DOI
http://www.americanscientist.org/article/computation-and-the-human-predicament

Summary
Forty years ago this spring, a little book titled The Limits to Growth landed with a big thump. The authors reported on an exercise in computer modeling, which they grandly described as “Phase One of the Project on the Predicament of Mankind.” According to the model, the human predicament was bleak, with less than a century to go before civilization would crumple under the burdens of overpopulation, famine, resource depletion and pollution. As a young journalist I was fascinated by this apocalyptic vision. I was also intrigued by the remarkable idea that computation might be a useful tool for understanding the human predicament.

Facebook

Twitter

LinkedIn

Google Plus

Email

Print
Current Issue
THIS ARTICLE FROM ISSUE
MAY-JUNE 2012
VOLUME 100, NUMBER 3
PAGE 186
DOI: 10.1511/2012.96.186


VIEW ISSUE
Forty years ago this spring, a little book titled The Limits to Growth landed with a big thump. The authors reported on an exercise in computer modeling, which they grandly described as “Phase One of the Project on the Predicament of Mankind.” According to the model, the human predicament was bleak, with less than a century to go before civilization would crumple under the burdens of overpopulation, famine, resource depletion and pollution. As a young journalist I was fascinated by this apocalyptic vision. I was also intrigued by the remarkable idea that computation might be a useful tool for understanding the human predicament.



Ad Right
In 1972 I had no way to explore the workings of the Limits model for myself. Twenty years later, though, with a desktop computer and ready-to-run modeling software, I was able to twiddle the model’s various knobs and observe the effects on the outcome. I wrote about that experience in 1993, in the first column published in these pages under the rubric “Computing Science.”

Recently I have turned to the Limits model yet again, this time delving into details of its implementation—the 150 equations that govern the evolution of the simulated world. Closer examination of the model’s structure has not increased my confidence in its predictive power. On the other hand, the hope that computation might have something to tell us about the fate of the planet remains very much alive. We don’t have an abundance of better tools for seeing into the future. An interesting challenge is to clarify what distinguishes the computational methodology of The Limits to Growth from other models that policymakers take more seriously, such as the climate models that now underlie much of the discussion of global warming.

Relevance for Complex Systems Knowledge
The article reviews the systems dynamics model "World 3" that was used in the seminal  and controversial book "Limits to growth". The review is based on a scrutiny of the parameters brought into the model, but it also reflects on the critiscism against the model and on the actual opportunities to construct and implement the model in the early 1970´s.

Rerunning the model with modern computer facilities show both strengths and weaknesses. Putting critique in context of what the model actually promises to do the article provides a factual and balanced view.


The conclusion is that the model is not convincing, containing some fundamental flaws. seen in the context that it was constructed by a small team, compared to the way climate modelling is done today by large communities of researchers, it still can be seen as a good endeavour.

Point of Strength
The article is a must read in a course that provides foundational concepts for systems modelling of socio-ecological issues, particularly if it aims at providing a historical background.