Posts to the UN NGO Thematic Consultation on Educationon how to measure and improve education for the Post2015 UN development goals. My series of three comments focus on the tools a student needs to create their own educations… NOT on measuring the productive value of their educations for business. We did that already, and overdid it. It would do both students and society a great deal more good to look at the basic competencies offered, to see if students are getting the tools they need for exploring the world, like having competence in math, reading, and understanding ‘relationships’.
Productivity is often the assumed purpose of education, but has produced an unsustainable spoiling and depletion of the earth’s resources, now straining all its human and natural ecological systems. So it’s our students who need the tools for guiding their own educations, to take us out of that dilemma created by the poor learning of their parents.
Schools and teachers should mainly be judged by their own peer and served communities, only measuring achievement in core competencies, and create a new core competency in “relationships“. Understanding relationships is a new essential competency for living in a world thrown into disarray by rapidly changing relationships of all kinds, caused by our prior vast misunderstanding the relationships between ourselves and the earth.
1. Based on my understanding of quality of learning, the indicators used to measure learning outcomes should be:
… kept simple. We should only use unambiguous measures giving confidence in what is being measured, like “numeracy”, “literacy”, “understanding relationships”, “understanding design”, i.e. rudimentary life skills. Continue reading It’s the student that creates the education→
There’s unquestionably something wrong with a world society expecting to push the talents of its people and the resources of the earth, our cultural resilience and her ecological resilience, to absorb regularly multiplying scales of new challenge and change. It naturally gets out of scale with reality.
It gets out if scale by being a continuation of the path we’ve been on, but now pushing everyone and everything to create and adapt to ever greater change even as it becomes unmanageable. So it now increasingly pushes people and cultures to acts of desperation. It’s part of our whole culture, though, and is driven relentlessly by compound investing, the financial principle followed for seeking prosperity everywhere in the world, now escalating the challenges and risks.
For a fairly simple reason it becomes a trap, because the people leading society don’t discover the illogic of it, because they don’t feel the illogic of it. Increasing productivity by leaps and bounds had always been our ideal of “good”. It is perhaps the most unquestioned belief of modern man.
To have THAT become a serious threat is deeply unexpected. So only the people who can feel the counter-intuitive changes in the realities, (feel intuitively that the “logic” of the system has become “illogical”), are able to then maintain a motivation to search for the evidence to discover the real root of our emerging conflict with our own ideals.
the root of our emerging conflict … with our own ideals.
There are a great variety of reasons to organize people
Sometimes it’s to discover something or to accomplish somethingSometimes it’s to connect people who share their views Sometimes for people who share a common world from different views… (but have remarkably different talents and views)
If you know of good examples or methods not mentioned here,
please post comments
It’s Collaborative Work between groups of stakeholders that often “don’t speak the same language”. It takes art, patience and a sound method to get them to immerse themselves in the environment of the problem or opportunity that they need each other to respond to as partners.
It follows nature’s model of systems design to begin the growth of any system with a business model for multiplying one’s control of their environment. That’s what happens when planting a seed, that grows by multiplying it’s ‘secret’ internal design, consuming its host environment ever faster, at first. It doesn’t pay in the end, though, for either businesses or any other kind of economic system, to keep following that model, as if endlessly getting nature ever more pregnant could be the soul (or ‘sole’) purpose of self-organization.
When you get environments pregnant you also need to budget for child care, is the point. That’s the time a growth system stops using its profits for its own self-inflation, and switches to using them instead for discovering its original purposes and nurturing them. Study any kind of growth system that fulfills its own purposes. That’s what is done to discover and fulfill their ultimate purposes.
Systems build on growing profits and give them away to keep thriving.
I’ve written extensively, from numerous perspectives, on both the systems science and financial implications. What’s implied is our need to follow nature’s example, and instead of investing in self-inflation to consuming our host ever faster…, giving away our profits to find our true purposes in having begun to grow.
