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??
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.
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.
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.
Re: 18 – 21 Oct 2016 Addis Ababa, Ethiopia (research ref’s at the bottom)
Fourth meeting of the IAEG-SDGs
SD indicators need one more, the World SDG
so Innovators can design their goals
in relation to the whole
My comment is as an expert on both system design and natural science indicators, on how innovative organization develops in both natural and intentional complex systems. There is a great depth of professional design practice that has yet to be consulted regarding the plan for the SDG’s
The general model of innovative transformations is that the emerging culture change, starting from some “seed pattern”, and then going through the classic phases of their own life-cycle of internal growth and changing roles in their environment (fig 1). There are of course many kinds of invasive systems and life-cycles. The type we are most often concerned with innovative transformations of human design, whether our own educations, or our society’s struggle to become “sustainable”, succeeds or not.
The earliest visible pattern is the emergence of an “inspiration” or “design”, looking for an opportunity to take hold, to have a starting organization that gets going by using environmental energy for building up the design. That energy flow for formation then tapers off as the transformation progresses, toward refining the “new capability”, or “new culture” or “new business” etc.
The natural goal is generally to stabilize the design as it begins its real work at a peak of vitality, beginning a long productive life. So in general, it’s to first grow and then make a home, to have a life. This model developed from study of natural change patterns , applying constraints of physics principles for energy use, that for designs to develop or change they need to develop new energy uses too.
Fig 1. The stages of organization to build systems and their energy uses
I’ve been attending the UN SDG meetings for four years, first for the Institute for Planetary Synthesis, and then with CIVICUS, learning a tremendous amount, but also noticing the very distinct lack of systems thinking in the design of the SDG’s. The main reasons seem to be that systems thinking is not taught in liberal arts educations, and that the design of the SDG’s was mainly shaped by demands for change, by issue focused groups from governments and civil society, not experienced with how organization relies on designs to join differentiated parts. So ideas of how to organizing the differentiated parts when undiscussed and were mostly left out.
So the process produced 17 idealistic “goals” and 36 main “topics” discussed mostly separately, arising from a profound concern with the whole global pattern of culture change and economic development. Personally I had a wonderful time, but was also sad I never got to talk about my main expertise, i.e. on how the parts of whole systems connect. From a natural systems view the SDG’s may be spoken of as separate, but are all indicators of “holistic cultural growth”. They’re not really indicators of “economic growth”, as it’s whole culture growth that brings value to an economy not the reverse.
With the process lacking systems thinking resulted in missing systems indicators: for how differentiated parts connect, for how cultures develop unity and cohesion. The diagram below is mainly for study, a “sense making tool”, a “map of questions” to help guide innovative changes.
The challenge is our usual mental confusion, with our minds working with disconnected bits of information and but actually working in holistic organizations and trying to engage with holistic systems of our world. So our “maps” and our “worlds” show a “mismatch of variety”. So we need to constantly study and learn from new experience. To succeed with an SD partnership, the organizers first need to find a “start-up match” between its “own abilities” and “an environmental opportunity”. Usually it takes “a study of the context”, identifying “forces to make whole” with a “unifying response” ( a reference to “pattern language”) . In terms of the 8 kinds of indicators for planning change, it’s matching type IV indicators of whole system potential, one set within the organization and the other in the environment. The actual initiative might focus on one or the other…
The 4 quadrant map has “condition indicators” for “states” (how things are) and “guides” (what can change). It has “context indicators”, “local” and “global”. The four quadrants are repeated for the Organization and the Environment as a 3rd dimension for the array. This arrangement borrows a bit from David Snowden’s Cynefine “place” centered holistic complex system business design practice. It fits with the long lists of indicators of functionally different kind needed for the SDG’s
There are also other advanced holistic system design traditions to choose from. In all of them design proceeds in “stages” of team “learning”, “work” then “review”. With each cycle all the indicators being worked with are reviewed. All the indicators the organization uses to guide it are consulted in the learning phase of each cycle. The architectural, product design and performance design professions have ancient traditions of how they do their work. Newer traditions of system design where this kind of learning is studied include “action learning”, “pattern language”, “object oriented design”, and “permaculture”. None of these traditions of advanced design practice seem to have been consulted for the SDG’s for some reason.
