Posts Tagged ‘complexity’
“Fools ignore complexity. Pragmatists suffer it… Geniuses remove it.”*…
World War II bomber planes returned from their missions riddled with bullet holes. The first response was, not surprisingly, to add armor to those areas most heavily damaged. However, the statistician Abraham Wald made what seemed like the counterintuitive recommendation to add armor to those parts with no damage. Wald had uniquely understood that the planes that had been shot where no bullet holes were seen were the planes that never made it back. That’s, of course, where the real problem was. Armor was added to the seemingly undamaged places, and losses decreased dramatically.
The visible bullet holes of this pandemic are the virus and its transmission. Understandably, a near-universal response to the COVID-19 pandemic has been to double down on those disciplines where we already possess deep and powerful knowledge: immunology and epidemiology. Massive resources have been directed at combating the virus by providing fast grants for disciplinary work on vaccines. Federal agencies have called for even more rapid response from the scientific community. This is a natural reaction to the immediate short-term crisis.
The damage we are not attending to is the deeper nature of the crisis—the collapse of multiple coupled complex systems.
Societies the world over are experiencing what might be called the first complexity crisis in history. We should not have been surprised that a random mutation of a virus in a far-off city in China could lead in just a few short months to the crash of financial markets worldwide, the end of football in Spain, a shortage of flour in the United Kingdom, the bankruptcy of Hertz and Niemann-Marcus in the United States, the collapse of travel, and to so much more.
As scientists who study complex systems, we conceive of a complexity crisis as a twofold event. First, it is the failure of multiple coupled systems—our physical bodies, cities, societies, economies, and ecosystems. Second, it involves solutions, such as social distancing, that involve unavoidable tradeoffs, some of which amplify the primary failures. In other words, the way we respond to failing systems can accelerate their decline.
We and our colleagues in the Santa Fe Institute Transmission Project believe there are some non-obvious insights and solutions to this crisis that can be gleaned from studying complex systems and their universal properties…
The more complicated and efficient a system gets, the more likely it is to collapse altogether. Scientists who study complex systems offer solutions to the pandemic: “The Damage We’re Not Attending To.”
See also: “Complex Systems Theory Explains Why Covid Crushed the World.”
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As we think systemically, we might recall that it was on this date in 1835 that the New York Sun began a series of six articles detailing the discovery of civilized life on the moon. Now known as “The Great Moon Hoax,” the articles attributed the “discovery” to Sir John Herschel, the greatest living astronmer of the day. Herschel was initially amused, wryly noting that his own real observations could never be as exciting. But ultimately he tired of having to answer questioners who believed the story. The series was not discovered to be a hoax for several weeks after its publication and, even then, the newspaper did not issue a retraction.
The “ruby amphitheater” on the Moon, per the New York Sun (source)
“Man is not born to solve the problem of the universe, but to find out what he has to do; and to restrain himself within the limits of his comprehension”*…
Half a century ago, the pioneers of chaos theory discovered that the “butterfly effect” makes long-term prediction impossible. Even the smallest perturbation to a complex system (like the weather, the economy or just about anything else) can touch off a concatenation of events that leads to a dramatically divergent future. Unable to pin down the state of these systems precisely enough to predict how they’ll play out, we live under a veil of uncertainty.
But now the robots are here to help…
In new computer experiments, artificial-intelligence algorithms can tell the future of chaotic systems. For example, researchers have used machine learning to predict the chaotic evolution of a model flame front like the one pictured above. Learn how– and what it may mean– at “Machine Learning’s ‘Amazing’ Ability to Predict Chaos.”
* Johann Wolfgang von Goethe
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As we contemplate complexity, we might recall that it was on this date in 1961 that Robert Noyce was issued patent number 2981877 for his “semiconductor device-and-lead structure,” the first patent for what would come to be known as the integrated circuit. In fact another engineer, Jack Kilby, had separately and essentially simultaneously developed the same technology (Kilby’s design was rooted in germanium; Noyce’s in silicon) and had filed a few months earlier than Noyce… a fact that was recognized in 2000 when Kilby was Awarded the Nobel Prize– in which Noyce, who had died in 1990, did not share.
Noyce (left) and Kilby (right)
“To imagine a language is to imagine a form of life”*…
Jeremy England is concerned about words—about what they mean, about the universes they contain. He avoids ones like “consciousness” and “information”; too loaded, he says. Too treacherous. When he’s searching for the right thing to say, his voice breaks a little, scattering across an octave or two before resuming a fluid sonority.