Getting the whole system to reorient its purposes, from growth to funding what matters to us… would indeed involve some “rethinking”. It might be easier than it seems at first, though, as it seems to be for lots of other kinds of systems in nature that do it casually and simply, without a thought actually. They often succeed by just giving all their products away to see what others make use of. That’s what the cells in organisms and the organisms in ecologies largely do. They don’t give away what is needed for them to operate, though, so there’s some sort of line between what they must give away for the whole to thrive, and must keep for themselves to thrive.
Knowing that it’s probably a physical necessity for our survival makes it easy to discard the options that obviously wouldn’t work, and send you “back to the drawing board” looking for the secret to the ones that would…
A way to respond to experience we’re unable to articulate.
There are lots of cases when what attracts us to a theory is its sort of “spooky” truth. “Urban myths” often contain them, and science can often be the source of them, as well as cultural sayings and religion too, of course. The value is that they give you, a way to respond to experience we’re unable to articulate.
For applying them to real world problems, however, it’s rather important to “do the work” of finding real examples you can study and articulate. What’s NOT needed is “spooky action” for real problems… ;-) So here are a couple notes on how to find real examples to help you apply curiously attractive metaphors and “spooky theories” to decision making about the real problems, such as our groping with finding our place on earth. jlh
“spooky theory” then becomes a metaphor for something real you understand well enough to use as a guide.
Piercing the Veil: Markovich. Painting In Oil On Wood, 2006
1. for Greenleap 9/23/12 – “Spooky biomimicry” as “what to do”
Richard – Ultimately “what to do” is a communal process somehow, as we’re in communal trouble. Lots of people are seeking new directions of learning, but I can tell are often still using the blinders of the past to guide them… and not wanting to hear about it at all. All you can offer them a more authentic way to search for new learning, hoping they’ll see it as fun.
Natural systems are the complexly organized and behaving “creatures of nature” that by definition operate without our thinking about them, or knowing anything about them, or doing anything, and are largely invisible to us. That’s by definition “spooky nature”. It’s also the source of all our mysterious stories about unanswered questions, and all our mysterious experiences. What we can do with “spooky ideas” that situations suggest to us is then find an example that isn’t spooky, that we can then use as a real guide to how complex systems work and how to interact with them. – ed jlh
Preface: My last post on the dramatic declining share of wages in GDP since 1970 mostly discussed that remarkable change in behavior of the whole system in relation to how the numbing complexity of business would make computers better “wage earners”, shifting income from wage earners to investors. Complexity too great to follow what’s happening… ??The graph here is a simpler version, showing the same dramatic shift in the disproportionate changes in wages and GDP since 1970.
This post is on how the same shift from wages to profits reduces demand for the products, “made for people” but for which neither business decision making tools nor investors have an appetite. The economy visibly changed behavior. It was coincident with computer decision making emerging as a leading tool of business, and the historic numbing complexity everyone has experienced (reflected in changing language use).
The third important way is a later realization. Computers are overwhelmingly better at making deterministic predictions… but can’t be programmed to consider human values, so they’re omitted from the rules for what to optimize… Computers are even more likely to keep applying old values that no longer apply than humans too. When resource prices go up, for example, the old standard investment models say “speed up”, while nature is signaling “slow down”.
It may seem there’s nothing more dispassionate and “neutral” than automated decision making, but that easily becomes purely ruthless too. So it seems to create a “perfect storm” of misdirection to use computers to multiply their programs in a time of fundamental change in our world. If the model says “choice A = X profit” there’s no way to tell if a different story would be told had humans studied how ‘A’ applied in the current circumstance, so the model built without human values also omits any way to argue with it.
You can see one global effect of this naturally “inhuman” decision making of computer models in their universal penny shaving for profit. That seems directly behind the ever stricter control of decisions, since computers were introduce, by the computer’s measure of value, “the bottom line”. Before that, business people needed to think of the business as a whole, and not a single number, ruling almost every choice. So it produces ever growing pressure to “make money” for the sake of money, whether making a bit less to invest in other values might be a better fiduciary choice.