Fig 2 Three dimensions of planning for innovative change, Organization & Environ, States & Guides, Local & Global
I do hope the above is helpful
for where SDG implementations can go for advice.
My real reason for writing, …and offering this way of understanding transformational change,… is the oddly disastrous pattern of excluded indicators in the official statistics for the SDG’s. The measures of ESG impacts that businesses are told to report as measures of their responsibility, have many more exclusions than inclusions.
It is possibly unintentional but oddly very boldly “hidden in sight”, the clear exclusion of all responsibility for the disruptive impacts of business and investor money decisions. It comes from the modern continuation of the ancient practice of excluding all business responsibility for economic “externalities” of the choices for what to profit from. Some impacts of what to profit from no one in the past would have know about. Now we really do know most of them.
The very largest exclusion from business impact reporting, though, is one that anyone would always have known about. It’s all the human consumption that business revenue pays for to obtain human services, ALL of it, as if those impacts had no environmental cost. That one accounting exclusion is commonly five or ten times the impacts the rules say businesses should count. The indication is that we have not started doing any form of sustainable development yet, systematically making decisions as if 80-90% of the impacts don’t exist.
At the UN and in writing to people I’ve been finding most people understand all this fairly quickly, …but then avoid engaging in discussion, the worst of all possible responses for our world. The cover-up and avoidance is always the bigger crime.
I urge you to respond to the challenge.
There’s a simple way, too, include in SD reports one new indicator, “global share of GDP impacts” proportional to share of global GDP
It’s really important to start the discussion.
Thanks for all your dedication and work
Most sincerely,
Jessie Henshaw
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The next more detailed introduction, to the “mostly uncounted” SD impact indicator problem, with references.
fyi –
I’m writing as a scientist, and expert on the design of natural systems and natural science indicators. I had wanted to attend the Ethiopia EAG meeting on Indicators, due to the major neglected issues I need to raise. Not having a sponsor I thought to pass on some of it to others who may get there. It’s about reliable filling the unusually large gaps in the SD impact indicators used for decision making.
As a consulting systems scientist I’ve has been attending UN meetings for four years, observing the SDG process, and noticing the big gaps in systems thinking being built into the plan. One in particular is that our impact measurement methods are not holistic, but actually quite fragmentary. Just having better information on visible impacts won’t tell us about the growing system-wide impacts, so SD decisions will still be unable to avoid traditional pitfalls of economic planning. Going ahead with just fragmentary indicators could really then make the SDG effort backfire, perhaps badly, adding to the “externalities” of the economy not reducing them.
That we are not yet doing holistic impact assessment is fairly easily documented, as whole categories left out of the accounting. There’s an amazing list of things the economists (at the direction of the OECD it seems) have arbitrarily left out of the list of things to count. The peculiar result is that the exclusions add up to nominally 90% of the real total. The biggest category of exclusions is usually the largest category of business environmental impacts. It’s the impact of paying business people for their human services, and for professional services, financing and public services. As a result SD decisions to maximize profit are being made unaware of nominally 90% of the future impact costs of those decisions. It’s surely a long standing habit we can’t change all at once, but we desperately need a recognition of it.
The economists have historically counted the business impacts as only things the business specifically directs. That then treats the “consumption for production” of human services as having zero impact, the usual largest of costs and of lasting environmental impacts of any business. The same is the case for all other supply chain impacts that are packaged as “services”, all counted as having zero environmental impact.. Having so little information on the lasting direct costs of business profits has always been a problem, and when combined with not feeling responsible defining “business as usual”. Today SD decision makers are still trying to maximize returns with a similar lack of information, though, as if just feeling responsible would compensate for the misinformation. It doesn’t.
