How the Living Earth Simulator Will Work

By: Robert Lamb

Order Out of Chaos

Black swans, before their discovery in the late 1600s, were widely considered a scientific impossibility by Western minds.
Black swans, before their discovery in the late 1600s, were widely considered a scientific impossibility by Western minds.
Dean Mouhtaropoulos/Getty Images for Red Bull Air Race

Let's return to the world of weather forecasts for a moment, as well as the world of butterflies and hurricanes. You've probably heard of chaos theory, the mathematical field concerned with the seemingly disorganized behavior of highly dynamic systems. The term originates in 1961 with meteorologist Edward N. Lorenz and his fascination with how the smallest of atmospheric variables can result in drastically different weather models. Yes, it's the butterfly effect, the notion that an insect might flap its wings in Brazil and stir up a tornado in Texas.

Due to its many variables, a dynamic system such as Earth's atmosphere is difficult to predict -- and the Living Earth Simulator aims to forecast outcomes in dynamic systems composed of interwoven dynamic systems. How do we hope to stay afloat in such an ocean of chaos? Plus, consider that the simulated Earth would be one with access to a Living Earth Simulator: a simulation of the world that has access to a simulation of the world. Can even a supercomputer find predictable patterns amid such complexity?


Other critics take aim at our ability to predict virtually anything at all. Nassim Nicholas Taleb's Black Swan Theory takes its name from the fact that before the discovery of Australia, scientific observation suggested that all swans were white. There was no more such thing as a black swan as there was a green or purple one. Then European explorers discovered a black swan Down Under -- an event that was both unpredictable and exceptional.

The black swan was an outlier, existing beyond the realm of reasonable expectation. But the human mind depends on pattern recognition, so, Taleb writes in his Black Swan book, we humans think up explanations for an outlier's occurrence after we encounter it, making it explainable and predictable.

By their very nature, outliers are unpredictable and, according to Taleb, this implies the inability to predict the course of history, given how much outliers such as the market crash of 1987, the demise of the Soviet Bloc and the Sept. 11 terrorist attacks have drastically informed the shape of human events.

Another criticism stems not from the science of predictability but from the stubborn and irrational natures of humans. Assume for a moment that a cabal of supercomputers will one day crunch all our big data and advise us on which choice in a given decision will steer us away from some major catastrophe. Will we listen to the machines?

Columbia University statistician Victoria Stodden argues we might not, especially if we can't comprehend the colossal calculations that went in to the computer decision [source: Weinberger]. Stodden points to scientists' warnings about the dangers of climate change -- and how often these simulation-based warnings go unheeded.

Dirk Helbing and FutureICT remain confident, however, that the Living Earth Simulator will vastly improve humanity's ability to cope sustainably with the challenges of a dynamically changing world. The models won't be perfect, won't glimpse the far future or the minutiae of daily life. But, according to Helbing, they will provide us greater insight into how many systems that make up human society actually work.

Explore the links below to discover even more about the future of technological innovation.

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More Great Links


  • Bakker, R. Scott. "Outing the It that Thinks: The Collapse of an Intellectual Ecosystem." Three-Pound Brain.(Jan. 13, 2012)
  • Burnham, Michael. "NASA-Cisco climate project to flash 'Planetary Skin.'" The New York Times. March 3, 2009. (Jan. 13, 2012)
  • Daily, Larry Z. "The Relationship of Hobbies and Personality." Shepherd University. (Jan. 13, 2012)
  • FutureICT. Web site. 2011. (Jan. 13, 2012)
  • Hsu, Jeremy. "Europe's Living Earth Simulator Could Forecast the Future." Popular Science. April 30, 2010. (Jan. 13, 2012)
  • IBM. "Bringing big data to the enterprise: What is BIG DATA?" (Jan. 13, 2012)
  • Morgan, Gareth. "Earth project aims to 'simulate everything.'" BBC News. Dec. 27, 2010. (Jan. 13, 2012)
  • Taleb, Nassim Nicholas."'The Black Swan: The Impact of the Highly Improbable." The New York Times. April 22, 2007. (Jan. 13, 2011)
  • Weinberger, David. "The Machine That Would Predict the Future." Scientific American. December 2011.