Author’s Note: 2/16 – My work on this problem dates back to the 70’s really, and my developing methods for “whole system accounting”. In simple terms “whole system” or “inclusive” accounting means you can’t keep “robbing Peter to pay Paul” without noticing. It comes from the customary methods of natural science, not used in economics. Instead of using arbitrary accounting categories, one uses naturally defined partitions of the whole system to define your categories. One is ultimately forced to get it right by there being lots of natural reasons you can’t keep “robbing Peter” (calling what’s unaccounted for ‘externalities’) without dire consequences.
Whole system accounting models force you to look at what you are leaving out of the model, by requiring the use of accounting categories that add up to the whole, partitions of the system. That’s what natural science does to validate the data collection and produce “closed accounting” of the system in question. Oddly so do business financial accounts, but just not economic accounts. Using partitions of the whole for your accounting categories forces you to estimate how much is going uncounted. The first discussions of complete economic economic models of that kind are my 1983 General Allocation Theory and 1985 Unconditional Positive feedback in the economic system in the SGSR proceedings for that year.
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1970 marked the sudden end of steadily growing US wages, as a sharply accelerating trend of growing economic inequity and loss or resilience began.
“Information overload” was a rapidly growing topic of conversation and computers emerged as the premiere tool for driving business profit.
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Was that how humans began to be replaced by technology,
as things got too complex?
comment 1.
I think the question is quite relevant, and in line with Nobel laureate Wassily Leontief’s 1983 warning that humans will go the way of the horse in the business of providing goods and services. What most people don’t know is that started dramatically in ~1970,
Indexing UN GDP (1880 to 2010) and US median wage levels (from 1948) at 1970 shows how they grew at the same rates before 1970, and then have been growing apart. It shows the divergence between levels of wage incomes and wealth, a societal shift from earned incomes and wages, toward unearned income and finance.
It’s remarkably clear in the data, quite indelible as a “coincidence” between introducing computers for business use in ~1970 and the “the great divergence” of breaking American society apart with lagging earnings from employment and multiplying earnings from wealth. Why did it occur. Following from my 2010 Complexity too great to follow what’s happening… ?one could explain it as cause by the numbing increase in the complexity of everything we do, affecting people but not the computers or the calculation of profits. Looked at from a social view of ever faster increasing economic inequity… it looks more like people using computers to make money, robbing Peter to pay Paul and not counting it.
For those interested, here’s the same data without indexing the wage curves to GDP:
History US GDP with Percentiles of Median Wages approximately scaled as partitions of the whole
On now to recognize the somewhat universal responses to system and relationship overload, as strains resulting in loss of resilience and a risk of sudden disruption; replying to Helene on Systems Thinking World on her “UN Call for Revolutionary Thinking” thread.
The most general pattern is resilient relationships becoming rigid, like the surface of a balloon does *before* it can be easily pricked by a pin, or as people become rigid before losing patience. I think that comes directly from resilient systems generally being organized as networks of things that share their resources, and when all the parts run out of spare capacities to share at once the system can’t be flexible, and is then vulnerable to sudden failure.
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@Helene – Thanks for the reminder. Here are some principles for detecting and responding to the inflection point. Mathematically it’s “passing it’s point of diminishing returns”, when increasing benefit of expansion starts to decrease. Long successful habits of expanding a system become a liability, and strain their internal parts and environments.
It means about the same thing for a whole economy as for a little girl outgrowing her only party dress. Ignoring strain on one’s limits brings an unexpected end to the parties. The problem for systems operated by abstract rules of thinking, is that responding to change isn’t in the rules. So there’s a need to revive common metaphors for responding to the unknown, like for “overdoing it” or “crossing the line”, as strategic signs of externalities needing close examination.
