Recent Updates

daviding 9:11 am on January 19, 2018  

Moving to stream.syscoi.com

The content from syscoi.com/stream has been moved to stream.syscoi.com.  This experiment will gradually be quiesced.

Benjamin P. Taylor has moved over to model.report (based on the lobste.rs platform) at the end of 2015, after the community on LinkedIn was threatened with a shutdown.  The model.report site accumulated a community.  In early January 2018, the technical administrator for model.report told Benjamin that he would be unable to continue to support the community, and would help them to move elsewhere.

Benjamin reached out to me, and asked if I could help archive the site.  Thus, there is now a model.report archive preserved as a static site at https://syscoi.com/model.report/model.report/recent.html

In addition, the community has accepted my invitation move over to syscoi.com.  In doing so, I suggested to Benjamin that the partnership should move over onto a fully-supported WordPress.com infrastructure, so all of the feature of the O2 project (e.g. @reply) would become available.  Migrating the content from syscoi.com/stream to stream.syscoi.com has been relatively easy, although registration processes and menus are changing a bit.

So, everyone who registered on syscoi.com/stream should soon be receiving an invitation to become an author on stream.syscoi.com.  If anyone happens across this message, and wants to join the community over at stream.syscoi.com , it will be a two-step process.  First become a subscriber, and then request the permission to become an author.  We are taking this precaution in an effort to reduce potential spam, as SysCoI has always been designed as a platform where e-mail subscription is a good option.

Thanks to everyone who contributed to this experiment!  We hope to see you over at stream.syscoi.com.

daviding 1:40 pm on January 4, 2018
Tags: definition, systems sciences, what is   

Challenges in defining systems science

As members of the Systems Sciences Working Group are organizing for an IFSR Conversation in April 2018, the group focusing on “What is systems science?” will be revisiting a question that has emerged before.

On a message on the Systems Sciences Discussion List, James N. Martin abridged and reposted an e-mail from Gerald Midgely.

Here is the abridged writing by James Martin, dated Dec. 29, 2017:

— begin paste —

Here is a bit of useful wisdom with respect to the question of “what is systems science?”  Gerald has given me permission to post this on our Sys Sci discussion list. He was responding to the proposal from Gary Smith to conduct a workshop at the IFSR Conversation in April to address this question

Here are his key points. His full message is enclosed at the end of this email.

  • First, don’t ever be under the illusion that you can break systems science down into its constituent components, agree on them all, and therefore gain agreement on the whole. That’s approaching systems science through reductionist analysis, and it won’t work.
  • Second, … do not expect that achieving consensus in a small group will generalise to a wider community without (a) a strong message of utility and (b) co-ordinated and strategic action to connect to what matters to other people.
  • Third, and linked to the above, be aware that ideas gain currency, not because they are truthful and beautiful in themselves, but because of their utility (the value of the inferences that can be made from them).
  • Fourth, and this is probably the hardest thing of all for Systems Scientists to hear – it means that the Systems Science that is of relevance to Systems Engineering might be different from the Systems Science of relevance to systems biology, politics and family therapy.
    • A foundational idea in Systems Science is that we can define some generic theory that is relevant across the board.
    • I still do think that this is the case, in the sense that there are some concepts (like how parts combine in systems to create emergent properties from the perspectives of observer-participants) that can be defined independently from the receiving discipline.
    • However, these relatively abstract conceptualizations, because they are not communicated in the context that the receiving discipline understands, may appear to the engineer to involve too much work for too little value.
  • Fifth, … the interactions with the problems of Systems Engineering will change the theory.
    • It may be that Systems Science explains some things, but not others, so there is a need for integration with other theory;
    • or it could even be that the particularities of Systems Engineering contexts lead people to conclude that an evolution of systems theory is needed in a new direction.
  • Systems Engineers can learn a lot from both the science of whole systems (Systems Science) AND thinking through the use of systems concepts that have been abstracted from their original theoretical context (Systems Thinking).

Best Regards, James

— end paste —

Here is the original e-mail from Gerald Midgely addressed to Gary Smith, dated Nov. 20, 2017.

— begin paste —
Hi Gary, Jennifer et al,

Thanks for looping me into this conversation. I know this is a long email, but I really hope it is a helpful one that can prevent the group going down some blind alleys. Below are some suggestions, purely based on my own understanding and experience, having seen people aiming for and failing to achieve a consensual definition of systems science for as long as I have been in the systems community (my first ISSS conference was 1989).