I think most important is not to pick fights but to raise discussions of our common responsibility to address our common interests, to begin to include ones we’d been blind to. The caution is that It’s common for people whose sight is suddenly restored to be in shock, so it’s caring for them not making demands that lets them see.
If you or others would like to follow this up, you might start from watching my video comment to the UN on July 11 (1), and read the short “Impacts Uncounted” circular (2). I found it very effective for explaining the details when talking with people at the UN. There’s also a quite surprising scientific solution that makes holistic accounting possible, first reported in a peer reviewed 2011 paper (3). How to use that principle that “shares of the economy are directly responsible for shares of its impacts”, because of globalization, actually, is shown in a general 2014 proposal to the UN called the “World SDG” (4). It’s not getting discussed much yet, apparently due to the shock. Another caution, of course, is that we need the old economy to build the new one, part of why transformations are complex.
The big mental shock seems to be realizing the lasting impacts of using money are not close to “zero” at it appears. They’re actually very likely close to “average”, for being so unusually widely distributed the way an efficient economy works, that to do most anything takes everyone’s service. That “reassessment” is an almost infinite change of scale in our responsibilities, after all. It directly connects what we do innocently with money with all the disruptive things the economy increasingly does as our growth model collides with the limits of the earth, ..hurting the distressed communities the most.
So what we need is for people to keep doing what they’re doing, and begin to assume they have a real responsibility for what’s going wrong with the economy and the world, in approximate direct proportion to their share of the economy.
I hope that connects with your thinking and gives you a start with mine. Please send me anything you think is relevant.
Good luck your good work! Thanks so much for your time.
To help people understand my work, here are a couple of examples of data science to discover dramatic recent culture changes in New York City. The work is based on a careful lifelong study of eventful natural change, of all sorts, done by following the stages of growth and decay evident in the natural life cycles of culture change events.
following the stages of growth and decay evident in the natural life-cycles of culture change
My method depends on finding data that shows clear evidence of growth or decay, as those identify natural processes of irreversible organizational development, in the natural successions of change. Below are samples from two advanced studies of unexpected dramatic societal change, and a drawing of the markers of change I use to suggest what evidence to look for to discover what’s changing.
The two advanced studies are the mysterious 1991 collapse of the great NYC crack culture (1), and second, the mysterious 1970 splitting apart of the US economy into rich and poor sectors on different tracks (2). Both were simply enormous cultural events that very largely went unnoticed, dramatic “break-outs” of culture change that had been brewing for a long time, and then swiftly changed how we live. The study of the collapse of the NYC crack culture and many other examples are in the archive of my research from the 80s and 90s called “The physics of happening”
It gets easier to discuss these cultural changes once you sense what is being opened up to view is really the stories of our own lives. These and patterns of change in things we are all talking about anyway, only with data showing the systematic progression of key measurements of them. The basic science for following markers of change, implied by the physics principle of energy conservation (3), implying that lasting change is a process of organizational development. So the markers suggest places to ask “what’s developing”.
basic science for following markers of organization change, implied by the physics principle of energy conservation
the markers suggesting places to ask “what’s developing”.
1.
The End of Crack and Breakout of Hip-Hop
… three years before the mayor who took credit for it took office. The real main player was the strain on the families of the NYC drug cultures involved. They had become particularly traumatized by it, and the rest of society desperately searching for some way to change too. Everything people wanted to have work started working all at once, when their kids stopped looking up to the drug lords! They turned to the emerging Hip-Hop mass culture as an exciting alternative to be part of, a riveting story when well told.
What tipped me off was the “decay curve” shape of the NYS murder rate data shown in the NY Times. The abrupt decay curve shape, rapid at first and decelerating over years, without wiggle, is a very clear indicator of the death of a natural culture, in this case seeming to be from the youth that had once fed it turning away..