His caution is understandable. The 34-year-old assistant professor of physics at the Massachusetts Institute of Technology is the architect of a new theory called “dissipative adaptation,” which has helped to explain how complex, life-like function can self-organize and emerge from simpler things, including inanimate matter. This proposition has earned England a somewhat unwelcome nickname: the next Charles Darwin. But England’s story is just as much about language as it is about biology…
A new theory on the emergence of life’s complexity: “How Do You Say ‘Life’ in Physics?“
* Ludwig Wittgenstein, Philosophical Investigations
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As we resist the urge to simplify, we might send carefully-constructed birthday greetings to Sir Karl Raimund Popper; he was born on this date in 1902. One of the greatest philosophers of science of the 20th century, Popper is best known for his rejection of the classical inductivist views on the scientific method, in favor of empirical falsification: A theory in the empirical sciences can never be proven, but it can be falsified, meaning that it can and should be scrutinized by decisive experiments. (Or more simply put, whereas classical inductive approaches considered hypotheses false until proven true, Popper reversed the logic: conclusions drawn from an empirical finding are true until proven false.)
Popper was also a powerful critic of historicism in political thought, and (in books like The Open Society and Its Enemies and The Poverty of Historicism) an enemy of authoritarianism and totalitarianism.
“I’m not afraid of death; I just don’t want to be there when it happens”*…
The life expectancy for the average woman in the United States is 81 years and 2 months. For men, it’s 76 years and 5 months. These are the most recent estimates from the Centers for Disease Control and Prevention. Just subtract your current age from those numbers for a rough estimate of how many years you have left.
It feels accurate. It feels precise.
But people die at various ages. Life is imprecise. Otherwise, you could just plan your days all the way up to your last.
Also, life expectancy is typically quoted “from birth.” It’s the number of years a baby is expected to live the moment he or she escapes from the womb into the wondrous realities of the outside world. This is a good measure for progress in countries and is a fine wideout view, but it’s just so-so for you and me, as individuals.
The range of your life expectancy is much more interesting…
See for yourself: toggle to your gender and age on Flowing Data‘s interactive graphic (based on data from the Social Security Administration), and see the “Years You Have Left to Live, Probably.”
* Woody Allen
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As we memento mori, we might spare a thought for Giambattista Vico; he died on this date in 1744. A political philosopher, rhetorician, historian, and jurist, Vico was one of the greatest Enlightenment thinkers. Best known for the Scienza Nuova (1725, often published in English as New Science), he famously criticized the expansion and development of modern rationalism and was an apologist for classical antiquity.
He was an important precursor of systemic and complexity thinking (as opposed to Cartesian analysis and other kinds of reductionism); and he can be credited with the first exposition of the fundamental aspects of social science, though his views did not necessarily influence the first social scientists. Vico is often claimed to have fathered modern philosophy of history (although the term is not found in his text; Vico speaks of a “history of philosophy narrated philosophically”). While he was not strictly speaking a historicist, interest in him has been driven by historicists (like Isaiah Berlin).
From the Department of Stating the Obvious…
From AAAS’ Science, “It’s Official: Physics is Hard“:
Students and researchers alike have long understood that physics is challenging. But only now have scientists managed to prove it. It turns out that one of the most common goals in physics—finding an equation that describes how a system changes over time—is defined as “hard” by computer theory. That’s bad news for physics students who hope that a machine can solve all their homework problems, but at least their future jobs in the field are safe from automation.
Physicists are often interested in mathematically describing how a system behaves: for instance, a formula tracks the motions of the planets and their moons in their complicated dance around the sun. Researchers work out these equations by measuring the objects at various points in time and then developing a formula that links all of those points together, such as filling in a video from a set of snapshots.
With each new variable, however, it becomes tougher to find the right equation. Computers can speed things up by sifting through potential solutions at breakneck speed, but even the world’s top supercomputers meet their match with a certain class of problems, known as “hard” problems. These problems take exponentially more time to solve with every additional variable that is thrown into the mix—an extra planet’s motion, for instance…
[Full article here]
Problems like these, known in complexity theory as NP-hard, may be discouraging of the prospect of quick solutions; but at least they seem to offer physicists some measure of job security. Still, if a bankable short-cut could be found, it would have profound implications for math and it applications. So the Clay Mathematics Institute has chosen the challenge as one of its Millennium Problems: the scientist who comes up with a universal “problem tenderizer” wins $1 million.
As we remember that pie are square, we might spare a memorial thought for the polymathic John Arbuthnot; he died on this date in 1735. The mathematician, essayist, and physician published his translation of Huygens’ Of the Laws of Chance (1692), to which Arbuthnot added further games of chance– the first work on probability published in English. He wrote a series of satirical pamphlets introducing “john Bull” (the now-iconic “Englishman”), and co-founded Scriblerus Club, where he inspired co-founders Jonathan Swift (Gulliver’s Travels book III) and Alexander Pope (Peri Bathous, Or the Art of Sinking in Poetry, Memoirs of Martin Scriblerus, and The Dunciad). And from 1705, he was physician to Queen Anne until her death in 1714.
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