First, don’t ever be under the illusion that you can break systems science down into its constituent components, agree on them all, and therefore gain agreement on the whole. That’s approaching systems science through reductionist analysis, and it won’t work. Jennifer Wilby will remember a workshop at an ISSS conference back in the early 90s where people sought to define common terms. They started with ‘hierarchy’, because they thought it would be the easiest, and 3 hours later they abandoned the attempt, as there were so many different perspectives. The exercise didn’t even get past the first concept because the part (in this case hierarchy) was connected in so many ways to different systems philosophies, and the meaning was subtly different in each case.

Second, and this is really important in the context of a group pursuit exercise such as the one you are planning, do not expect that achieving consensus in a small group will generalise to a wider community without (a) a strong message of utility and (b) co-ordinated and strategic action to connect to what matters to other people. The systems community (along with every other scientific community) is full of groups suffering from “the tragedy of enlightenment” – saying, “we have done so much work to get this far, so why won’t anyone listen to us?”  There is a neat little idea called Relevance Theory from the discipline of linguistics that explains why. Relevance to others is a function of the value of the inferences that those others can make from the new idea (i.e., its utility) minus the amount of work it takes to integrate that idea into their conceptual framework. Therefore, ideas may fail to disseminate because they generate a “so what?” reaction (which can be because they really don’t offer much added value to others, even though they do to you, or because they do not connect sufficiently with the worldviews of those you want to influence). They may also fail because they are too complex, and if it means internalising 50 new concepts, and understanding the contributions of 100 researchers over 70 years, people will see the mountain of work as enormous and will not yet have experienced the value of it, so will be dismissive. I used to get really angry when the Systems wheel got reinvented every generation or so (see, for instance, how complexity theory and systems biology failed to acknowledge their roots in GST), but now I realize that insistence on acknowledging the history of ideas actually prevents access to them. That’s hard for us to hear, but remember we are the affictionados who already see the value, so for us the work is worth it – others haven’t got to that point.

Third, and linked to the above, be aware that ideas gain currency, not because they are truthful and beautiful in themselves, but because of their utility (the value of the inferences that can be made from them). Therefore, for your project, the connection with Systems Engineering is actually more important than Systems Science itself! Again, for systems scientists this might be hard to hear – our tendency is first to work out what Systems Science is, and then to look at how Systems Engineers can gain inferences from it. However, the huge risk of doing this is the construction of a fine-tuned and intricately self-referencing and self-reinforcing set of concepts (Systems Science) that obstructs take-up in three ways: (1) it offers inferences that are relevant to systems theorists in domains other than engineering, and neglects the inferences that will be of value for Systems Engineers; (2) it does not dovetail with the language of Systems Engineers, so the value is not immediately obvious, and (3) it takes too much work to learn the subtlety. If it does any of these things, it risks failure.

Fourth, and this is probably the hardest thing of all for Systems Scientists to hear – it means that the Systems Science that is of relevance to Systems Engineering might be different from the Systems Science of relevance to systems biology, politics and family therapy. A foundational idea in Systems Science is that we can define some generic theory that is relevant across the board. I still do think that this is the case, in the sense that there are some concepts (like how parts combine in systems to create emergent properties from the perspectives of observer-participants) that can be defined independently from the receiving discipline. However, these relatively abstract conceptualizations, because they are not communicated in the context that the receiving discipline understands, may appear to the engineer to involve too much work for too little value. Again, the connection with the discipline matters more than Systems Science itself (how many times have you heard that the connections between the parts are as important, or even more so, than the parts themselves?), and the way Systems Science gets presented (the emphasis on some concepts rather than others, with particular examples) will be different from the Systems Science that gets presented to another audience, even if there are some common reference concepts.

Fifth, and this will also be hard to hear – the interactions with the problems of Systems Engineering will change the theory. It may be that Systems Science explains some things, but not others, so there is a need for integration with other theory; or it could even be that the particularities of Systems Engineering contexts lead people to conclude that an evolution of systems theory is needed in a new direction. If Systems Scientists then resist this, because it is a breach of the ideal of generality, then there will be a split in the research community, and the consensus you started out with will be broken. Here I am reminded of Kurt Richardson’s insightful complexity theory of language: as conceptual formations meet new contexts, bifurcations of meaning happen. This is why there is so much variety in systems theory in the first place. Disciplines narrow the contexts of meaning that their theory is designed to address, and therefore they can maintain more coherence and consensus than Systems Science, which self-consciously seeks to address ALL contexts. I actually did my PhD on this problem (1988 to 1992), and argued that we need a theory to EXPLAIN the pluralism (thus giving a different kind of coherence than a single systems theory), not a once-and-for-all theory to eliminate it. In this situation, we should expect diversity, not rebel against it and try to reduce it. The task of the Systems Scientist is therefore not to produce the best possible, fully worked-out systems theory, which will (of course) be relevant to systems scientists and nobody else! Rather, our task is to define the leanest possible theory, or set of concepts, which maximises value by being easily translatable into multiple, diverse contexts (such as Systems Engineering), while causing the people in those contexts very little work to internalise the concepts. This can be done with the Systems Engineering link (and other links) in mind, so the desire for purity is always countered by the need for communication with others.