… a sudden structural change in how the US economy worked that broke out in 1968-70. A huge transformation occurred in how Wall Street defined profit, shifting from Wall Street seeing its role as helping businesses create value, to seeing its role as taking profit from business for shareholders. [note:…the strong appearance is that it actually changed the “polarity” of wealth management, in effect violating all of Asimov’s laws of robotics at once, as the first major use of computers for business to robotically take profits from business for shareholders (and traders)]. That shareholders and everyone else didn’t know maximizing the extraction of wealth from businesses would end up driving businesses to impoverish society… is of course the catch.
The curves here mainly indicate that something enormously big happened. The US data for median household incomes is “indexed” to US GDP (scaled to equal) at 1970, the time when the whole system behavior change occurred. GDP represents the whole economy’s income, that as the data also shows, before 1970, growing at the same proportional rates as the median incomes. It was after 1970 they all then split apart, with the GDP doubling and doubling while the median household incomes fell farther and farther behind.
3. The “Life-cycle Markers” derived from the physics principle of “energy conservation”
…that implies it takes organizational development for energy use to begin or end. It helps make sense of the way regular proportional change (what growth and decay curves show) is so commonly present where lasting change occurs. Once you begin to ask “what happened” where lasting change takes place, you look for the evidence of organizational changes taking off. and changing directions.
UN meetings on the first year of SDG implementation are over now, were very intense, and in the end quite successful for finding a new way to discuss the neglected issue of natural limits. The scientific community that understands the connection between our natural limits and economic growth has been totally shut out of the UN discussion for years. I didn’t get to speak to the main body on that directly, but I finally found a way to talk about the problem, that the SDG’s don’t in any real way count the global impacts of our decisions:
The ISO’s world environmental accounting standards fail to honor its fiduciary duty to our interests and human right to honest data,
only counting local impacts, leaving all global impacts of financial decisions uncounted and unaccountable.
SD decision makers are the most hurt, kept from knowing most of what they are deciding.
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The 17 Goals
It had seemed I would have a chance to speak at the UN, officially representing the long neglected interests of the scientific community that understands the coupling of the economy and natural limits. Below is the email I sent a number of scientists and other experts who understanding is not being represented:
Friends,
I found a way for scientists who have long understood natural limits, to get official representation at the UN, in the UN’s community of CSO’s (Civil Society Organizations), as a member of its “Major Groups and Other Stakeholders” (MGoS). The present work is the review and guidance of the UN’s global Sustainable Development Goals project (SDG’s), and the High Level Political Forum’s (HLPF) oversight of it. https://sustainabledevelopment.un.org/hlpf
Please circulate widely. Non-expert members welcome too. There is no organization at this time, just me seeing an opportunity to have our long neglected interests given official recognition. I might start a Google Group with the names or something… Any statement would be in the interests of the group rather than as if representing a group position
The draft text for representing the group’s interest to the UN is is here.
Time was too short for it to get around, and response was slow, except for the two great ones I really appreciate getting, so I turned off the Google invitation form . It still seems to be something that community really should find a way to do though!
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]
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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.
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2016 forward:
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”.
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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.
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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.
US GDP growth & US Income Levels falling behind, Incomes are scaled to 1970 GDP to compare rates, following GDP growth to 1970, then lagging and splitting apart.
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.
A 14 year record of NYSE trading frequency showing a dramatic change right after the new 1964 SEC trading rules were adopted.
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.
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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! ;-)
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.
empirical evidence of systemization
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.
Working with BigData, especially learning how to read the designs and behavioral patterns of the earth’s natural systems, its living cultures of all kinds, and to sense our roles in them, opens up a tremendous new field of understanding. It of course also opens up very new kinds of perspectives to puzzle over, both offering to show us new paths and making it clear various reasons to question what we’ve been doing.
This series of Tweets came out in a group somehow, mostly in this sequence today, seeming to build a framework of interconnecting points, like tent stakes and poles maybe, a design for hosting ways to do it. ……Jessie
What we talk about becomes society’s reality, so we can read #BigData for what’s happening #following_all_cultures and #resources_on_earth.
