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Chaos by James Gleick

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Benoit Mandelbrot, butterfly effect, cellular automata, Claude Shannon: information theory, discrete time, Edward Lorenz: Chaos theory, experimental subject, Georg Cantor, Henri Poincaré, Isaac Newton, iterative process, John von Neumann, Louis Pasteur, mandelbrot fractal, Murray Gell-Mann, Norbert Wiener, pattern recognition, Richard Feynman, Richard Feynman, Stephen Hawking, stochastic process, trade route

Tiny differences in input could quickly become overwhelming differences in output—a phenomenon given the name “sensitive dependence on initial conditions.” In weather, for example, this translates into what is only half-jokingly known as the Butterfly Effect—the notion that a butterfly stirring the air today in Peking can transform storm systems next month in New York. When the explorers of chaos began to think back on the genealogy of their new science, they found many intellectual trails from the past. But one stood out clearly. For the young physicists and mathematicians leading the revolution, a starting point was the Butterfly Effect. The Butterfly Effect Physicists like to think that all you have to do is say, these are the conditions, now what happens next? —RICHARD P. FEYNMAN THE SUN BEAT DOWN through a sky that had never seen clouds.

But Lorenz tried different sorts of minor complications, and he finally succeeded when he put in an equation that varied the amount of heating from east to west, corresponding to the real-world variation between the way the sun warms the east coast of North America, for example, and the way it warms the Atlantic Ocean. The repetition disappeared. The Butterfly Effect was no accident; it was necessary. Suppose small perturbations remained small, he reasoned, instead of cascading upward through the system. Then when the weather came arbitrarily close to a state it had passed through before, it would stay arbitrarily close to the patterns that followed. For practical purposes, the cycles would be predictable—and eventually uninteresting. To produce the rich repertoire of real earthly weather, the beautiful multiplicity of it, you could hardly wish for anything better than a Butterfly Effect. The Butterfly Effect acquired a technical name: sensitive dependence on initial conditions. And sensitive dependence on initial conditions was not an altogether new notion.

“I’m still not clear on chaos,” says Laura Dern’s character in the 1993 film Jurassic Park, so that Jeff Goldblum’s character—who announces himself as a “chaotician”—can explain flirtatiously, “It simply deals with unpredictability in complex systems…. A butterfly can flap its wings in Peking, and in Central Park you get rain instead of sunshine.” By then the Butterfly Effect was well on its way to becoming a pop-culture cliché: inspiring at least two movies, an entry in Bartlett’s Quotations, a music video, and a thousand Web sites and blogs. (Only the place names keep changing: the butterfly flaps its wings in Brazil, Peru, China, California, Tahiti, and South America, and the rain/hurricane/tornado/storm arrives in Texas, Florida, New York, Nebraska, Kansas, and Central Park.) After the big hurricanes of 2006, Physics Today published an article titled “Battling the Butterfly Effect,” whimsically blaming butterflies in battalions: “Visions of Lepidoptera terrorist training camps spring suddenly to mind.” Aspects of chaos—different aspects, usually—have been taken up by modern management theorists on the one hand, and postmodern literary theorists on the other.

Exploring Everyday Things with R and Ruby by Sau Sheong Chang

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Alfred Russel Wallace, bioinformatics, business process, butterfly effect, cloud computing, Craig Reynolds: boids flock, Debian, Edward Lorenz: Chaos theory, Gini coefficient, income inequality, invisible hand, p-value, price stability, Skype, statistical model, stem cell, Stephen Hawking, text mining, The Wealth of Nations by Adam Smith, We are the 99%, web application, wikimedia commons

However, more often than not, a fluctuation can swing so wildly that the bottom drops out and the whole population dies off, as shown in Figure 8-6. This happens even if we start off with the same parameters! Why does this happen? We have discussed emergent behavior, where small local rules result in complex, macro-level, group behavior. The pattern we have observed here, rather than emergent behavior, can be classified as a kind of “butterfly effect”; see the sidebar Butterfly Effect. Figure 8-6. Population fluctuation swings, resulting in extinction of the roids Butterfly Effect In chaos theory, the butterfly effect is the sensitive dependence on initial conditions, where a small change somewhere in a nonlinear system can result in large differences at a later stage. This name was coined by Edward Lorenz, one of the pioneers of chaos theory (and no relation to Max Lorenz of the Lorenz curve fame). In 1961, Lorenz was using a computer model to rerun a weather prediction when he entered the shortened decimal value .506 instead of entering the full .506127.

Our focus in this simulation was on population patterns over a period of time. We observed that it is difficult to reach a state where a population is stable enough to survive for a long time. Very often, population fluctuations involve crazy swings that eventually end with the extinction of the society, even with identical starting parameters. We observed that a small effect can ripple down, causing unexpected changes—a phenomenon known as the butterfly effect. The final scenario dealt with evolution. We simulated natural selection by getting the offspring of the roids to inherit traits of their parents. These traits were specially designed to influence the survivability of the roids over a period of time. We anticipated that, if natural selection occurred, the traits of the roid population would move toward those that allow it to best survive.