Just one other thing I would like to add, which is not an outcome of the above reasoning, but also important. I think some clarity is needed about the difference and connections between Systems Science and Systems Thinking in this context. It seems to me that Systems Engineers can learn a lot from both the science of whole systems (Systems Science) AND thinking through the use of systems concepts that have been abstracted from their original theoretical context (Systems Thinking). If you are in any doubt about the difference, think about how ‘boundary’ is used in Systems Science as a reference to the edge of a real-world system (seen from the perspective of an observer, of course). However, when the boundary concept is moved into the domain of Systems Thinking, we can suddenly talk about boundaries defining what OUGHT to happen, etc. The concept has been abstracted from its original meaning and is deployed more widely. I am pointing this out, not to state the obvious, but to make it clear that defining Systems Science for use in Systems Engineering is only part of what the systems community can offer the engineering world. There are three risks here: (1) failing to notice Systems Thinking, and the Systems Engineering community getting confused between two competing claims of benefit (it is too much work for Engineers to sort this out, and both Systems Science and Systems Thinking will fail to deliver); (2) imperialistically presenting Systems Science as if it is both Systems Science and Systems Thinking, which will spark a paradigm war in our own research community; and (3) saying that Systems Science is right and Systems Thinking wrong, or a pale immitation, which risks both a paradigm war in our own community AND failure to deliver because we are expecting engineers to discriminate between competing claims! Please can we build clarity on the science/thinking distinction into our offering, without saying that either is less worthy than the other?

Thanks for listening, if I have not caused you too much work and you have read this far!

Best wishes, Gerald

— end paste —

These responses may not satisfy those looking for “simple answers”

#definition, #systems-sciences, #what-is

daviding 12:33 pm on September 24, 2017
Tags: death, equilibrium   

Stable equilibrium is death

Be suspicious of science(s) based on a presumption of equilibrium.  This dates back to 1910, with Henry Adams on the second law of thermodynamics.

If the silent, half-conscious, intuitive faith of society could be fixed, it might possibly be found always tending towards a belief in future equilibrium of some sort, that should end in becoming stable; an idea which belongs to mechanics, and was probably the first idea that nature taught to a stone or to an apple; to a lemur or an ape; before teaching it to Newton. [pp. 185-186]

Unfortunately for society, the physicists again abruptly interfere, like Sancho Panza’s doctor, by earnest protests that, if one physical law exists more absolute than another, it is the law that stable equilibrium is death.  [editorial emphasis added]

A society in stable equilibrium is — by definition, — one that has history, and wants not historians.  [p. 186]

Thomson and Clausius startled the world by announcing this principle in 1852; but the ants and bees had announced it some millions of years before, as a law of organisms, and it may have been established early, in more convincing form, by some of the caterpillars.  [pp. 186-187]

According to the recent doctrine of Will or Intuition, this conclusion was the first logical and ultimate result reached in the evolution of organic life; but the professor of history who shall accept the hymenoptera and lepidoptera as teachers in the place of Kelvin and Clausius, will probably find himself in the same dilemma as before.  [p. 187]

If he aims at carrying his audience with him, he will have to adopt the current view of a society rising to an infinitely high potential of energy, and there remaining in equilibrium, the only view which will ensure him the sympathy of men, as well as, — probably, — of caterpillars; but if wants to conciliate science, he will have to deride the idea of a stable equilibrium of high potential, and insist that no stable social equilibrium can be reached except by degrading social energies to a level where they can fall no further and do no more useful work.  [pp. 188-189]

Perhaps this formula, too, may please many students, whose potential of vital energy, — or, in simpler words, whose love of work, — is less archaic than that of the ants and bees; but as a matter of practical teaching, — as a mere choice between technical formulas, — the two methods result in the same dilemma for the old-fashioned evolutionist who clings to his ideals of indefinite progress.

Between the two equilibriums, each mechanical and each insisting that history is at an end, lost forever in the ocean of statistics, the classical University teacher of history, with his intuitions of freewill and art, can exist only as a sporadic survival to illustrate for his colleagues the workings of their second law of thermodynamics [p. 188].