Overload is a surprisingly common feeling, with visible effects
The most common signs of “overdoing it”, and needing new strategy, are formerly stable and flexible sub-systems
becoming “unresponsive”,
developing “the shakes” or “become rigid”
This is a brief but relevant comment, from my Systems Thinking World discussions, points out a way the efforts by Goggle and others, to mine “meaning” from of the massive quantities of semantic data now available, is missing a golden opportunity. There are a variety of ways to use the natural structures of languages as a key.
@Ferenc – I don’t recall the subject of data mining semantic meaning coming up, but I sure agree there seems no computer search strategy yet in use for that. I have some original technical ideas of how to do it, but they all begin with learning to recognize how natural languages “integrate common knowledge” for you, by how language communities naturally develop within their own social commons, (or “silo”).
So the first step to learning how to read the natural organization of semantic structures generally is to learn how recognize and observe the development of natural languages and the semantic webs they create. This STW community is one, for example, as is any other community with a sustained internal conversation.
Armed with that, perhaps a computer whiz could learn to crawl the web to develop a lexicon of the code phrases of a great variety of distinctive language communities. That could provide a way to let you search on any topic of your interest, for any language group’s interest in it.
I’ve tried to suggest that to Google a few times, to let people do web searches from a “scientific” viewpoint, or “entertainment” or “youth” or “religious”, “liberal”, “conservative”, “European”, “Asian” or other distinctive community of interest.
Wouldn’t having that option, to look in on other language cultures and learn from what they’re learning from, would be very entertaining and enlightening itself, wouldn’t it?
– Similar spatial mapping methods, like from satellite imagery or network mapping, locate cells of self-organizing systems from their development signatures and boundaries.
A crowd sourcing proposal. Suggested to WNYC as a new form of news coverage
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From a natural history view, how the US news media reports on what’s happening of public importance is, well, entertainment news, that misses most of what’s actually happening and how it’s connected. Even Public Radio mostly giving us six shows a day of talk about all the same things that “everyone” is talking about. It tracks how the discussion is changing, but misses almost entirely how the world itself keeps complexly and dramatically changing by itself.
To open a LinkedIn community discussion in “Systems Thinking World”, on the “whole systems approach” and scientific method I use, for discovering and understanding natural systems, I offered the following lead-in
We might study anything identifiable, and growth curves in time-series data seem associated with some kind of growing system, developing from scratch. The usual difficulty discovering what’s going on inside them may be strong evidence that they’re organized and changing internally, not visible to or determined by their environments. If such individual systems exist, would they also have locations, external bounds of some kind, a beginning in time and an end?
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7/24/12
54 comments
#1• Jessie Henshaw • There are a few problems I’m trying to raise with this. One is the scientific difficulty of studying things you can point to, but can’t actually define. Science does better with “data” and numerical relationships, studying that as a ‘map’ for a more complex ‘territory’. Organizational change within individual natural systems isn’t readily mapped by “data”, though.
Is that one of the reasons there appear to be so many kinds of individual events and natural systems that display periods of essentially explosive creative organizational development, from storms to personal relationships, to social movements, disease outbreaks and swarms of new technologies, but science seems not to have yet identified that as a field of study?
12 days ago
#2 • Fabian Szulanski • What about agent based modeling? Would that be a point of departure for helping understand? Then some emergence, bifurcation and disorder could eventually appear.
12 days ago
#3 • Jessie Henshaw • @Fabian Well, that would be studying models for mathematical rules, not natural systems, wouldn’t it? To study natural physical systems, as if they were ABM’s, is more like what I’m suggesting.
Say you assume the natural world is like the big amazing computer the physicists postulate it actually is. Well then, we’re looking right at nature’s ABM without realizing it, and just need to discover it’s way of inventing things. We don’t have access to a “decompiler” of nature’s source code, though, do we? What we see are systems that evolve new organization by changing everywhere at once, somehow. It makes it appear that nature is doing fresh programming, on many levels at once, with nearly every process and event she creates. Continue reading Natural Whole Systems Thinking – philosophy & method on STW→
New systems science, how to care for natural uncontrolled systems in context