: (question mark, colon), in Ruby ternary conditional expression, if and unless > (right angle bracket), The R Console, Variables and Functions -> assignment operator, R, Variables and Functions > R console prompt, The R Console ' ' (single quotes), enclosing Ruby strings, Strings [ ] (square brackets), Vectors, Matrices, Data frames accessing subset of R data frame, Data frames enclosing R matrix indexes, Matrices enclosing R vector indexes, Vectors [[ ]] (square brackets, double), enclosing single R vector index, Vectors A aes() function, R, Aesthetics An Inquiry into the Nature and Causes of the Wealth of Nations (University of Chicago Press), The Invisible Hand apply() function, R, Interpreting the Data Armchair Economist (Free Press), How to Be an Armchair Economist array() function, R, Arrays arrays, R, Arrays–Arrays arrays, Ruby, Arrays and hashes–Arrays and hashes, Arrays and hashes artificial society, Money (see Utopia example) as.Date() function, R, Number of Messages by Day 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Boids algorithm, Schooling Fish and Flocking Birds–The Origin of Boids Box, George Edward Pelham (statistician), regarding usefulness of models, The Simple Scenario break keyword, R, Conditionals and Loops brew command, Installing Ruby using your platform’s package management tool butterfly effect, The Changes C c() function, R, Vectors CALO Project, The Emailing Habits of Enron Executives camera, pulse oximeter using, Homemade Pulse Oximeter case expression, Ruby, case expression chaos theory, The Changes charts, Charting–Adjustments, Plotting charts, Statistical transformation, Geometric object, Interpreting the Data–Interpreting the Data, Interpreting the Data–Interpreting the Data, Interpreting the Data–Interpreting the Data, The Second Simulation, The Second Simulation–The Second Simulation, The Third Simulation–The Third Simulation, The Third Simulation–The Third Simulation, The Final Simulation–The Final Simulation, The Final Simulation–The Final Simulation, Analyzing the Simulation–Analyzing the Simulation, Analyzing the Second Simulation–Analyzing the Second Simulation, Number of Messages by Day of the Month–Number of Messages by Hour of the Day, Generating the Heart Sounds Waveform–Generating the Heart Sounds Waveform, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate, Money–Money, Money–Money, Implementation bar charts, Plotting charts, Interpreting the Data–Interpreting the Data, The Second Simulation–The Second Simulation, The Third Simulation–The Third Simulation, The Final Simulation–The Final Simulation histograms, Statistical transformation, Geometric object, Money–Money line charts, Interpreting the Data–Interpreting the Data, Analyzing the Simulation–Analyzing the Simulation, Analyzing the Second Simulation–Analyzing the Second Simulation Lorenz curves, Money–Money scatterplots, Interpreting the Data–Interpreting the Data, The Second Simulation, The Third Simulation–The Third Simulation, The Final Simulation–The Final Simulation, Number of Messages by Day of the Month–Number of Messages by Hour of the Day, Implementation waveforms, Generating the Heart Sounds Waveform–Generating the Heart Sounds Waveform, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate class methods, Ruby, Class methods and variables class variables, Ruby, Class methods and variables–Class methods and variables classes, R, Programming R classes, Ruby, Classes and objects–Classes and objects code examples, Using Code Examples (see example applications) colon (:), Symbols, Vectors creating R vectors, Vectors preceding Ruby symbols, Symbols comma-separated value (CSV) files, Importing data from text files (see CSV files) Comprehensive R Archive Network (CRAN), Packages conditionals, R, Conditionals and Loops conditionals, Ruby, Conditionals and loops–case expression contact information for 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a database, Importing data from text files, The First Simulation–The First Simulation, Interpreting the Data, How to Be an Armchair Economist, The Simulation, Grab and Parse–Grab and Parse, The Emailing Habits of Enron Executives–The Emailing Habits of Enron Executives, Homemade Digital Stethoscope–Extracting Data from Sound, Extracting Data from Sound–Extracting Data from Sound, Homemade Pulse Oximeter–Extracting Data from Video, Extracting Data from Video analyzing, Data, Data, Everywhere–Data, Data, Everywhere, Bringing the World to Us, How to Be an Armchair Economist charts for, How to Be an Armchair Economist (see charts) obstacles to, Data, Data, Everywhere–Data, Data, Everywhere simulations for, Bringing the World to Us (see simulations) audio, from stethoscope, Homemade Digital Stethoscope–Extracting Data from Sound CSV files for, Importing data from text files, The First Simulation–The First Simulation, Interpreting the Data, The Simulation, Extracting Data from Sound–Extracting Data from Sound, Extracting Data from Video from Enron, The Emailing Habits of Enron Executives–The Emailing Habits of Enron Executives from Gmail, Grab and Parse–Grab and Parse importing, R, Importing Data–Importing data from a database video, from pulse oximeter, Homemade Pulse Oximeter–Extracting Data from Video data frames, R, Data frames–Data frames data mining, The Idea data.frame() function, R, Data frames database, importing data from, Importing data from a database–Importing data from a database dbConnect() function, R, Importing data from a database dbGet() function, R, Importing data from a database DBI packages, R, Importing data from a database–Importing data from a database Debian system, installing Ruby on, Installing Ruby using your platform’s package management tool def keyword, Ruby, Classes and objects dimnames() function, R, Matrices distribution, normal, Money dollar sign ($), preceding R list item names, Lists doodling example, Shoes doodler–Shoes doodler double quotes (" "), enclosing Ruby strings, Strings duck typing, Ruby, Code like a duck–Code like a duck dynamic typing, Ruby, Code like a duck–Code like a duck E economics example, A Simple Market Economy–A Simple Market Economy, The Producer–The Producer, The Consumer–The Consumer, Some Convenience Methods–Some Convenience Methods, The Simulation–The Simulation, Analyzing the Simulation–Analyzing the Simulation, The Producer–The Producer, The Consumer–The Consumer, Market–Market, The Simulation–The Simulation, Analyzing the Second Simulation–Analyzing the Second Simulation, Price Controls–Price Controls charts for, Analyzing the Simulation–Analyzing the Simulation, Analyzing the Second Simulation–Analyzing the Second Simulation Consumer class for, The Consumer–The Consumer, The Consumer–The Consumer Market class for, Some Convenience Methods–Some Convenience Methods, Market–Market modeling, A Simple Market Economy–A Simple Market Economy price controls analysis, Price 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Number of Messages by Day of the Month–Number of Messages by Day of the Month, Number of Messages by Day of Week–Number of Messages by Hour of the Day R package for, creating, MailMiner–MailMiner emergent behavior, The Origin of Boids (see also flocking example) Enron Corporation scandal, The Emailing Habits of Enron Executives Epstein, Joshua (researcher), It’s a Good Life Growing Artificial Societies: Social Science from the Bottom Up (Brookings Institution Press/MIT Press), It’s a Good Life equal sign (=), assignment operator, R, Variables and Functions Euclidean distance, Roids evolution, Evolution example applications, Using Code Examples, Shoes stopwatch–Shoes stopwatch, Shoes doodler–Shoes doodler, The R Console–Sourcing Files and the Command Line, Data frames–Introducing ggplot2, qplot–qplot, Statistical transformation–Geometric object, Adjustments–Adjustments, Offices and Restrooms, A Simple Market Economy, Grab and Parse, My Beating Heart, Schooling Fish and Flocking Birds, Money artificial utopian society, Money (see Utopia example) birds flocking, Schooling Fish and Flocking Birds (see flocking example) doodling, Shoes doodler–Shoes doodler economics, A Simple Market Economy (see economics example) email, Grab and Parse (see email example) fuel economy, qplot–qplot, Adjustments–Adjustments heartbeat, My Beating Heart (see heartbeat example) height and weight, The R Console–Sourcing Files and the Command Line league table, Data frames–Introducing ggplot2 movie database, Statistical transformation–Geometric object permission to use, Using Code Examples restrooms, Offices and Restrooms (see restrooms example) stopwatch, Shoes stopwatch–Shoes stopwatch expressions, R, Programming R external libraries, Ruby, Requiring External Libraries–Requiring External Libraries F factor() function, R, Factors, Text Mining factors, R, Factors–Factors FFmpeg library, Extracting Data from Video, Extracting Data from Video field of vision (FOV), Roids fish, schools of, Schooling Fish and Flocking Birds (see flocking example) flocking example, Schooling Fish and Flocking Birds–The Origin of Boids, The Origin of Boids, Simulation–Simulation, Roids–Roids, The Boid Flocking Rules–Putting in Obstacles, The Boid Flocking Rules–The Boid Flocking Rules, A Variation on the Rules–A Variation on the Rules, Going Round and Round–Going Round and Round, Putting in Obstacles–Putting in Obstacles Boids algorithm for, Schooling Fish and Flocking Birds–The Origin of Boids centering path for, Going Round and Round–Going Round and Round obstacles in path for, Putting in Obstacles–Putting in Obstacles research regarding, A Variation on the Rules–A Variation on the Rules Roid class for, Roids–Roids rules for, The Origin of Boids, The Boid Flocking Rules–The Boid Flocking Rules simulations for, Simulation–Simulation, The Boid Flocking Rules–Putting in Obstacles flows, Shoes, Shoes stopwatch fonts used in this book, Conventions Used in This Book–Conventions Used in This Book for loop, R, Conditionals and Loops format() function, R, Number of Messages by Day of the Month FOV (field of vision), Roids fuel economy example, qplot–qplot, Adjustments–Adjustments function class, R, Programming R functions, R, Variables and Functions–Variables and Functions G GAM (generalized addictive model), The Changes gem command, Ruby, Requiring External Libraries .gem file extension, Requiring External Libraries generalized addictive model (GAM), The Changes Gentleman, Robert (creator of R), Introducing R geom_bar() function, R, Interpreting the Data, The Second Simulation, The Final Simulation geom_histogram() function, R, Geometric object geom_line() function, R, Analyzing the Simulation geom_point() function, R, Plot, Interpreting the Data, Generating the Heart Sounds Waveform geom_smooth() function, R, Interpreting the Data ggplot() function, R, Plot ggplot2 package, R, Introducing ggplot2–Adjustments Gini coefficient, Money Git utility, Ruby Version Manager (RVM) Gmail, retrieving message data from, Grab and Parse–Grab and Parse graphics device, opening, Basic Graphs graphics package, R, Basic Graphs graphs, Charting (see charts) Growing Artificial Societies: Social Science from the Bottom Up (Brookings Institution Press/MIT Press), It’s a Good Life H hash mark, curly brackets (#{ }), enclosing Ruby string escape sequences, Strings hashes, Ruby, Arrays and hashes–Arrays and hashes heart, diagram of, Generating the Heart Sounds Waveform heartbeat example, My Beating Heart, My Beating Heart, My Beating Heart, Homemade Digital Stethoscope, Homemade Digital Stethoscope, Homemade Digital Stethoscope–Extracting Data from Sound, Generating the Heart Sounds Waveform–Generating the Heart Sounds Waveform, Generating the Heart Sounds Waveform, Finding the Heart Rate–Finding the Heart Rate, Homemade Pulse Oximeter–Homemade Pulse Oximeter, Homemade Pulse Oximeter–Extracting Data from Video, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate charts for, Generating the Heart Sounds Waveform–Generating the Heart Sounds Waveform, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate data for, Homemade Digital Stethoscope–Extracting Data from Sound, Homemade Pulse Oximeter–Extracting Data from Video audio from stethoscope, Homemade Digital Stethoscope–Extracting Data from Sound video from pulse oximeter, Homemade Pulse Oximeter–Extracting Data from Video heart rate, My Beating Heart, Finding the Heart Rate–Finding the Heart Rate, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate finding from video file, Generating the Heartbeat Waveform and Calculating the Heart Rate–Generating the Heartbeat Waveform and Calculating the Heart Rate finding from WAV file, Finding the Heart Rate–Finding the Heart Rate health parameters for, My Beating Heart heart sounds, My Beating Heart, My Beating Heart, Homemade Digital Stethoscope, Generating the Heart Sounds Waveform health parameters for, My Beating Heart recording, Homemade Digital Stethoscope types of, My Beating Heart, Generating the Heart Sounds Waveform homemade pulse oximeter for, Homemade Pulse Oximeter–Homemade Pulse Oximeter homemade stethoscope for, Homemade Digital Stethoscope height and weight example, The R Console–Sourcing Files and the Command Line here-documents, Ruby, Strings hex editor, Extracting Data from Sound histograms, Statistical transformation, Geometric object, Money–Money Homebrew tool, Installing Ruby using your platform’s package management tool hyphen (-), Variables and Functions, Variables and Functions -> assignment operator, R, Variables and Functions <- assignment operator, R, Variables and Functions I icons used in this book, Conventions Used in This Book if expression, R, Conditionals and Loops if expression, Ruby, if and unless–if and unless Ihaka, Ross (creator of R), Introducing R ImageMagick library, Extracting Data from Video IMAP (Internet Message Access Protocol), Grab and Parse importing data, R, Importing Data–Importing data from a database inheritance, Ruby, Inheritance–Inheritance initialize method, Ruby, Classes and objects inner product, Roids–Roids installation, Installing Ruby–Installing Ruby using your platform’s package management tool, Installing Shoes–Installing Shoes, Introducing R, Installing packages–Installing packages R, Introducing R R packages, Installing packages–Installing packages Ruby, Installing Ruby–Installing Ruby using your platform’s package management tool Shoes, Installing Shoes–Installing Shoes Internet Message Access Protocol (IMAP), Grab and Parse Internet Message Format, The Emailing Habits of Enron Executives invisible hand metaphor, The Invisible Hand irb application, Running Ruby–Running Ruby J jittering, Adjustments jpeg() function, R, Basic Graphs L Landsburg, Stephen E.


pages: 346 words: 92,984

The Lucky Years: How to Thrive in the Brave New World of Health by David B. Agus

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3D printing, active transport: walking or cycling, Affordable Care Act / Obamacare, Albert Einstein, butterfly effect, clean water, cognitive dissonance, crowdsourcing, Danny Hillis, Drosophila, Edward Lorenz: Chaos theory, en.wikipedia.org, epigenetics, Kickstarter, medical residency, meta analysis, meta-analysis, microbiome, microcredit, mouse model, Murray Gell-Mann, New Journalism, pattern recognition, personalized medicine, phenotype, placebo effect, publish or perish, randomized controlled trial, risk tolerance, statistical model, stem cell, Steve Jobs, Thomas Malthus, wikimedia commons

Lorenz was an MIT meteorologist who tried to explain why it is so hard to make good weather forecasts; he wound up starting a scientific revolution called chaos theory. In the early 1960s, he noticed that small differences in a dynamic system such as the atmosphere could give rise to vast and often unexpected results. These observations ultimately led him to develop what became known as the butterfly effect, a term that grew out of an academic paper he presented in 1972 entitled “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?”7 The butterfly effect has significant relevance in all matters of health. We are each agents of change in the Lucky Years; we are each butterflies flapping our wings in a space-time continuum on earth. How we live today affects how we are tomorrow. It also impacts the people with whom we interact, our neighbors, the next generation, our children, and their children.

CLICK HERE TO SIGN UP or visit us online to sign up at eBookNews.SimonandSchuster.com Contents NOTE TO READERS EPIGRAPH LIST OF ILLUSTRATIONS INTRODUCTION DESTINY OF THE SPECIES Welcome to the Lucky Years CHAPTER 1 THE CENTURY OF BIOLOGY The Cure Is Already Inside You CHAPTER 2 THIS ISN’T SCIENCE FICTION The Power of Technology to Extend Your Life CHAPTER 3 THE FUTURE YOU How Your Small Data in the Context of Big Data Will Save You CHAPTER 4 THE DAWN OF PRECISION MEDICINE How to Manage Its Power and Perils CHAPTER 5 TAKE THE TWO-WEEK CHALLENGE How to Measure and Interpret Your Own Data CHAPTER 6 THE DANGER OF MISINFORMATION How to Know Whom and What to Trust CHAPTER 7 A BODY IN MOTION TENDS TO STAY LUCKY The One Supplement You’re Not Getting Enough Of CHAPTER 8 WONDER DRUGS THAT WORK Sleep, Sex, Touching, and Tools to Tame Inflammation CHAPTER 9 THE BUTTERFLY EFFECT Get Ready to Flap Your Wings ACKNOWLEDGMENTS ABOUT THE AUTHOR NOTES INDEX NOTE TO READERS This publication contains the opinions and ideas of its author. It is intended to provide helpful and informative materials on the subjects addressed in the publication. It is sold with the understanding that the author and publisher are not engaged in rendering medical, health, or any other kind of professional services in the book.