1910_ALetterToAmericanTeachersOfHistory

There’s a 1992 appreciation of Henry Adams by Keith Burich.

Ever since Henry Adams penned the phrase “stable equilibrium is death” in his Letter to American Teachers of History (1910), historians have quite naturally assumed that he was referring to the awful predictions of the Second Law of Thermodynamics, which requires the irreversible dissipation of human and natural energies point of a universal, deadening stasis. […] What has been lost on Adams’s biographers, however, is the fact that his interest in and understanding of modern science was far in advance of many of his contemporaries’, including many scientists, and that his dabblings in geology and evolution in the 1860s reflected an early uneasiness with the prevvailing assumptions that the forces governing man and nature are rational, predictable, and purposeful. [p. 631]

[…]

Lyell’s three-volume Principles of Geology, published in 1830, became the foundation for modern geology. It was more than a textbook on geology, however; it was a defense of a theory of the earth’s organic and inorganic development, a theory that came to be known as uniformitarianism. Lyell hoped to establish geology as a legitimate science by insisting that the theories had to be based on empirical observation and verification rather than metaphysical speculation and that the organic and inorganic history of the earth could be explained by forces currently at work in nature. The competing theory, catastrophism, is most often associated with biblical literalism. Since according to the Word the earth was created in 4004 B.C., its geological contours had to have been the result of divinely directed interventions, catastrophes like floods, because the earth’s relative youth did not allow for more gradua processes. [pp. 632-633]

[….]

As Stephen Jay Gould has recently shown, Lyell and his predecessor, the eighteenth-century English geologist James Hutton, were committed to a cyclical conception of time, or what Gould terms “time’s stately cycle.” Under the Newtonian dispensation Hutton and Lyell were trying to apply to geology, like causes have like effects; changes are predictable. If the catastrophists were to be believed, however, time would not form an endless series of identical cycles, but a linear progression pointing in some unknowable direction. According to Gould, Hutton and Lyell were unwilling to embrace the possibility that the changes that effected organic and inorganic history might be rapid and discontinuous. Randomness could not order the universe, or so they thought, and thus time’s stately cycle must lay at its heart.

Adams let his readers know from the outset that Lyell had hitched his horse to uniformitarianism and was unwilling to entertain alternative explanations for geological phenoemena, a shortcoming Adams would later exploit in the review He warned his audience not to expect more than a textbook on uniformitarian principles from Lyell. [p. 634]

[…]
By the 1860s Adams was already chafing at attempts to reduce man and nature to mechanical, deterministic formulas and to impose “one Form, Law, Order or Sequence” on history. It was motion and change, not promises of perfection, that attracted him. Nevertheless, he had no alternative but to accept the prevailing orthodoxies of the day. [p. 644]

[….]

Adams’s suspicions about the inadequacies of uniformitarianism have recently and indirectly been given credence by Gould and his colleague Niles Eldredge, who have questioned the assumption that evolution proceeds inexorably from lower and simpler organisms to higher and more complex species. Gould and Eldredge have suggested instead that species remain remarkably stable over time and that new species appear abruptly and rapidly, not gradually and progressively out of existing species. Adaptation and natural selection account for minor changes but only after the equilibria in which species normally persist are “puncutated” by the sudden appearance of new species. Furthermore, Gould has shown that evolution has been by catastrophes, like the one that caused the demise of the dinosaurs and more serious ones that extinguished up to percent of all species nearly six hundred million. Gould has concluded that such catastrophes have been more instrumental in shaping the course of evolution than competition and natural selection. If so, then no necessary direction can be imputed to evolution, and the current state of nature may not be inevitable and predictable.  [p. 645]

Good science (and history) should learn from nature.

References

Adams, Henry. 1910. A Letter to American Teachers of History. Washington [Press of J.H. Furst]. http://archive.org/details/alettertoamerica00adamuoft.

Burich, Keith R. 1992. “‘Stable Equilibrium Is Death’: Henry Adams, Sir Charles Lyell, and the Paradox of Progress.” The New England Quarterly 65 (4): 631–47. doi:10.2307/365825.

#death, #equilibrium

daviding 7:05 am on August 21, 2017
Tags: fourth turning, generational theory   

Cyclical history and generations

If systems change over time, the change may follow a linear or cyclical pattern.

