Limits to Growth

Limits to Growth @F-L-O-W

 
 

Frederick Jackson Turner studied the effect of the frontier on the US and the effect of the closing of the frontier.  He may have been the first to look at limits to growth, which may have clues about how to remain happy while not increasing in size.

Closed Frontier
Turner saw the land frontier was ending, since the U.S. Census of 1890 had officially stated that the American frontier had broken up.  He sounded an alarming note, speculating as to what this meant for the continued dynamism of American society as the source of America’s innovation, and democratic ideals were disappearing.

http://en.wikipedia.org/wiki/Frontier_Thesis

http://en.wikipedia.org/wiki/Frederick_Jackson_Turner

 

 

 

Figure 1. Base scenario from 1972 "Limits to Growth", printed using today’s graphics by Charles Hall and John Day in "Revisiting Limits to Growth After Peak Oil" http://www.esf.edu/efb/hall/2009-05Hall0327.pdf

 

 

 

 

 

Cassandra and the limits to growth

Listen!  For no more the presage of my soul,
Bride-like, shall peer from its secluding veil;
But as the morning wind blows clear the east,
More bright shall blow the wind of prophecy.

(Words of Cassandra in Aeschilus’ Agamennon)

Sometimes I wonder how it was that Cassandra, the Trojan prophetess, had so much trouble in convincing her fellow Trojan citizens that it was not such a good idea to demolish the city walls to let in that big, wooden horse.  Maybe she spoke in riddles and using obscure language, as fitting for a prophetess.  But in our case, facing global warming and resource depletion, I believe that it is fundamental today to arrange our knowledge in ways that can be understood by citizens and decision makers.  Otherwise, all the work we have done will be lost and we’ll remain just Cassandras.

In 1992, William Nordhaus wrote an article (1) where he strongly criticized "The Limits to Growth" (LTG) study.  Referring to the 1972 version of LTG, he said that,

"….it seems apparent that the dynamic behavior of the enormously complicated Limits I model was not fully understood (or even understandable) by anyone, either authors or critics."

Which we may take as correct at least in one respect; that is, if Nordhaus meant to include himself among these "critics".  Indeed, with this sentence, Nordhaus may have been admitting that his 1973 paper (2), where he had even more strongly criticized world modeling, was completely wrong. Simply, in 1973 he hadn’t understood how the model worked, and not even in 1992. (I discuss in detail these papers by Nordhaus in my book "LTG Revisited" (3).)

It is also true that the large majority of those who criticized the first LTG study after its publication, in 1972, did so without really understanding world modeling.  But is it true that the "world3" model at the basis of the study was not "understandable," as Nordhaus maintains?  Possibly, Nordhaus had based his evaluation on this graph:

This is a scan of the graphical representation of the world3 model taken from my personal copy of the 1972 edition of LTG.  The boxes are labeled in Italian but, either in English or in Italian, the logic of the model is very difficult to grasp. It appears just as a random collection of boxes and arrows, not unlike the plan of the subway of a major city.  What you have here, indeed, is an example of a "spaghetti model", a typical bane of system dynamics (SD) models (as discussed, for instance, by Jacques Lefevre).  It is possible that it is this complex and apparently haphazard scheme that confused LTG critics and supporters alike.  It may have been one the reasons of the flood of criticism that accused the LTG study of being based on arbitrary assumptions, if not a hoax purposefully designed to trick the public.  People just couldn’t believe that the mass of spaghetti shown in the figure could generate to a cycle of growth and decline and that this cycle was to be the destiny of our economy.
But the world3 model was not arbitrary.  As one of the first models of this kind in history, it is not surprising that its graphic representation left something to be desired.  That didn’t affect the performance of the model, which withstood very well the test of time.  The real world parameters, so far, have behaved close to the results of the "base case" scenario of the 1972 LTG study, as Turner shows.  Critics had to work hard to find weak points in the study that went beyond simple statements of disbelief, as I discussed in a post of mine.  In the end, they had to settle on very minor points that had no relevance to the significance of the study.

The LTG model was not impossible to understand, either.  If you look at the text of the original 1972 LTG book, you’ll see that the figure shown above came only after several pages that described in detail how the model worked.  The authors made a thorough job in showing diagrams of the various subsets of the model.  That made the model understandable even by economists.

Unfortunately, that was not enough.  No matter how well the model was explained, understanding LTG required an effort that most people were not willing to expend.  It is difficult to fight against the human tendency of disbelieving bad news – the Cassandra effect, in short.

But we can learn something from the LTG experience.  A fundamental point is related to the public perception of models.  For a scientist, the need for models is obvious; but it is not so for a politician or for the public.  In this sense, world modeling and modern Climate Science have the same problem. Both fields are seen as based on complex models that are beyond the capability of understanding of the non-specialist.  So, what is exactly the role of models in the public debate on the issues of climate change and resource depletion?

Sometimes, people seem to believe in models just because they are complex.  Otherwise they see complexity as proof that the model is wrong or irrelevant.  The problem of complex models is that they leave people free to chose one or the other attitude, depending on their feelings or their political ideas.  So, I think we badly need to frame our models in "mind sized bites" of knowledge – as suggested by Seymour Papert – that people can grasp.

As an example, here is how Magne Myrveit has represented the five main stocks of "The Limits to Growth" model (from a paper titled "The World Model Controversy").


This figure can be criticized as an oversimplification, but it is a huge step forward in the sense that it gives an immediate visual idea of what the main elements of the models are.  Yet, it has a problem. "Mind sized" doesn’t just mean reducing the number of elements in the model.  It means, in my opinion, providing also a clue on what makes the model tick.  In other words, a representation such as this one, simple as it is, still suffers from the spaghetti syndrome.  It is static; it doesn’t tell you anything on where the system is going.  And, yet, the results of the calculations clearly show that the system is going somewhere; it is undergoing a cycle of growth and decline.  That is not clear at all from this figure.