While these drugs can’t prevent infection itself, if they can prevent potentially fatal complications like organ failure, they will likely be part of the treatment protocol until an effective preventive measure such as a vaccine against the virus can be developed. Once again, this goes to show the power of what’s already in our arsenal. The Lucky Years are already here. And even though we’re entering a high-tech era of medicine, the same old ancient secrets to a good, long life are still relevant. Nothing will ever be able to substitute for things like sleep, sex, and touch—and perhaps gnawing on the bark of a willow tree. CHAPTER 9 The Butterfly Effect Get Ready to Flap Your Wings All religions, arts, and sciences are branches of the same tree. All these aspirations are directed toward ennobling man’s life, lifting it from the sphere of mere physical existence, and leading the individual toward freedom. —Albert Einstein Medicine is a science of uncertainty and an art of probability. —Sir William Osler If a jeweler tried to sell you a diamond that looked fake, you’d probably find another jeweler because something in your gut would tell you to move on.


pages: 208 words: 70,860

Paradox: The Nine Greatest Enigmas in Physics by Jim Al-Khalili

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Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, butterfly effect, clockwork universe, complexity theory, dark matter, Edmond Halley, Edward Lorenz: Chaos theory, Ernest Rutherford, Henri Poincaré, invention of the telescope, Isaac Newton, luminiferous ether, Magellanic Cloud, Olbers’ paradox, Schrödinger's Cat, Search for Extraterrestrial Intelligence, The Present Situation in Quantum Mechanics, Wilhelm Olbers

He won the King’s prize even though he didn’t come up with an answer to the original question about the stability of the whole solar system. Poincaré had discovered that the way a system of even just three interacting bodies evolves in time cannot be knowable exactly—let alone one involving all bodies in the solar system (at least, all the planets and their moons, along with the Sun). But the implications of this discovery would have to wait another three-quarters of a century. THE BUTTERFLY EFFECT Let’s give our all-powerful computer the far more modest task of predicting the way the balls on a pool table will scatter when hit by the cue ball at the start of a game. Every ball on the table will be knocked in some way and most will undergo multiple collisions, many bouncing off each other and the sides of the table. Of course, the computer would need to know precisely how hard the cue ball is struck and the exact angle at which it collides with the first ball in the pack.

This is why it is so difficult to make long-term weather predictions, since we can never know to infinite accuracy all the variables that affect the real weather. It’s just like the pool-table example, only far more complicated. We can now know with reasonable reliability if it will rain in a few days’ time, but we can never know if will rain on this date next year. It was this profound realization that led Lorenz to coin the term “the butterfly effect.” The idea of the flap of a butterfly’s wings having a far-reaching ripple-type effect on subsequent events seems to have first appeared in a short story called “A Sound of Thunder,” written in 1952 by Ray Bradbury. The idea was borrowed by Lorenz, who popularized it as the now familiar notion of the flapping of a butterfly’s wings somewhere leading months later to a hurricane on the other side of the world.

For it doesn’t matter that we live in a deterministic universe in which the future is, in principle, fixed. That future would be knowable only if we were able to view the whole of space and time from the outside. But for us, and our consciousnesses, embedded within space-time, that future is never knowable to us. It is that very unpredictability that gives us an open future. The choices we make are, to us, real choices, and because of the butterfly effect, tiny changes brought about by our different decisions can lead to very different outcomes, and hence different futures. So, thanks to chaos theory, our future is never knowable to us. You might prefer to say that the future is preordained and that our free will is just an illusion—but the point remains that our actions still determine which of the infinite number of possible futures is the one that gets played out.


pages: 226 words: 59,080

Economics Rules: The Rights and Wrongs of the Dismal Science by Dani Rodrik

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airline deregulation, Albert Einstein, bank run, barriers to entry, Bretton Woods, butterfly effect, capital controls, Carmen Reinhart, central bank independence, collective bargaining, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, distributed generation, Edward Glaeser, Eugene Fama: efficient market hypothesis, Fellow of the Royal Society, financial deregulation, financial innovation, floating exchange rates, fudge factor, full employment, George Akerlof, Gini coefficient, Growth in a Time of Debt, income inequality, inflation targeting, informal economy, invisible hand, Jean Tirole, Joseph Schumpeter, Kenneth Rogoff, labor-force participation, liquidity trap, loss aversion, low skilled workers, market design, market fundamentalism, minimum wage unemployment, oil shock, open economy, price stability, prisoner's dilemma, profit maximization, quantitative easing, randomized controlled trial, rent control, rent-seeking, Richard Thaler, risk/return, Robert Shiller, Robert Shiller, school vouchers, South Sea Bubble, spectrum auction, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, trade liberalization, trade route, ultimatum game, University of East Anglia, unorthodox policies, Washington Consensus, white flight

., 1n Boulding, Kenneth, 11 bounded rationality, 203 Bowles, Samuel, 71n Brazil: antipoverty programs of, 4 globalization and, 166 Bretton Woods Conference (1944), 1–2 Britain, Great, property rights and, 98 bubbles, 152–58 business cycles, 125–37 balanced budgets and, 171 capital flow in, 127 classical economics and, 126–27, 129, 137 inflation in, 126–27, 133, 135, 137 new classical models and, 130–34, 136–37 butterfly effect, 39 California, University of: at Berkeley, 107, 136, 147 at Los Angeles, 139 Cameron, David, 109 capacity utilization rates, 130 capital, neoclassical distribution theory and, 122, 124 capital flow: in business cycles, 127 economic growth and, 17–18, 114, 164–67 globalization and, 164–67 growth diagnostics and, 90 speculation and, 2 capitalism, 118–24, 127, 144, 205, 207 carbon, emissions quotas vs. taxes in reduction of, 188–90, 191–92 Card, David, 57 Carlyle, Thomas, 118 carpooling, 192, 193–94 cartels, 95 Cartwright, Nancy, 20, 22n, 29 cash grants, 4, 55, 105–6 Cassidy, John, 157n Central Bank of India, 154 Chang, Ha-Joon, 11 chaos theory, butterfly effect and, 39 Chicago, University of, 131, 152 Chicago Board of Trade, 55 Chile, antipoverty programs and, 4 China, People’s Republic of, 156, 163, 164 cigarette industry, taxation and, 27–28 Clark, John Bates, 119 “Classical Gold Standard, The: Some Lessons for Today” (Bordo), 127n classical unemployment, 126 climate change, 188–90, 191–92 climate modeling, 38, 40 Cochrane, John, 131 coffee, 179, 185 Colander, David, 85 collective bargaining, 124–25, 143 Colombia, educational vouchers in, 24 colonialism, developmental economics and, 206–7 “Colonial Origins of Comparative Development, The” (Acemoglu, Robinson, and Johnson), 206–7 Columbia University, 2, 108 commitment, in game theory, 33 comparative advantage, 52–55, 58n, 59–60, 139, 170 compensation for risk models, 110 competition, critical assumptions in, 28–29 complementarities, 42 computable general equilibrium (CGE) models, 41 computational models, 38, 41 computers, model complexity and, 38 Comte, Auguste, 81 conditional cash transfer (CCT) programs, 4, 105–6 congestion pricing, 2–3 Constitution, U.S., 187 construction industry, Great Recession and, 156 consumers, consumption, 119, 129, 130, 132, 136, 167 cross-price elasticity in, 180–81 consumer’s utility, 119 contextual truths, 20, 174 contingency, 25, 145, 173–74, 185 contracts, 88, 98, 161, 205 coordination models, 16–17, 42, 200 corn futures, 55 corruption, 87, 89, 91 costs, behavioral economics and, 70 Cotterman, Nancy, xiv Cournot, Antoine-Augustin, 13n Cournot competition, 68 credibility, in game theory, 33 “Credible Worlds, Capacities and Mechanisms” (Sugden), 172n credit rating agencies, 155 credit rationing, 64–65 critical assumptions, 18, 26–29, 94–98, 150–51, 180, 183–84, 202 cross-price elasticity, 180–81 Cuba, 57 currency: appreciation of, 60, 167 depreciation of, 153 economic growth and, 163–64, 167 current account deficits, 153 Curry, Brendan, xv Dahl, Gordon B., 151n Darwin, Charles, 113 Davis, Donald, 108 day care, 71, 190–91 Debreu, Gerard, 49–51 debt, national, 153 decision trees, 89–90, 90 DeLong, Brad, 136 democracy, social sciences and, 205 deposit insurance, 155 depreciation, currency, 153 Depression, Great, 2, 128, 153 deregulation, 143, 155, 158–59, 162, 168 derivatives, 153, 155 deterrence, in game theory, 33 development economics, 75–76, 86–93, 90, 159–67, 169, 201, 202 colonial settlement and, 206–7 institutions and, 98, 161, 202, 205–7 reform fatigue and, 88 diagnostic analysis, 86–93, 90, 97, 110–11 Dijkgraaf, Robbert, xiv “Dirtying White: Why Does Benn Steil’s History of Bretton Woods Distort the Ideas of Harry Dexter White?”

Interestingly, the immediate example that Watts deploys is the economy: “The U.S. economy, for example, is the product of the individual actions of millions of people, as well as hundreds of thousands of firms, thousands of government agencies, and countless other external and internal factors, ranging from the weather in Texas to interest rates in China.”21 As Watts notes, disturbances in one part of the economy—say, in mortgage finance—can be amplified and produce major shocks for the entire economy, as in the “butterfly effect” from chaos theory. It is interesting that Watts would point to the economy, since efforts to construct large-scale economic models have been singularly unproductive to date. To put it even more strongly, I cannot think of an important economic insight that has come out of such models. In fact, they have often led us astray. Overconfidence in the prevailing macroeconomic orthodoxy of the day resulted in the construction of several large-scale simulation models of the US economy in the 1960s and 1970s built on Keynesian foundations.


pages: 266 words: 86,324

The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow

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Albert Einstein, Alfred Russel Wallace, Antoine Gombaud: Chevalier de Méré, Atul Gawande, Brownian motion, butterfly effect, correlation coefficient, Daniel Kahneman / Amos Tversky, Donald Trump, feminist movement, forensic accounting, Gerolamo Cardano, Henri Poincaré, index fund, Isaac Newton, law of one price, pattern recognition, Paul Erdős, probability theory / Blaise Pascal / Pierre de Fermat, RAND corporation, random walk, Richard Feynman, Richard Feynman, Ronald Reagan, Stephen Hawking, Steve Jobs, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, V2 rocket, Watson beat the top human players on Jeopardy!