For people who would prefer to listen to a description and critical evaluation on cyclical patterns, a recent lecture is “Thoughts on Cyclical History & Generations” | Prof. CJ | May 22, 2017 | The Dangerous History Podcast (episode 0140, 1h53m) is at http://profcj.org/ep140/ .  This covers:

  • Ancient conceptions of cyclical time
  • The concept of linear time
  • Some modern conceptions of cyclical time
  • The generational theory of William Strauss & Neil Howe, authors of (among other things) the famous book The Fourth Turning: An American Prophecy
  • What the Strauss-Howe theory says about recent American history as well as about its present & future
  • CJ’s thoughts on Strauss & Howe’s theory

For a human system, the cycle has been described as a saeculum with a periodicity of about 80 years, with four turnings (analogous to spring, summer, autumn, winter) of about 20 years each.  This research is explained online at The LifeCourse Method, published circa 2012.  The generational theory is more thoroughly explained by William Strauss and Neil Howe | The Fourth Turning | Broadway Books | 1997, (which has a preview on Google Books, as well as on Amazon).  There is a Wikipedia page on Strauss-Howe generational theory, as well as a continuing discussion at generational-theory.com .

This theory is based on Anglo-American history dating back to the 1400s, and admits that other societies could be on different cycles.  While William Strauss passed away in 2007, Neil Howe is still active with his research, and even posts at https://twitter.com/howegeneration.  A search on “Neil Howe, turnings” rapidly turns up more interviews and recently published articles.

#fourth-turning, #generational-theory

daviding 12:33 pm on July 19, 2017  

Capitalism and the principal-agent problem

Within a capitalist system, perhaps there’s more than one way to distribute moral hazard.  Here’s a concrete view of an investor-dominated approach at Apple, as compared to a managerial-dominated approach at Google.

Which principal-agent problem is more vexing? Stock-market returns are one, albeit imperfect, way of answering this question and since the initial developments, Google has far outperformed Apple. But that pattern is flipped if the time frame is restricted to the past year. So it won’t be known for many years to come if Apple or Google has a sharper financial strategy.

More importantly, though, how do these strategies impact the lives of everyday people? A capitalist system aims for the efficient allocation of capital, and indeed, workers have a better shot at seeing median wages increase when money is being put to its most productive use. So to an extent, how they fare under each system has to do with who is deciding where and how profits get invested. When managers reallocate profits, that reallocation benefits from the capabilities and knowledge that companies have built over decades, but suffers from the possibly poor incentives of managers. When investors are the ones reallocating profits, however, the scope of the reallocation can be broader, theoretically leading to more innovation; at the same time, those investors don’t have preexisting organizational capabilities and they may suffer from their own short-term time horizons.

Even if one considers the disparities in the shares of wealth accruing to labor and capital problematic—and there certainly are other strategies for addressing those disparities—making sure that managers and investors are dividing their responsibilities on capital allocation efficiently is critical for making the economic pie as big as it can be. And in that regard, while the problems of Google’s model are significant, they are also well appreciated. The excesses of Apple’s model and the widespread deployment of share buybacks are just as dangerous—and not nearly as well understood.

“Capitalism the Apple Way vs. Capitalism the Google Way” | Mihir A. Desai | July 10, 2017 | The Atlantic at https://www.theatlantic.com/business/archive/2017/07/apple-google-capitalism/532995/

The Atlantic: Capitalism the Apple Way vs. Capitalism the Google Way

JPOvaska 7:51 am on July 3, 2017  

Question for systems community: How to apply systems thinking?

Hi all systems people!

I am a recent graduate from Aalto University, Finland, where I studied in the interdisciplinary Creative Sustainability master’s degree program. Systems thinking was one of the bedrocks of the program, and we were fortunate to have David Ing teach us about systems sciences in one of our courses. David has been giving me advice after the course, and after a recent conversation about how to apply systems thinking, he requested that I post my question to SysCoI. So here goes.

My question is: How would you advice a recent graduate entering the workforce to apply systems thinking? Where would you start and what practices would you implement? I would also love to hear any stories of how you have applied systems thinking and practices to real life problem settings.

Thank you already in advance!

JP

 

daviding 3:46 pm on June 17, 2017  

Learning-by-trying

Working with social computing technologies can involve a lot of learning-by-trying.

While there is some similarities with “innovation configurations” research on implementation knowledge, this definition of learning-by-trying focuses on the integrating.

“Each configuration is built up from a range of components to meet the very specific requirements of the particular use organization. Configurations therefore demand substantial user input and effort if they are to be at all successful, and such inputs can provide the raw material for significant innovation” (Fleck 1994, 637–38).

Configuring social computing technologies don’t follow the characteristics of wicked problems. The issues are typically complicated rather than complex, and can be worked out with time.

Fleck, James. 1994. “Learning by Trying: The Implementation of Configurational Technology.” Research Policy 23 (6): 637–652. doi:10.1016/0048-7333(94)90014-0.