So, I think that if we want to make useful mind sized models we must clarify that there is a tendency; a force, the result of something that in technical terms is called a "potential".  Potentials generate forces, and forces move things along.  I think this is the point that Jacques Lefevre was doing when he used the metaphor of chemical reactions for describing system dynamics models.  But there is an even simpler metaphor: "bathub dynamics" as discussed by John Sterman and Linda Sweeney.

Now, this is a real mind sized model, in the sense that it is clear that it is gravity (better said, the gravitational potential) that moves water in a certain direction.  This representation of the model is not static, it shows what happens.  It was with this example in my mind that I proposed the "three tiered fountain" image as a representation of a simple world model:

Neither a bathtub nor a fountain have the characteristic that we call "feedback", which is crucial in world models as it generates non linear growth and decline.  Nevertheless, these are images that clarify the fact that the system is driven by a potential.  Water must go somewhere and that is because of the gravitational potential.  Then, it is clear that if we start from a limited reservoir of water, then at some moment it must run out.  In a world model, it is not gravity that moves things, but thermodynamic potentials, in turn related to the energy stocked in the natural resources that an economy exploits.  And it should be also clear that if natural resources exist in limited amounts, they must run out at some moment. So, we can build a simple, mind sized model as:
Once these points are understood, we can use even this very simple "three stock" models to gain a surprising wealth of insight on how economic systems behave.  I used this model in previous posts and I showed how it can explain the "Seneca Effect", that is why the decline of economic and social systems is so often much faster than growth. So, I think this is a line to pursue if we want our models to be understood and, more than all, acted upon.  That is true for both resource depletion and climate change, which are two sides of the same coin.  But would mind sized models solve the problem of the disconnection of scientists and decision makers?  Well, that won’t be easy, of course. Sometimes, when playing with these models, I see myself as if I really were the ancient Cassandra, the Trojan prophetess, drawing stock and flow diagrams on the sand in front of perplexed Trojan citizens. Not easy.  Yet, I think we have to try.

References
1. Lethal Models 2: The Limits to Growth Revisited, by William Nordhaus Brookings Papers on Economic Activity, Vol 1992, No. 2 (1992), pp 1-59. URL: http://www.jstor.org/stable/2534581
2. World Dynamics: Measurement Without Data,William D. Nordhaus, The Economic Journal, vol. 83, No. 332 (Dec., 1973), pp. 1156-118, http://www.jstor.org/stable/2230846
3. "The Limits to Growth Revisited" Ugo Bardi, Springer 2011

 

Another excellent additional ongoing attempt to refine the question of modeling.  I agree that it’s important to ‘mind size’ this aspect of the problem – primarily (at this point) so that people cannot so easily dismiss it out of hand.  Kudos for continuing this effort, Ugo!

The deeper issue remains, however: whence derives the Cassandra effect?  And to what extent will making things easier to understand undercut that effect, if at all?

I like how you put it: "the human tendency of disbelieving bad news" – and complicated, hard-to-understand models give people a ‘good’ (or at least a plausible) pretext to disbelieve.  But even if we take away that excuse by providing easier-to-understand models, we still will face the same underlying effect, because it is a psychological one.

Do you think it likely that it will manifest in some other way?

It seems to me that William Rees’ recent essay at the PCI is directly on point:

http://www.postcarbon.org/Reader/PCReader-Rees-Culture.pdf

wherein he notes:

"Humans may pride themselves as being the best evidence for intelligent life on Earth, but an alien observer would record that the (un)sustainability conundrum has the global community floundering in a swamp of cognitive dissonance and collective denial."

He goes on to say:

‘Psychologist Robert Povine argues from the available evidence that the
starting assumption in behavioral psychology should be “that consciousness doesn’t play a role in human behaviour.  This is the conservative position that makes the fewest assumptions.” ‘

and:

‘Cognitive scientists have determined that cultural norms, beliefs, and values are effectively imprinted on the human brain. In the normal course of a person’s development and maturation, repeated social, cultural, and sensory experiences actually help to shape the individual’s synaptic circuitry in a neural “image” of those experiences.  Once entrenched, these neural structures alter the individual’s perception of subsequent experiences and information.  People seek out experiences that reinforce their preset neural circuitry and select information from their environment that matches these structures. Conversely, “when faced with information that does not agree with their internal structures, they deny, discredit, reinterpret or forget that information." ‘

My personal experience in life has tended to confirm these observations, which are also in alignment with the characterization of confirmation bias made by Sir Francis Bacon centuries ago.

It seems we are really faced here with something fundamental – or perhaps a better word would be ‘primal’ – to human nature, or more precisely to the nature of human psychology.  We really, for the most part, tend not to be consciously acting beings, at least when it comes to matters which involve basic biological impulses (though I do not mean to imply any sort of determinism).  And, I think we fail to even recognize that fact.  Which makes two successive obstacles to overcome when attempting to ‘reach’ the public, politicians, etc.

I have to admit being in the camp which thinks, in fact, that this will not be done.  I view much of the work being done on peak oil not as an effort to change the trajectory we have already established and which seems all but certain to persist, but rather as efforts that can aid in establishing a new trajectory – the one that begins from the bottom of the cliff and goes forward.

In that sense, I view it as crucial that we learn the proper lessons from the coming ‘reset’ to humanity’s external conditions (so that we can let go of the cultural myths which have not, and will not serve us well).  And I think the work being done here has the potential to be very useful in that regard.

– Oz

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