But Lorenz found that such small differences led to massive changes in the result.2 The phenomenon was dubbed the butterfly effect, based on the implication that atmospheric changes so small they could have been caused by a butterfly flapping its wings can have a large effect on subsequent global weather patterns. That notion might sound absurd—the equivalent of the extra cup of coffee you sip one morning leading to profound changes in your life. But actually that does happen—for instance, if the extra time you spent caused you to cross paths with your future wife at the train station or to miss being hit by a car that sped through a red light. In fact, Lorenz’s story is itself an example of the butterfly effect, for if he hadn’t taken the minor decision to extend his calculation employing the shortcut, he would not have discovered the butterfly effect, a discovery which sparked a whole new field of mathematics.

In this experiment, as one song or another by chance got an early edge in downloads, its seeming popularity influenced future shoppers. It’s a phenomenon that is well-known in the movie industry: moviegoers will report liking a movie more when they hear beforehand how good it is. In this example, small chance influences created a snowball effect and made a huge difference in the future of the song. Again, it’s the butterfly effect. In our lives, too, we can see through the microscope of close scrutiny that many major events would have turned out differently were it not for the random confluence of minor factors, people we’ve met by chance, job opportunities that randomly came our way. For example, consider the actor who, for seven years starting in the late 1970s, lived in a fifth-floor walk-up on Forty-ninth Street in Manhattan, struggling to make a name for himself.


pages: 327 words: 97,720

Loneliness: Human Nature and the Need for Social Connection by John T. Cacioppo

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Alfred Russel Wallace, biofilm, butterfly effect, Celebration, Florida, corporate governance, delayed gratification, experimental subject, impulse control, income inequality, Jane Jacobs, mental accounting, meta analysis, meta-analysis, placebo effect, post-industrial society, Rodney Brooks, Ted Kaczynski, The Death and Life of Great American Cities, theory of mind, urban planning, urban renewal, Walter Mischel

To echo Henry Melvill once again: “Our actions run as causes and return to us as results.” In the field of complex adaptive systems, scientists refer to the Butterfly Effect, whereby the wind displaced by the flutter of a butterfly’s wing in Africa might initiate an immensely involved string of consequences that alter the weather over Europe days or weeks later. This particular example may be something of an exaggeration, but it isn’t just a metaphor. Using supercomputers, researchers can actually work out the details that allow simple causes to interact, compound, and amplify to yield complex and profound results. In more technical terms, the Butterfly Effect is called “sensitive dependence on initial conditions,” and it reflects the way that small-scale events interact with large ones. The more dramatic the small-scale cause, the more immediate and more easily measured the large-scale results.

The simple realizations that we are not passive victims, that we do have some control, and that we can change our situation by changing our thoughts, expectations, and behaviors toward others can have a surprisingly empowering effect, especially on our conscious effort to self-regulate. A second inkling of control comes from recognizing that we have latitude in choosing where to invest our social energy. And as we saw in our discussion of the Butterfly Effect, it does not take an enormous change to alter one’s course and destination dramatically. Charitable activities enable us to put ourselves in the social picture with less fear of rejection or abuse, but even here some discretion is in order. Coaching kids’ soccer requires at least a little knowledge of the game, but being manager or assistant coach often requires nothing more than a willingness to show up and pass around the Gatorade and the orange slices.

An increase in average per capita memberships by one unit was correlated with a decrease in mortality of 66.8 per 100,000. Lower levels of trust within the local culture were associated with higher rates of mortality for every cause of death, including cardiovascular disease, cancer, and infant mortality. One interpretation of such data: Social isolation, including social fragmentation, can kill. Henry Melvill wrote of our causes returning to us as effects; complexity theorists have their Butterfly Effect. Whether we think in terms of “sympathetic threads” or of autonomous agents acting in a complex system, the fact remains that individual behaviors created both the peace and beauty of Middlebury, Vermont, and the tribal warfare of the Sunni triangle. Of course vast economic, political, and cultural forces are also at play, but ultimately, human beings shape their environment through individual, iterative behaviors.


pages: 295 words: 66,824

A Mathematician Plays the Stock Market by John Allen Paulos

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Benoit Mandelbrot, Black-Scholes formula, Brownian motion, business climate, butterfly effect, capital asset pricing model, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, Donald Trump, double entry bookkeeping, Elliott wave, endowment effect, Erdős number, Eugene Fama: efficient market hypothesis, four colour theorem, George Gilder, global village, greed is good, index fund, invisible hand, Isaac Newton, John Nash: game theory, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Nash equilibrium, Network effects, passive investing, Paul Erdős, Ponzi scheme, price anchoring, Ralph Nelson Elliott, random walk, Richard Thaler, Robert Shiller, Robert Shiller, short selling, six sigma, Stephen Hawking, transaction costs, ultimatum game, Vanguard fund, Yogi Berra

This is so despite the fact that linear systems and models are much more robust, with small differences in initial conditions leading only to small differences in final outcomes. They’re also easier to predict mathematically, and this is why they’re so often employed whether their application is appropriate or not. The chestnut about the economist looking for his lost car keys under the street lamp comes to mind. “You probably lost them near the car,” his companion remonstrates, to which the economist responds, “I know, but the light is better over here.” The “butterfly effect” is the term often used for the sensitive dependence of nonlinear systems, a characteristic that has been noted in phenomena ranging from fluid flow and heart fibrillations to epilepsy and price fluctuations. The name comes from the idea that a butterfly flapping its wings someplace in South America might be sufficient to change future weather systems, helping to bring about, say, a tornado in Oklahoma that would otherwise not have occurred.

Brian auditors Aumann, Robert availability error average values compared with distribution of incomes risk as variance from averages average return compared with median return average value compared with distribution of incomes buy-sell rules and outguessing average guess risk as variance from average value averaging down Bachelier, Louis Bak, Per Barabasi, Albert-Lazló Bartiromo, Maria bear markets investor self-descriptions and shorting and distorting strategy in Benford, Frank Benford’s Law applying to corporate fraud background of frequent occurrence of numbers governed by Bernoulli, Daniel Beta (B) values causes of variations in comparing market against individual stocks or funds strengths and weaknesses of technique for finding volatility and Big Bang billiards, as example of nonlinear system binary system biorhythm theory Black, Fischer Black-Scholes option formula blackjack strategies Blackledge, Todd “blow up,” investor blue chip companies, P/E ratio of Bogle, John bonds Greenspan’s impact on bond market history of stocks outperforming will not necessarily continue to be outperformed by stocks Bonds, Barry bookkeeping. see accounting practices bottom-line investing Brock, William brokers. see stock brokers Buffett, Warren bull markets investor self-descriptions and pump and dump strategy in Butterfly Economics (Ormerod) “butterfly effect,” of nonlinear systems buy-sell rules buying on the margin. see also margin investments calendar effects call options. see also stock options covering how they work selling strategies valuation tools campaign contributions Capital Asset Pricing Model capital gains vs. dividends Central Limit Theorem CEOs arrogance of benefits in manipulating stock prices remuneration compared with that of average employee volatility due to malfeasance of chain letters Chaitin, Gregory chance. see also whim trading strategies and as undeniable factor in market chaos theory. see also nonlinear systems charity Clayman, Michelle cognitive illusions availability error confirmation bias heuristics rules of thumb for saving time mental accounts status quo bias Cohen, Abby Joseph coin flipping common knowledge accounting scandals and definition and importance to investors dynamic with private knowledge insider trading and parable illustrating private information becoming companies/corporations adjusting results to meet expectations applying Benford’s Law to corporate fraud comparing corporate and personal accounting financial health and P/E ratio of blue chips competition vs. cooperation, prisoner’s dilemma complexity changing over time horizon of sequences (mathematics) of trading strategies compound interest as basis of wealth doubling time and formulas for future value and present value and confirmation bias definition of investments reflecting stock-picking and connectedness. see also networks European market causing reaction on Wall Street interactions based on whim interactions between technical traders and value traders irrational interactions between traders Wolfram model of interactions between traders Consumer Confidence Index (CCI) contrarian investing dogs of the Dow measures of excellence and rate of return and cooperation vs. competition, prisoner’s dilemma correlation coefficient. see also statistical correlations counter-intuitive investment counterproductive behavior, psychology of covariance calculation of portfolio diversification based on portfolio volatility and stock selection and Cramer, James crowd following or not herd-like nature of price movements dart throwing, stock-picking contest in the Wall Street Journal data mining illustrated by online chatrooms moving averages and survivorship bias and trading strategies and DeBondt, Werner Deciding What’s News (Gans) decimalization reforms decision making minimizing regret selling WCOM depression of derivatives trading, Enron despair and guilt over market losses deviation from the mean. see also mean value covariance standard deviation (d) variance dice, probability and Digex discounting process, present value of future money distribution of incomes distribution of wealth dynamic of concentration UN report on diversified portfolios. see stock portfolios, diversifying dividends earnings and proposals benefitting returns from Dodd, David dogs of the Dow strategy “dominance” principle, game theory dot com IPOs, as a pyramid scheme double-bottom trend reversal “double-dip” recession double entry bookkeeping doubling time, compound interest and Dow dogs of the Dow strategy percentages of gains and losses e (exponential growth) compound interest and higher mathematics and earnings anchoring effect and complications with determination of inflating (WCOM) P/E ratio and stock valuation and East, Steven H.