And what may matter most in #BigData is going from reading abstract patterns to reading naturally occurring ones. http://synapse9.com/jlhCRes.pdf
Then add the magic of learning to read the patterns #BigData reveals, as exposing the designs of the natural systems producing it.
Reading #BigData for natural patterns shows you even the best data doesn’t show what systems are producing it.
No degree in #data_science will neglect pattern recognition for understanding the natural systems creating the data.http://www.synapse9.com/pub/2015_PURPLSOC-JLHfinalpub.pdf
If our world #economy is causing trouble for the #earth, why do we think it helps to speed it up? #Get_real_people!
Escher
Are @google, @IBM or other #BigData #research teams learning how to read design patterns of natural systems?? http://synapse9.com/jlhCRes.pdf
To start reading natural systems in #bigdata look for cultures made individually, clustering or growing from seeds.
from PURPLSOC 2016 http://www.synapse9.com/pub/2015_PURPLSOC-JLHfinalpub.pdf
Then follow recognizing nature’s cultures with learning from them, going back and forth between models
from PURPLSOC 2016 http://www.synapse9.com/pub/2015_PURPLSOC-JLHfinalpub.pdf
When reading #bigdata for behaviors of cultures also note contradictions in the news, like #jobs_going_to_Mexico and #refugees_escaping_too.
#BigData exposes surprising whole system views too, #professionals managing systems of growing inequity, disruptive change and impacts too.
#BigData reveals living cultures: business, economic, social, biological or ecological, etc. all either: homeless, home seeking or enjoying.
As you see their forms you realize two things:1) our world is very #alive and 2) most #bigdata is too “big”, making you look for other views
To read #bigdata as views of shifting cultures, alone or together, pushes a #whole_system_view for units of measure. https://synapse9.com/signals/2014/02/26/whats-scope-4-and-why-all-the-tiers/
A #whole_system_view, like #studying_the_camera not what’s in its view, is how to start seeing ourselves in the data!http://www.synapse9.com/jlhpub.htm#ns
Sixteen Tweets on reading our world in #BigData, it’s many moving parts, units of measure & big recognitions required.
ed note: One tweet, that became #11, was rephrased and put in a more logical location a few hours after the first posting.
ed note: The current discussion of the core dilemma of capitalism, as a limitless system for creating growing wealth, is in terms of the crises we now face caused by it, producing socially disruptive innovation and growing financial inequity. Those include 1) threats of rapidly growing social inequity, 2) unsustainable national and private debt, 3) disruptive scales of job loss from globalization and automation, 4) demands for unachievable ever faster and ever more complex learning and change , 5) the rapid depletion of earth’s resources, 6) disruption of the climate and earth’s ecologies, and of course 7) increasing international conflicts between conflicting economic interests, and of course, 8) growing risks of grand scale financial collapses due to failing promises, as a kind of general list. It’s quite a list. There’s been a very long debate but mostly scattered in pieces and hidden from view. That’s both because the primary culprit is our whole way of life, naturally hard to talk about, and what to do with “money” .
The design of our economic system that defines “capitalism” is very simple. It’s “the use of investment profits to build up investments”. That’s it. Why such a simple practice has a hold on us is that it promises both society and individuals ever faster growing profits without growing work. Of course that tends to end up badly, having been much too good to be true from the start. The equally simple design of all natural systems is that “any system needs to build up to get started, and then stop building up to continue”. The two definitions conflict. Keynes and Boulding foresaw that the two would come to blows, once the economic system had built up and needed to stop building up to continue. They saw capitalism could become like a natural system and can change only if investors spend their profits. The sense of it is that investors would “pay it forward” so their profits would take care of the future rather that keep “paying it back” so old money could take ever more from the future. It would let our economic system first build up, and then stop building up, to be able to continue, with no guarantees but as a possible path forward. It’s all too simple as a design problem, as how all enduring natural systems develop and needs the social principle to make sense. The dilemma is completely unsolvable as a financial problem within capitalism, though, challenging our whole way of life as a rather immediate concern. jlh 3/14/16
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The intensification of work for concentrating wealth and profits. – Click – to see QuarksDaily article on how this process drains our world.
