became “The Sorcerer’s Apprentice”* and now we are dealing with having turned the planet into our Fantasia. The truth is that if we “Break Up the Banks” the financial system we designed to grow unearned income will just keep multiplying the disruptions the scientists always pointed to it causing! Are there options?? Well find someone honest who studies it perhaps…
Sorcerer’s Apprentice http://goo.gl/Zu69yD
(If this YouTube copy is inaccessible sometimes you may need to find another copy or just recall the heroic tragedy of it all, from the last time you saw it.)
Day after the NY Primary 2016:
In New York State yesterday there seemed to be a lot of answers, but we can all see more questions too. Neither Trump nor Sanders are offering practical ways of doing it, but clearly raised a huge chorus of “throw the bums out”, without actually identifying “who the bums are” as part of the questions left hanging. To the surprise of many Trump’s win was so persuasive it seems to almost legitimize his candidacy. To the surprise of many as well, Sanders overall persuasively lost to Hillary Clinton, and only had persuasive wins in conservative upstate areas. In ultra-liberal New York City, his claim to ultra-liberal leadership found really very few neighborhoods persuaded. New York is the kind of place that needs no persuasion at all on the legitimacy of his issues, but found his manner and inability to say what he’d actually do, and relying on a constant stream what had to be called rather misogynist digs.. caused him to lose legitimacy.
So nearly all agree the bums need to be thrown out, but “who the bums are” remains unanswered, and largely undiscussed too, The Trump campaign colorfully claims the intention to disregard all the rules to “get the raccoons out of the basement”, and with no strategy but public outrage, sweep away the broken Republican party and Washington DC political establishments. Sanders imagines that some executive order breaking up the banks and popular demand for relieving very real and widespread despair will remove all the barriers to doing that.
I’ve studies these problems in great detail for many years, and have in fact been expecting to have to somehow claim to have predicted this kind of grand societal collision with itself from the first time I caught a glimpse of the real problem. My observations are only a little more detailed and focused on locating who has a choice, who actually is “at fault” in that sense, as the natural disaster at the end of capitalism has been has been long predicted for what I see as all the wrong reasons for centuries.
That real problem is that “Wall Street” is the name given to the practices of the financial traders who trade everyone’s investment funds, and so… “Wall Street” actually already works for us, and doing precisely what we ask it to do. There’s just something profoundly confused about what we ask it to do. We ask it to manage the use of our idle savings to produce profits to add to our savings, and so multiply in scale without end except for letting the trader take a share of the spoils, Of course the bargain is that multiplying your profit taking from your world with no exception eventually destroys your world, invisible only if you don’t look.
I don’t know quite why Goethe did not sharply identify that ultimately seductive bargain with the Devil when writing Faust. That play is apparently his morality tale about what happens when making that bargain. He was, though, enough more clear in depicting it in his balladic poem Der Zauberlehrling, that Walt Disney used as the basis of his ever popular animated film Fantasia, and very pointed fable “The Sorcerer’s Apprentice”.
Our hero, Mickey Mouse, steals a look at the sorcerer’s book of secrets and immaturely calls upon its magic to command his broom to carry the heavy water of his chores, so he can sleep all day. As he awakes he finds the magical broom can’t be stopped, as Micky doesn’t know what spell to cast for that, and is flooding the whole house and castle, and so MUST be stopped. Then like people feel today, Micky picks up his ax to do in the boom for good…, but finds in chopping up the one it only multiplies magical brooms and the rising flood turns into a great torrent.
The failure of Mickey’s strategy would, of course, be repeated if Sanders’ grand gesture calling for “breaking up the banks” were to actually be applied. The various banks that have now grown overwhelmingly big, magically carrying our water so we can accomplish ever more without work, will all just continue expand, as long as we ask them to use our savings as before. You would just get more banks accumulating more disparity in the wealth of the world. Whether the phrase “break up the banks” refers to dividing up the banks into smaller ones, or separating their savings and investing functions, it wouldn’t alter a bit the basic service they are being asked to provide us as investors. They’d still be using our idle money to multiply, in some magical way, so we can be showered with fruits without labor, and left with the puzzle of why that can’t keep working.
Investors may or may not feel “wet”, but if you look around the world, everyone else does look rather soaked! It’s a quandary that we’ll have to resolve, why the secrets of creating wealth were apparently not shared by our process of enjoying wealth. So what’s clear, at least, is we now have a new job. It’s not one that Wall Street asked for, perhaps, but that they can’t refuse as they work for us. It’s to break with the Faustian bargain we made with ourselves, and perhaps stumbling some also stumble without regrets so much as anticipation, get about the work of showing the world another side of what we can do with our genius.
Here we don’t find ourselves without a plan of action, is what’s different from the many calls to protest, though the plan may need repeated adjustment and improvement in various ways. It’s ironically not like Bernie’s plan to “not take Wall Street’s money” either. It’s indeed to “take Wall Street’s money” we belatedly realize, because Wall Street is in fact just managing our money for us, and we just need to as for the right thing. That’s the real way to break our bargain with the Devil, that we do seem to be at a great historical point of rejecting. We can take our knowledge of wealth with us too, but only if we learn the other tricks needed to leave the earth whole and to share.
The following is written for circulation in the “data science” research communities, on some advances in scientific methods of system recognition I’d like to share. It starts with mention of the very nice 9 year old work published by Google on “Detecting Influenza Epidemics using search engine query data” taken from a letter to that paper’s authors. Take the reference to be to your own work, though, as it involves system recognition either in life or exposed by streams of incoming data.
I expect a lot of new work has followed your seminal paper on detecting epidemics as natural systems.
But are there people starting to focus on more general “system recognition”,
studying “shapes of data” that expose “design patterns” for the systems producing it?
Any individual “epidemic” is a bit like a fire running it’s course, and sometimes innovating the way it spreads. That change in focus directs attention to how epidemics operate as emergent growth systems, with sometimes shifting designs that may be important and discoverable, if you ask the right questions. You sometimes hear doctors talking about them that way. In most fields there may be no one thinking like doctors, even though in a changing world it really would apply to any kind of naturally changing system.
Turning the focus to the systems helps one discover transformations taking place, exposed in data of all sorts. One technique allows data curves to be made differentiable, without distortion. That lets you display evidence of underlying systems perhaps entering periods of convergence, divergence or oscillation, for example, prompting questions about what evidence would confirm it or hint at how and why.
Focusing on “the system” uses “data” as a “proxy” for the systems producing it, like using a differentiable “data equation” to closely examine a system’s natural behavior. In the past we would have substituted a statistic or an equation instead. By prompting better questions that way it makes data more meaningful, whether you find answers right away or not. I think over the years I’ve made quite a lot of progress, with new methods and recognized data signatures for recurrent patterns, and would like to find how to share it with IT, and collaborate on some research.
Where it came from is very briefly summarized with a few links below. Another quick overview is in 16 recent Tweets that got a lot of attention this past weekend, collected as an overview of concepts for reading living systems with bigdata.
I hope to find research groups I can contribute to. If you’re interested you might look at my consulting resume too. If you have questions and want to talk by phone or Skype please just email a suggested time.