Kozlowski, Dennis Kraus, Karl Krauthammer, Charles Kudlow, Larry Lakonishok, Josef Landsburg, Steven Lay, Ken LeBaron, Blake Lefevre, Edwin Leibweber, David linguistics, power law and Lo, Andrew logistic curve lognormal distribution Long-Term Capital Management (LTCM) losing through winning loss aversion lotteries present value and as tax on stupidity Lynch, Peter MacKinlay, Craig mad money Malkiel, Burton management, manipulating stock prices Mandelbrot, Benoit margin calls margin investments buying on the margin as investment type margin calls selling on the margin market makers decimalization and World Class Options Market Maker (WCOMM) Markowitz, Harry mathematics, generally Greek movies and plays about outguessing the average guess risk and stock markets and Mathews, Eddie “maximization of expected value” principle mean value. see also expected value arithmetic mean deviation from the mean geometric mean regression to the mean using interchangeably with expected value media celebrities and crisis mentality and impact on market volatility median rate of return Merrill Lynch Merton, Robert mnemonic rules momentum investing money, categorizing into mental accounts Morgenson, Gretchen Motley Fool contrarian investment strategy PEG ratio and moving averages complications with evidence supporting example of generating buy-sell rules from getting the big picture with irrelevant in efficient market phlegmatic nature of mu (m) multifractal forgeries mutual funds expert picks and hedge funds index funds politically incorrect rationale for socially regressive funds mutual knowledge, contrasted with common knowledge Nash equilibrium Nash, John Neff, John negatively correlated stocks as basis of mutual fund selection as basis of stock selection stock portfolios and networks Internet as example of price movements and six degrees of separation and A New Kind of Science (Wolfram) Newcomb, Simon Newcombe, William Newcombe’s paradox Niederhoffer, Victor Nigrini, Mark nominal value A Non-Random Walk Down Wall Street (Lo and MacKinlay) nonlinear systems billiards example “butterfly effect” or sensitive dependence of chaos theory and fractals and investor behavior and normal distribution Nozick, Robert numbers anchoring effect Benford’s Law and Fibonacci numbers and off-shore entities, Enron Once Upon a Number (Paulos) online chatrooms online trading optimal portfolio balancing with risk-free portfolio Markowitz efficient frontier of options. see stock options Ormerod, Paul O’Shaughnessy, James P/B (price-to-book) ratio P/E ratio interpreting measuring future earnings expectations PEG variation on stock valuation and P/S (price to sales) ratio paradoxes Efficient Market Hypothesis and examples of Newcombe’s paradox Parrondo’s paradox St.


pages: 250 words: 75,586

When the Air Hits Your Brain: Tales From Neurosurgery by Frank Vertosick

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butterfly effect, double helix, index card, medical residency, random walk

Example: a billiard ball rolling off the hood of a car. When placed in one spot, it rolls one way; placed one millimeter to the right or left of that spot, it rolls in a different direction altogether. Where the ball ends up depends entirely upon where we place it initially. The impact of the initial conditions has been named the “butterfly effect,” since, in the chaotic theory of weather, the beating of a butterfly’s wings in Asia can cause a hurricane in the southern Atlantic months later. Our lives evolve from our own butterfly effects. The tiniest perturbations in our youths, our “initial conditions,” generate profound alterations in our later lives. In my case, I had wanted to be a computer scientist, but no openings in my freshman computer-science courses existed. If I had jumped one or two places ahead in the registration line, I would have made it into freshman comp sci and never become a physician.

If I had jumped one or two places ahead in the registration line, I would have made it into freshman comp sci and never become a physician. What delayed my arrival at the registration office? I don’t remember—stopping for a hamburger, maybe, or speaking to a friend—but whatever this long-forgotten event was, it changed my life. If I could have taken cardiac surgery, as I had wanted, I would probably be one of the “best in the chest” now, and not a brain surgeon. The butterfly effect: a conversation here, a missed flight there…happenings which redirect the rivers of our lives. After buffeting about in the chaotic currents, I feared that I had been cast onto a distant shore, a place where I didn’t belong. Three months into my new practice, a seventy-year-old widow named Grace Catalano came to my office, pushed along in a wheelchair by her burly son. She had suffered from back and leg pains for years.


pages: 257 words: 80,100

Time Travel: A History by James Gleick

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Ada Lovelace, Albert Einstein, Albert Michelson, Arthur Eddington, augmented reality, butterfly effect, crowdsourcing, Doomsday Book, index card, Isaac Newton, John von Neumann, luminiferous ether, Marshall McLuhan, Norbert Wiener, pattern recognition, Richard Feynman, Richard Feynman, Schrödinger's Cat, self-driving car, Stephen Hawking, telepresence, wikimedia commons

In the event, a feckless time-tourist steps on a butterfly: “an exquisite thing, a small thing that could upset balances and knock down a line of small dominoes and then big dominoes and then gigantic dominoes, all down the years across Time.” The butterfly effect, though, is a matter of potential only. Not every flutter in the air leaves its mark on the ages. Most fade to nothing, damped by viscosity. That was Asimov’s assumption in The End of Eternity: that the effects of tampering with history tend to die out as the centuries pass, perturbations extinguished by friction or dissipation. His Technician confidently explains: “Reality has a tendency to flow back to its original position.” But Bradbury was right and Asimov was wrong. If history is a dynamical system, it’s surely nonlinear, and the butterfly effect must obtain. At some places, some times, a slight divergence can transform history. There are critical moments—nodal points.

.”*6 There are few happy endings, he found. It is often the writers of science fiction or “speculative fiction” who give us, not only the weirdest, but the most rigorously analyzed approaches to the working of history. It all might have been different. For want of a nail, the kingdom was lost. I coulda been a contender. Regret is the time traveler’s energy bar. If only…something. Every writer nowadays knows about the butterfly effect. The slightest flutter might alter the course of great events. A decade before the meteorologist and chaos theorist Edward Lorenz chose the butterfly for illustrative purposes, Ray Bradbury deployed a history-changing butterfly in his 1952 story “A Sound of Thunder.” Here the time machine—the Machine, a vague mess of “silver metal” and “roaring light”—carries paying sightseers on Time Safaris back to the era of the dinosaurs.


pages: 317 words: 100,414

Superforecasting: The Art and Science of Prediction by Philip Tetlock, Dan Gardner

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Affordable Care Act / Obamacare, Any sufficiently advanced technology is indistinguishable from magic, availability heuristic, Black Swan, butterfly effect, cloud computing, cuban missile crisis, Daniel Kahneman / Amos Tversky, desegregation, Edward Lorenz: Chaos theory, forward guidance, Freestyle chess, fundamental attribution error, germ theory of disease, hindsight bias, index fund, Jane Jacobs, Jeff Bezos, Mikhail Gorbachev, Mohammed Bouazizi, Nash equilibrium, Nate Silver, obamacare, pattern recognition, performance metric, place-making, placebo effect, prediction markets, quantitative easing, random walk, randomized controlled trial, Richard Feynman, Richard Feynman, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, Saturday Night Live, Silicon Valley, Skype, statistical model, stem cell, Steve Ballmer, Steve Jobs, Steven Pinker, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Watson beat the top human players on Jeopardy!

If the clock symbolizes perfect Laplacean predictability, its opposite is the Lorenzian cloud. High school science tells us that clouds form when water vapor coalesces around dust particles. This sounds simple but exactly how a particular cloud develops—the shape it takes—depends on complex feedback interactions among droplets. To capture these interactions, computer modelers need equations that are highly sensitive to tiny butterfly-effect errors in data collection. So even if we learn all that is knowable about how clouds form, we will not be able to predict the shape a particular cloud will take. We can only wait and see. In one of history’s great ironies, scientists today know vastly more than their colleagues a century ago, and possess vastly more data-crunching power, but they are much less confident in the prospects for perfect predictability.

In my EPJ research in the late 1980s, I had the experts forecast whether the Communist Party would remain in power in the Soviet Union, whether there would be a violent overthrow of apartheid in South Africa, and whether Quebec would separate from Canada. After the deadlines for three forecasts passed, and the correct answers were clear—no, no, and no—I asked the experts to consider the plausibility of counterfactual scenarios, in which small butterfly-effect tweaks caused history to unfold differently. When the what-iffery implied that their failed forecast would have turned out right—for example, if the coup against Gorbachev in 1991 had been better planned and the plotters had been less drunk and better organized, the Communist Party would still be in power—the experts tended to welcome the what-if tale like an old friend. But when the scenarios implied that their correct forecast could easily have turned out wrong, they dismissed it as speculative.

Misinterpretations of “30% rain tomorrow” include (a) it will rain 30% of the time tomorrow); (b) it will rain on 30% of the landmass of Berlin; (c) 30% of weather forecasters predict rain. The correct interpretation is much harder to wrap our heads around: when meteorologists quantify the weather conditions around Berlin right now and plug in their best models, the equations assign a 30% probability to rain tomorrow. Or another way to look at it, using Lorenzian computer simulations: if we could rerun the weather in Berlin thousands of times, with minor butterfly-effect tweaks for measurement error in antecedent conditions like winds and barometric pressures, it would rain in 30% of the computer-simulated worlds. Small wonder that Berliners resort to more concrete simplifications. 12. David Leonhardt, “How Not to Be Fooled by Odds,” New York Times, October 15, 2014. 13. Robert Rubin, in discussion with the author, June 28, 2012. 14. William Byers, The Blind Spot: Science and the Crisis of Uncertainty (Princeton, NJ: Princeton University Press, 2011), p. vii. 15.


pages: 239 words: 68,598

The Vanishing Face of Gaia: A Final Warning by James E. Lovelock

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Ada Lovelace, butterfly effect, carbon footprint, Clapham omnibus, cognitive dissonance, continuous integration, David Attenborough, decarbonisation, discovery of DNA, Edward Lorenz: Chaos theory, Henri Poincaré, mandelbrot fractal, megacity, Northern Rock, oil shale / tar sands, phenotype, planetary scale, short selling, Stewart Brand, University of East Anglia

The first indication that this was too good to be true came in 1890 when Henri Poincaré studied the interaction of three bodies held together by gravity while orbiting in space; he found that the behaviour of the system was wholly unpredictable. This was a serious flaw in the concept of determinism, but it was not until 1961 that Lorenz used an early computer to demonstrate the chaotic behaviour of weather and found it to be wholly unpredictable beyond about a week. He was the originator of the ‘butterfly effect’ – the idea that the small eddy made by the flapping of a butterfly’s wings could initiate much later a hurricane; he showed that this was because weather systems are highly sensitive to the initial conditions of their origin. May found that computer models of population growth showed similar chaotic behaviour, especially in biological systems containing more than two species; these discoveries stirred great interest among mathematicians and scientists in the nature of deterministic chaos.

