.
The Limits to Growth (LTG) is a
1972 report on the exponential
economic and
population growth with a finite supply of resources, studied by
computer simulation. The study used the
World3 computer model to simulate the consequence of interactions between the earth and human systems. The model was based on the work of
Jay Forrester of
MIT, as described in his book
World Dynamics.
The World3 model is based on five variables: "
population, food production, industrialization, pollution, and consumption of nonrenewable natural resources". At the time of the study, all these variables were increasing and were assumed to continue to grow
exponentially, while the
ability of technology to increase resources grew only linearly. The authors intended to explore the
possibility of a sustainable feedback pattern that would be achieved by altering growth trends among the five variables under three scenarios. They noted that their projections for the values of the variables in each scenario were predictions "only in the most limited sense of the word", and were only indications of the system's behavioral tendencies. Two of the
scenarios saw "overshoot and collapse" of the global system by the mid- to latter-part of the 21st century, while a third scenario resulted in a "stabilized world".
Commissioned by the
Club of Rome, the findings of the study were first presented at international gatherings in Moscow and Rio de Janeiro in the summer of 1971. The report's authors are
Donella H. Meadows,
Dennis L. Meadows,
Jørgen Randers, and William W. Behrens III, representing a team of 17 researchers.
The
report concludes that,
without substantial changes in resource consumption, "the most probable result will be a rather sudden and uncontrollable decline in both population and industrial capacity". Although its methods and
premises were heavily challenged on its publication, subsequent work to validate its forecasts continue to confirm that
insufficient changes have been made since 1972 to significantly alter their nature.
Since its publication, some 30 million copies of the book in 30 languages have been purchased. It continues to generate debate and has been the subject of several subsequent publications.
Beyond the Limits and
The Limits to Growth: The 30-Year Update were published in 1992 and 2004 respectively, and in 2012, a 40-year forecast from Jørgen Randers, one of the book's original authors, was published as
2052: A Global Forecast for the Next Forty Years.
Alternate predictions: After the
Club of Rome's controversial 1972 report
The Limits to Growth produced widespread alarm about the possibility that population growth and resource depletion might result in a 21st-century global "collapse", the
Hudson Institute responded with an analysis of its own,
The Next 200 Years, which concluded, instead, that scientific and practical innovations were likely to produce significantly better worldwide living standards. In 1970,
The Emerging Japanese Superstate, elaborating Kahn's predictions on the rise of Japan, was published.
Herman Kahn (February 15, 1922 – July 7, 1983) was a founder of the
Hudson Institute and one of the preeminent
futurists of the latter part of the twentieth century. He originally came to prominence as a
military strategist and
systems theorist while employed at the
RAND Corporation. He became known for analyzing the likely consequences of
nuclear war and recommending ways to improve survivability, making him one of the historical inspirations for the title character of
Stanley Kubrick's classic
black comedy film satire
Dr. Strangelove. His theories contributed heavily to the development of the
nuclear strategy of the
United States.
Maintaining this optimism about the future in his 1982 book
The Coming Boom, Kahn argued that pro-growth tax and fiscal policies, an emerging
information technology revolution, and breakthrough developments in the energy industry would make possible a period of unprecedented prosperity in the Western world by the early 21st century. Kahn was among the first to foresee unconventional extraction techniques like
hydraulic fracturing.
A little extra bit for people who are curious : systems dynamics models are a bit different than the modern machine learning systems we generally picture today. they do not have the ability to be trained and learn, instead they are hand built, usually using multiple theories that are then chained together into bigger 'systems'. The 'historical data' bit is for hand validation, you run known datasets through it and see how well your theory does, then you have to hand make adjustments. It is still pretty heavily used today since it is much more explainable than ML, but requires a lot more up front work and is not as useful for things like recommendation systems (the core of search, advertising, and product/media browsing) so it gets a lot less attention.