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from a 21st century view……
Your question is, do we all use our profits to extract increasing pay back from others,
building up an ever growing drain on what makes our world profitable?
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Or do we pay our profits forward to assure our world remains healthy
to grow our own ideals, our families, our communities and our world,
treating profits as a gift to what matters?
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J.M. Keynes and Ken Boulding were early and mid 20th century “whole system thinkers”. They were true geniuses, struggling for words to convey how complex systems with all independent parts work as a whole somehow. It’s truly the profound puzzle of nature, how illogical it is that all the independent parts of systems would act as if they were all coordinated. They didn’t stop at just looking for simple rules of prediction having no idea where they came from or when they might change. They also looked for and found elementally simple organizing principles of design, for how the parts of market economies coordinated with each other as whole systems and what drove them, central principles they weren’t able to communicate and that have yet to be appreciated at all. From their views they did each say that:
the world economy would soon bankrupt itself by over-investment,
as a natural limit to unlimited financial growth,
due to the central driving financial practice of compound investment
Each was also a expansive thinker with their own ways of speaking about broad principles, so they are hard to read too. It’s only by learning to think about the economy as a whole system, with all its parts working together, and distributing its surpluses and shortages throughout all its connections, that you can piece together from their writings the common finger prints for the above simple principle as what they were clearly saying.
I had some extra help with it, though. I learned of Keynes’ work on the natural limits of finance from speaking with Ken, having gotten a chance to ask him in person, if he knew of any economists who had studied the limits of compound investment as a natural limit to growth. I had asked Ken about it in 1983, and was able to understand what he said on the subject, because I had been searching for a few years already for anyone else who had discovered the principle, that growth systems, if not interfered with, would naturally upset their own conditions for growth. It’s a completely invariant natural principle. Continue reading Did Keynes & Boulding both really say that?→
We talk about making connections…
. . . . . . . . . . . . . . . . . . but what is it that actually “connects”?
Making Connections in life mysteriously needs to start and finish, and then perhaps establish a long sustained or a short relationship. Often we don’t see quite what’s happening till it’s either all over, or has really begun to noticeably develop and notice the rapid rates of change.
Sometimes we have an ‘inkling’ that something is changing at the very beginning, before anything really observable is apparent, as if becoming aware of the ‘germination’ of the whole event with an initially very slow building of a “new pattern”. It may be that intuiting “something changed” is experienced a bit like “feeling a change in the force” . We may imagine foresight for things that don’t develop, of course, and learn to just be watchful and not jump to conclusions, but wait till a real pattern of proportional scales of accumulation are evident. That’s ‘the pattern’ of systemic transformation.
What is perhaps the best indicator is always the “building process”, that as the illustration indicates is very much the same accelerating then decelerating accumulation of working parts. It’s *not* a numerical process, but if you notice the scales of change changing scale it can help you locate what is really working.
The illustration is of course also about the connections between the natural system processes of building, and the learning processes of building, and the holistic design processes of building, that I hope to get to see emerging as a “connection”! The PURPLSOC meeting “Elements” and PLoP meeting “Mining Living Quality” papers on “Guiding patterns of Naturally Occurring Design“, are full of these stories, maybe too much to enjoy all at once till you get a feel for this unusual way of approaching the study of “how things work”.
You might try a novel way of reading, other than beginning to end. One I often use with new books on unfamiliar topics is just “picking a few sentences at random” to see if they go anywhere for me, or trying the discussion topics at the end of sections or the whole work. Today I’m writing this post to take a break from the long task of doing the final edit of the main papers, seeing a need to have ‘something’ new on RNS, having noticed some scratch notes for the illustration made a couple weeks ago I thought would be fun to work on.
jlh
New systems science, how to care for natural uncontrolled systems in context