Norton, New York, 1988) James Lovelock, Gaia: The Practical Science of Planetary Medicine (1991), reprinted as Gaia: Medicine for an Ailing Planet (Gaia Books, London, 2005) James Lovelock, Homage to Gaia: The Life of an Independent Scientist (Oxford University Press, 2000) Index bold numbers refer to tables, italic numbers to figures adaptation 48, 49, 104 aerosol, atmospheric 35–8, 40 agribusiness 9, 86, 144, 146 agriculture, greenhouse gas 47 albedo, reduction of 46, 47, 163 algae 29, 33, 163 CLAW hypothesis 111, 116 ocean fertilization 98 Amsterdam Declaration 117, 165 Andreae, Meinrat 36, 94, 111, 116 anti-nuclear propaganda 70–76 Arctic, loss of ice 7, 10–11, 28 Bali, UN Climate Change Conference 4, 16, 47 belief, anecdotal 52–3, 73 Betts, Richard 38, 42 Bhopal industrial accident 72–3 biodiversity 115 biofuel crops 12–13 biogeochemistry 31, 121 biologists, and Gaia 119 Bolin, Bert 3, 120 Brand, Stewart 79, 111 Branson, Sir Richard 2 breathing, greenhouse gas emissions 47 British Antarctic Survey 42 Broecker, Wally, Fixing Climate 11, 97 Brown, Gordon 90 ‘butterfly effect’ 132 C4 plants 155 Caldeira, Ken 94, 95, 110, 112 Campaign for Nuclear Disarmament (CND) 74, 146 carbon dioxide burial 77, 96 effect on model Earth 34–5 and energy production 69 Eocene increase 101–2 production by population 47 reduction of 32, 33 regulation 108–10, 112 removal by algae 29, 33, 98 sequestration 96–9 carbon footprint 18, 48 carbon trading 48, 50 Carson, Rachel 143–5 CFCs 137, 145 chaos, deterministic 132–3, 164 Chapman Conferences 120 char, burial 58, 99–100 Charlson, Robert 15, 36, 38, 94, 111, 116 Chernobyl nuclear accident 71, 72–3 China, pollution 37 CLAW hypothesis 111, 116 climatologists, and Gaia 120 clouds artificial 95–6 CLAW hypothesis 111, 116 condensation nuclei 95, 111 effect on climate 35–8 coal 79, 83 combined heat and power generation 79 Common Agricultural Policy 90 Common Energy Policy 90 computers 130 Connes, Janine 107 Connes, Pierre 107 Cool Earth 97 Coombe Mill 136–43 ecosystem 139 grass-burning boiler 138 horticulture 140 tree planting 139 countryside, destruction of 9, 144 Cox, Peter 36, 42 Crane, Robert, The Earth System 110 Crichton, Michael, A State of Fear 147 Crutzen, Paul 94, 95 Daisyworld model 111, 112–14, 115 Dale, Sir Henry 15 Daniel, Billy 143 Darwinism 6, 31, 115, 119, 127–8, 131 Dasgupta, Sir Partha 5 Dawkins, Richard 111, 128, 153 DDT 147 Descartes, René 127, 130, 131, 158–9 deserts, solar thermal energy 66–7 determinism 132–3 Dickinson, Robert 42 dimethyl sulphide 98, 111, 116 disequilibrium 107, 112 dissonance, cognitive 25, 44 Doolittle, Ford 111 drought 10, 54–5 Dyke, James 115 Earth ageing 154 atmosphere 105, 107, 111–12 catastrophes 52, 152–3, 154 effect of carbon dioxide 34–5 hot state 2, 4, 34, 35, 118 human carrying capacity 56 as living system 7, 8–9, 47, 62, 165, 166 surface temperature 39 eco-warriors 21 Ehrlich, Ann 49 Ehrlich, Paul 49 electricity dependence on 16, 17, 88–9 production 65, 68 Electron Capture Detector (ECD) 145 energy 64–86 and political power 75–6 renewable 12, 80–85, 142 Eocene, climate 101–2, 104 Erikson, Brent 13 European Union, renewable energy policy 90 evapotranspiration 37, 38 evolution, Darwinian 6, 31, 115, 119, 127–8, 131 extremophiles 155 Farman, Joseph 42 feedback 167–8 climate models 34, 35, 100–101 ecosystems 38 Fells, Professor Ian 65 Festiger, Leon 25 fire 149–51 Flannery, Timothy 128 The Weather Makers 19 flooding 50 food production, greenhouse gas 47 supply 86–91 synthesized 16, 87, 100 forecasting climate change 23–45 forests clearance 97 evapotranspiration 38 fossil fuels 64, 77–80 Gaia naming by William Golding 1, 106, 128–9 perception of 126–7 see also Earth, as living system Gaia Theory, history 105–22, 166 Gardiner, Brian 42 Garrels, Robert 110 gas, natural 78–9, 83 genes, ‘selfish’ 153 geochemistry 108–10 geoengineering 92–104 Geological Society of London, 2003 Wollaston Medal 120 geologists, and Gaia 110, 119 geophysics 32 geophysiology 31, 100–102 global dimming 36, 102 Golding, William 1, 106, 128–9 Goodell, Jeff 80 Gore, Al 4, 15, 128 Gray, John 6 green ideology 12, 142–7 greenhouse condition 33, 101, 166 greenhouse gas 4, 47 Greenpeace 20, 74, 146 Greenspan, Alan 5 Hadley Centre for Climate Prediction and Research 36, 38, 42 Hamilton, William 115, 128, 153 Hansen, James 3, 5, 15 carbon dioxide reduction 32 scientific reticence 74 Hardin, Garrett 62 Harvey, Inman 115 Hayes, P.

Rethinking Money: How New Currencies Turn Scarcity Into Prosperity by Bernard Lietaer, Jacqui Dunne

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3D printing, agricultural Revolution, Albert Einstein, Asian financial crisis, banking crisis, Berlin Wall, BRICs, business climate, business process, butterfly effect, carbon footprint, Carmen Reinhart, clockwork universe, collapse of Lehman Brothers, complexity theory, conceptual framework, credit crunch, discounted cash flows, en.wikipedia.org, Fall of the Berlin Wall, fear of failure, fiat currency, financial innovation, Fractional reserve banking, full employment, German hyperinflation, happiness index / gross national happiness, job satisfaction, Marshall McLuhan, microcredit, mobile money, money: store of value / unit of account / medium of exchange, more computing power than Apollo, new economy, Occupy movement, price stability, reserve currency, Silicon Valley, the payments system, too big to fail, transaction costs, trickle-down economics, urban decay, War on Poverty, working poor

It would be some two centuries later, with the development of computers with massive computational prowess, until equations that would have taken a stadium full of people working for hundreds of years to solve could be solved in a matter of seconds. Relatively precise solutions to the three-body problem were demonstrated. A new field known by various names, including nonlinear dynamics, fractals, chaos, or complexity theory, began to emerge. The concept of the butterfly effect, whereby a flutter of a butterfly wing might cause a massive change in the weather countries away, became common knowledge. In short, it was now understood that everything affects everything else in multifaceted, often unpredictable ways. The critical middle, the stuff in between, as it were, is the infinite complexity of systems that are totally interactive, interconnected, and interdependent.

See Business cycle Boulder Gaian, 113 Brazilian Network of Community Development Banks (CDB), 107 Bridge financing, 121 Bristol Credit Union, 114 Bristol Pound (BP), 114–115 Brixton pound, 75 Brünningsche Notverordnungen, 179 Bubble, 33 Bullion, 27, 113. See also Gold standard Burden of expectations, 19 Bureaucracy, 108, 126–127 Burnout, 194 Business cycle, 51; bank debt amplifying, 52; Terra and, 134 Business-to-business system, 5 Bust. See Business cycle Bus token, 141–143 Butterfly effect, 31 Capitalism, 4, 22. See also Competition Capivari, 109 Carbon-backed currency, 116, 137, 201 Carbon premium exchange (CPX), 116–117 Carebank, 84– 85 Cash crunch, 148–149 Cell phone. See Mobile phone Central bank: bank debt and, 2, 40– 41; Brazil, 107; business cycle and, 52; Swedish, 25–26, 35– 36 CEO turnover, 217 Chance, 31– 32 Chaord, 192 Chaos, 31 Charity, 150 Chicago Plan, 3, 69–71, 231n15, 231n16 Chicago School of Economics, 35 Chiemgauer, 74–75, 87– 89, 88 Child welfare, 80 Civic, 146–148; in Mae Hong Son, 205; nonprofits and, 162 Civil society, 224 Civil unrest, 145–146, 181–182, 192–193 Class, 18; bridging, 83; investing, 193–194; in krama, 190; merchant, 2; middle, 2, 50, 75, 216; underclass, 216; upper, 29, 50.


pages: 289 words: 113,211

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber

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affirmative action, Albert Einstein, asset allocation, backtesting, Black Swan, Black-Scholes formula, Bonfire of the Vanities, butterfly effect, commodity trading advisor, computer age, disintermediation, diversification, double entry bookkeeping, Edward Lorenz: Chaos theory, family office, financial innovation, fixed income, frictionless, frictionless market, George Akerlof, implied volatility, index arbitrage, Jeff Bezos, London Interbank Offered Rate, Long Term Capital Management, loose coupling, margin call, market bubble, market design, merger arbitrage, Mexican peso crisis / tequila crisis, moral hazard, new economy, Nick Leeson, oil shock, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk/return, Robert Shiller, Robert Shiller, rolodex, Saturday Night Live, shareholder value, short selling, Silicon Valley, statistical arbitrage, The Market for Lemons, time value of money, too big to fail, transaction costs, tulip mania, uranium enrichment, yield curve, zero-coupon bond

Based on observations made by Edward Lorenz in the early 1960s and popularized by the so-called butterfly effect—the fanciful notion that the beating wings of a butterfly could change the predictions of an otherwise perfect weather forecasting system—this limitation arises because in some important cases immeasurably small errors can compound over time to limit prediction in the larger scale. Half a century after the limits of measurement and thus of physical knowledge were demonstrated by Heisenberg in the world of quantum mechanics, Lorenz piled on a result that showed how microscopic errors could propagate to have a stultifying impact in nonlinear dynamic systems. This limitation could come into the forefront only with the dawning of the computer age, because it is manifested in the subtle errors of computational accuracy. The essence of the butterfly effect is that small perturbations can have large repercussions in massive, random forces such as weather.

This is a point made by John Danaher in the introduction to Brazilian JiuJitsu: Theory and Technique, by Renzo Gracie and Royler Gracie with Kid Peligro and John Danaher (Montpelier, VT: Invisible Cities Press, 2001). 270 bindex.qxd 7/13/07 2:44 PM Page 271 INDEX Accidents/organizations, 159–161 Accountants, failure (reasons), 135 Accounting conventions, problems, 138 Accounting orientation, 137–138 Adaptation, best measure, 232–233 Adverse selection, 191–192 American depositary receipts (ADRs), 68 America Online (AOL), 139 Amex Major Market Index (XMI) futures, 12 Analytically driven funds, 248 Analytical Proprietary Trading (APT), 44–45 initiation, 189 remnant, form, 190 A Programming Language (APL), 43–47 asset, problem, 45 Armstrong, Michael, 130 Arthur Andersen, failure, 135 Artificial markets, 229 Asia Crisis (1997), 3, 115 Asian currency crisis, 114 Asian economies, 118 Asia-Pacific Economic Cooperation (APEC), 63 Assets class, hedge fund classification, 245 direction, hedge fund classification, 246 Asynchronous pricing, 225 AT&T Wireless Services IPO, SSB underwriting, 130 Back-office functions, 39 Bacon, Louis, 165 Bamberger, Gerry, 185–187, 251 Bankers Trust lawsuit, 38 purchase announcement, 75 Bank exposure, 146–147 Bank failures, 146 Bank of Japan, objectives/strategies, 166 Baptist Foundation, restatements/liability, 135 Barings (bank) bankruptcy, 39 clerical trading error, 38–39 derivatives cross-trading, 143 Beard, Anson, 13 Beder, Tanya, 204 Behavior, economic theory, 231 Berens, Rod, 73 Bernard, Lewis, 42, 52 Biggs, Barton, 11 Black, Fischer, 9 Black Monday (1929), 17 Black-Scholes formula, 9, 252 Block desk, 184–185 trading positions, 186 Bond positions, hedging, 30 Booth, David, 29 Breakdowns, explanation, 5–6 Broker-dealer block-trading desk, usage, 184 price setting role, 213–214 Bucket shop era, 177 Buffett, Warren, 62, 99, 181, 198 arb unit closure, 87–88 Bushnell, Dave, 129–131 Butterfly effect, essence, 227 Capital cushions, 106 Capitalism, 250 Cash futures, 251 arbitrageurs, 19, 23 spread, 19 trade, 19 Cerullo, Ed, 41 Cheapest-to-deliver bond, 251 Chicago Board Options Exchange (CBOE), 252 Black-Scholes formula, impact, 9–10 Citigroup Associates First Capital Corporation, 128 consolidation, impact, 132–134 Japanese private banking arm, 133 management change, Fed reaction, 133 organizational complexity/structural uncertainty, 126 Citron, Robert, 38 Coarse behavior benefits, 232–233 consistency, 236–237 271 bindex.qxd 7/13/07 2:44 PM Page 272 INDEX Coarse behavior (Continued) decision rules, 233 in humans, 235–237 measurement of, 238–239 response based on, 236 rules, optimality, 238 Cockroach example, 232–233, 235 Collateral, usage, 218 Collateralized mortgage obligations (CMOs), 71–75, 250 Commercial Credit, Primerica purchase, 126 Competitive prices, 36 Complexity by-product, 143 implications, 156 importance, 144–146 Consumer lending violations, Federal Reserve fine, 132 Control-oriented risk management, 200 Convergence Capital, 80 Convergence trades, 122 Convertible bond (CB) strategy, 57–58 Cooke, Bill, 185–187 Corporate defaults, possibility, 29–30 Corporate political risk, 140 Corrigan, Gerald, 196–198 Countervailing trades, 213 Credit Suisse First Boston, 72–73 Crises, causes, 240 da Vinci, Leonardo, 136 Denham, Bob, 62–63, 99, 195 Derivatives customization, 143 trading strategy, 30 Deterministic nonperiodic flow, 228 Detroit Edison, Fermi-1 experimental breeder reactor, 161–164 Deutsche Bank, investment banking (problems), 72–73 Dimon, Jamie, 77–78, 91, 97–98, 126 Distressed debt, event risk, 248–249 Dow Jones Industrial Average (DJIA), 2, 12 Dynamic hedge, 12, 161 Dynamic system, 228–229 Ebbers, Bernard, 70 Economic catastrophe, 257 Efficient markets hypothesis, 211 Einstein, Albert, 224–226 Emerging market bonds, 71 Enron restatements/liability, 135 U.S.


pages: 397 words: 110,130

Smarter Than You Think: How Technology Is Changing Our Minds for the Better by Clive Thompson

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3D printing, 4chan, A Declaration of the Independence of Cyberspace, augmented reality, barriers to entry, Benjamin Mako Hill, butterfly effect, citizen journalism, Claude Shannon: information theory, conceptual framework, corporate governance, crowdsourcing, Deng Xiaoping, discovery of penicillin, Douglas Engelbart, Edward Glaeser, en.wikipedia.org, experimental subject, Filter Bubble, Freestyle chess, Galaxy Zoo, Google Earth, Google Glasses, Henri Poincaré, hindsight bias, hive mind, Howard Rheingold, information retrieval, iterative process, jimmy wales, Kevin Kelly, Khan Academy, knowledge worker, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Netflix Prize, Nicholas Carr, patent troll, pattern recognition, pre–internet, Richard Feynman, Richard Feynman, Ronald Coase, Ronald Reagan, sentiment analysis, Silicon Valley, Skype, Snapchat, Socratic dialogue, spaced repetition, telepresence, telepresence robot, The Nature of the Firm, the scientific method, The Wisdom of Crowds, theory of mind, transaction costs, Vannevar Bush, Watson beat the top human players on Jeopardy!, WikiLeaks, X Prize, éminence grise

“You’re looking, and you realize, ‘This doesn’t have to be that way,’” as Stevens puts it. For her part, Barnard says her hours of playing with the map led her to a surprising epiphany: It’s actually easier to make a gerrymandered map than a fair one. Unbalanced districts aren’t purely a result of greed and deceit. Even honest-minded attempts to alter a district can produce unexpectedly bad results, in a butterfly effect. You might try to make district A more fair by siphoning off households from district B, only to find it inadvertantly makes districts C and D and F more gerrymandered. It was a nuanced political analysis that stemmed from hands-on experience instead of abstraction. I ask Barnard how long it would have taken her to redistrict the state if she hadn’t had the software. What if she’d had to do it like in the old days—with pencil and paper, and stacks of population tables?

Or you could pick a seemingly simple instruction—go forward ten steps, turn right ninety degrees, increase the number of steps by five, then repeat over and over—and discover it produced something unexpected: a square spiral, growing eternally larger. The children began to grasp the concept of recursion, the idea that complexity emerges from repeating a simple procedure over and over. They also began to intuit the butterfly effect: how changing one tiny part of a program can radically alter the outcome. If you tweak one element in that square-spiral program, making the angle ninety-five degrees instead of ninety, surprise: The squares will shift slightly, producing a new creation, looking like a spiral galaxy. And ninety-seven degrees looks different, too. This idea—that very small alterations can produce wildly different results—is something that many adults often fail to grasp, leading to massive failures in corporations, governments, teams, and families: The people at the top think that making a little change won’t make much difference, but that little change spirals out of control.

See also attention/focus; cognition; memory and problem-solving, 72 understanding, limits of, 14–15 brainstorming, 164 Brandt, Deborah, 50–52 Breaking Bad (TV show), 94–95, 102 Bridle, James, 70–71 Briggs, Charles F., 6 Briggs, Henry, 59 Brown, John Seely, 195 Building Maker, 171 Bürgi, Joost, 59 Burt, Dorothy, 184–86 Bush, Vannevar, 123, 143 butterfly effect, 191 Buxton, Arthur, 92 Cadwell, Courtney, 181–83 Capablanca, José Raúl, 3 Carmichael, Alexandra, 90 Carpenter, Matthew, 175–76 Carr, Nicholas, 12, 14, 136 “Cartoons Against Corruption,” 275 Carvin, Andy, 214–15 Cassiopedia, 260 Ceglowski, Maciej, 154–55 centaur, 3–6, 284 Cha, Meeyoung, 234–35 Chain, Ernest, 64 Change.org, 265 “Character of a Coffee-House,” 223 Cheever, Charlie, 74–75 chess Deep Blue supercomputer, 1–2, 5, 9–10, 280, 284 human/machine collaboration, 3–5, 284 humans versus machines, 1–6, 16 improving game and digital tools, 17–18 Kasparov versus online collective, 161–62 children.


pages: 327 words: 103,336

Everything Is Obvious: *Once You Know the Answer by Duncan J. Watts

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affirmative action, Albert Einstein, Amazon Mechanical Turk, Black Swan, butterfly effect, Carmen Reinhart, Cass Sunstein, clockwork universe, cognitive dissonance, collapse of Lehman Brothers, complexity theory, correlation does not imply causation, crowdsourcing, death of newspapers, discovery of DNA, East Village, easy for humans, difficult for computers, edge city, en.wikipedia.org, Erik Brynjolfsson, framing effect, Geoffrey West, Santa Fe Institute, happiness index / gross national happiness, high batting average, hindsight bias, illegal immigration, interest rate swap, invention of the printing press, invention of the telescope, invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, Joseph Schumpeter, Kenneth Rogoff, lake wobegon effect, Long Term Capital Management, loss aversion, medical malpractice, meta analysis, meta-analysis, Milgram experiment, natural language processing, Netflix Prize, Network effects, oil shock, packet switching, pattern recognition, performance metric, phenotype, planetary scale, prediction markets, pre–internet, RAND corporation, random walk, RFID, school choice, Silicon Valley, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, too big to fail, Toyota Production System, ultimatum game, urban planning, Vincenzo Peruggia: Mona Lisa, Watson beat the top human players on Jeopardy!, X Prize

Rather, when people tend to like something that other people like, differences in popularity are subject to what is called cumulative advantage, meaning that once, say, a song or a book becomes more popular than another, it will tend to become more popular still. Over the years, researchers have studied a number of different types of cumulative advantage models, but they all have the flavor that even tiny random fluctuations tend to get bigger over time, generating potentially enormous differences in the long run, a phenomenon that is similar to the famous “butterfly effect” from chaos theory, which says that a butterfly fluttering its wings in China can lead to a hurricane months later and oceans away.14 As with Granovetter’s model, cumulative advantage models have disruptive implications for the kinds of explanations that we give of success and failure in cultural markets. Commonsense explanations, remember, focus on the thing itself—the song, the book, or the company—and account for its success solely in terms of its intrinsic attributes.

The U.S. economy, for example, is the product of the individual actions of millions of people, as well as hundreds of thousands of firms, thousands of government agencies, and countless other external and internal factors, ranging from the weather in Texas to interest rates in China. Modeling the trajectory of the economy is therefore not like modeling the trajectory of a rocket. In complex systems, tiny disturbances in one part of the system can get amplified to produce large effects somewhere else—the “butterfly effect” from chaos theory that came up in the earlier discussion of cumulative advantage and unpredictability. When every tiny factor in a complex system can get potentially amplified in unpredictable ways, there is only so much that a model can predict. As a result, models of complex systems tend to be rather simple—not because simple models perform well, but because incremental improvements make little difference in the face of the massive errors that remain.


pages: 378 words: 110,518

Postcapitalism: A Guide to Our Future by Paul Mason

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Alfred Russel Wallace, bank run, banking crisis, banks create money, Basel III, Bernie Madoff, Bill Gates: Altair 8800, bitcoin, Branko Milanovic, Bretton Woods, BRICs, British Empire, business process, butterfly effect, call centre, capital controls, Claude Shannon: information theory, collaborative economy, collective bargaining, Corn Laws, corporate social responsibility, credit crunch, currency manipulation / currency intervention, currency peg, David Graeber, deglobalization, deindustrialization, deskilling, discovery of the americas, Downton Abbey, en.wikipedia.org, energy security, eurozone crisis, factory automation, financial repression, Firefox, Fractional reserve banking, Frederick Winslow Taylor, full employment, future of work, game design, income inequality, inflation targeting, informal economy, Internet of things, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kevin Kelly, knowledge economy, knowledge worker, late capitalism, low skilled workers, market clearing, means of production, Metcalfe's law, money: store of value / unit of account / medium of exchange, mortgage debt, Network effects, new economy, Norbert Wiener, Occupy movement, oil shale / tar sands, oil shock, payday loans, post-industrial society, precariat, price mechanism, profit motive, quantitative easing, race to the bottom, RAND corporation, rent-seeking, reserve currency, RFID, Richard Stallman, Robert Gordon, secular stagnation, sharing economy, Stewart Brand, structural adjustment programs, supply-chain management, the scientific method, The Wealth of Nations by Adam Smith, Transnistria, union organizing, universal basic income, urban decay, urban planning, wages for housework, women in the workforce

Calculated using 2014 minimum wage of 5300 tk, against retail price rise of 34 tk per kg. 12. In this section I am following the outline of the theory as presented in A. Kliman, Reclaiming Marx’s ‘Capital’: A Refutation of the Myth of Inconsistency (Plymouth, 2007) 13. http://www.Icddrb.org/who-we-are/gender-issues/daycare 14. K. Allen, ‘The Butterfly Effect: Chinese Dorms and Bangladeshi Factory Fires’, Financial Times, 25 April 2013, http://blogs.ft.com/ftdata/2013/04/25/the-butterfly-effect-chinese-dorms-and-bangladeshi-factory-fires/? 15. J. Robinson, Economic Philosophy (Cambridge, 1962) 16. A. Einstein, ‘Physics and Reality’, Journal of The Franklin Institute, vol. 221 (1936), pp. 349–82 17. OECD, ‘Education at a Glance 2014: OECD Indicators’, OECD, 2014, p. 14 18. L. Walras, Elements of Pure Economics: Or the Theory of Social Wealth (London, 1900), p. 399 19. http://library.mises.org/books/William%20Smart/An%20Introduction%20to%20the%20Theory%20of%20Value.pdf 20.


pages: 338 words: 106,936

The Physics of Wall Street: A Brief History of Predicting the Unpredictable by James Owen Weatherall

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Albert Einstein, algorithmic trading, Antoine Gombaud: Chevalier de Méré, Asian financial crisis, bank run, Benoit Mandelbrot, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, Brownian motion, butterfly effect, capital asset pricing model, Carmen Reinhart, Claude Shannon: information theory, collateralized debt obligation, collective bargaining, dark matter, Edward Lorenz: Chaos theory, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial innovation, George Akerlof, Gerolamo Cardano, Henri Poincaré, invisible hand, Isaac Newton, iterative process, John Nash: game theory, Kenneth Rogoff, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, martingale, new economy, Paul Lévy, prediction markets, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk-adjusted returns, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, statistical arbitrage, statistical model, stochastic process, The Chicago School, The Myth of the Rational Market, tulip mania, V2 rocket, volatility smile

This observation, a result of one of the very first computer simulations in service of a scientific problem, contradicted every classical expectation regarding how things like weather worked. (Lorenz quickly showed that much simpler systems, such as pendulums and water wheels, things that you could build in your basement, also exhibited a sensitivity to initial conditions.) The basic idea of chaos is summed up by another accidental contribution of Lorenz’s: the so-called butterfly effect, which takes its name from a paper that Lorenz gave at the 1972 meeting of the American Association for the Advancement of Science called “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?” (Lorenz never took credit for the title. He claimed one of the conference organizers came up with it when Lorenz forgot to submit one.) Lorenz never answered the question asked in the title of his talk, but the implication was clear: a small change in initial conditions can have a huge impact on events down the road.

Silver City was a paradigm Western mining town”: This background on Silver City is from Wallis (2007). “. . . first developed by a man named Edward Lorenz”: The biographical and historical details concerning Lorenz and the history of chaos theory are from Gleick (1987) and Lorenz (1993). “. . . the work of two physicists named James Yorke and Tien-Yien Li . . .”: The article is Li and Yorke (1975). “. . . the so-called butterfly effect . . .”: The paper is Lorenz (2000). Lorenz never used the metaphor of a butterfly flapping its wings, though he sometimes used a similar metaphor involving a seagull. “. . . Farmer through reading A. H. Morehead . . .”: Farmer read Morehead (1967); Packard read Thorp (1966). “. . . where the ball lands is sensitive to the initial conditions . . .”: Although there is some controversy concerning just what should count as a truly chaotic system, virtually everyone would agree that roulette is not chaotic.


pages: 370 words: 97,138

Beyond: Our Future in Space by Chris Impey

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3D printing, Admiral Zheng, Albert Einstein, Alfred Russel Wallace, Berlin Wall, Buckminster Fuller, butterfly effect, California gold rush, carbon-based life, Colonization of Mars, cosmic abundance, crowdsourcing, cuban missile crisis, dark matter, discovery of DNA, Doomsday Clock, Edward Snowden, Elon Musk, Eratosthenes, Haight Ashbury, Hyperloop, I think there is a world market for maybe five computers, Isaac Newton, Jeff Bezos, John von Neumann, Kickstarter, life extension, Mahatma Gandhi, Mars Rover, mutually assured destruction, Oculus Rift, operation paperclip, out of africa, Peter H. Diamandis: Planetary Resources, phenotype, purchasing power parity, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Search for Extraterrestrial Intelligence, Searching for Interstellar Communications, Silicon Valley, skunkworks, Skype, Stephen Hawking, Steven Pinker, supervolcano, technological singularity, telepresence, telerobotics, the medium is the message, the scientific method, theory of mind, V2 rocket, wikimedia commons, X Prize, Yogi Berra

The Biospherians could in the end just open the door and go home—Moon and Mars colonists will have very few options. The problems of food production and oxygen loss are not inherent to bioregenerative systems; they were specific to the Biosphere design and can be corrected. Most of the problems encountered were unforeseen and some were unforeseeable. Complex, miniature ecosystems are subject to nonlinear effects that compound over time. Call it the butterfly effect. Since colonists won’t be able to live exclusively in a bubble, another crucial piece of equipment is a spacesuit. Spacesuits have changed very little since the 1960s; the Americans, Russians, and Chinese all use bulky and clunky suits that offer safety but limited mobility.9 A spacesuit has to deal with vacuum and temperature extremes; it has to protect against micrometeorites and infiltration by dust; it has to provide breathable air; and it has to monitor the occupant’s vital signs.

Frank, 188 behavioral b’s, 15 Bell X-1, 71 Bell, Alexander Graham, 78 Bell Labs, 153 Benford, Gregory, 223–24 Benford, James, 223–24 Bennett, Charles, 230 Bering Strait, land bridge across, 8, 120, 218 Berlin Rocket Society, 32 Berlin Wall, 41 Berners-Lee, Tim, 78–79 Bernoulli, Daniel, 68 Berserker series (Saberhagen), 177, 259 Bezos, Jeff, 103 Bible, 148–49 big bang theory, 131, 255 “Big Ear” telescope, 237 Bigelow, Robert, 102–3 binary stars, 126 biohackers (grinders), 207 biomarkers, 216–18 Biosphere 2 experiment, 192–97, 193, 285–86 black projects, 69–70, 72, 144 Blade Runner, 204, 208, 259 Blue Origin, 103 Boeing X-37, 72, 85 Bohr, Niels, 213, 288 Bostrom, Nick, 207, 245–47, 260–61 Bounty, HMS, 202 Bradbury, Ray, 164 brains: computer interfaces with, 205–7 human, 12–17, 203, 283 of orcas, 190 radiation damage to, 115 simulation of, 259–61 “brain in a vat” concept, 260 Branson, Holly and Sam, 89 Branson, Richard Charles Nicholas, 80, 86–89, 95, 97–98, 101–2, 106 Breakthrough Propulsion Physics, 290 Brezhnev, Leonid, 42 Brightman, Sarah, 102 Brin, Sergey, 275 British Airways, 87 British Interplanetary Society, 221 Brokaw, Tom, 74 Brother Assassin (Saberhagen), 177 Bryan, Richard, 238 buckyballs, 151, 231 Buddhism, 20, 267 Bulletin of the Atomic Scientists, 197 Buran, 72 Burnett, Mark, 75 Burroughs, Edgar Rice, 164 Burrows, William, 35–36 Bush, George W., administration of, 93 Bussard, Robert, 222 butterfly effect, 195 By Rocket into Interplanetary Space (Oberth), 31 California, population dispersion into, 8 California, University of: at Irvine, 112, 223 at Los Angeles, 78 Calvin, William, 15 camera technology, 53, 176–77, 205 Cameron, James, 92, 120, 176 Canada, 142 canals, on Mars, 163 canards, 82–83 cancer, 180 cannonball, Newton’s experiment with, 25, 267 cannons: acceleration force of, 26 smooth-bore, 24 carbon, 172 in nanotechnology, 151–52, 182 as requirement for life, 123–24, 256 carbon dioxide, 132, 171, 172–73, 182, 193–94, 196, 218, 278 carbon nanotubes, 151–52 carbyne, 152 Cassini spacecraft, 52–53, 125, 182 Castro, Fidel, 41 casualties, early Chinese, 22 cataracts, 115 cats, 48–49, 251 causality principle, 230–31 cave paintings, 15 celestial property rights, 145–47 Center for Strategic and International Studies (CSIS), 158 centrifuges, 114 Cerf, Vinton, 67 Chaffee, Roger, 43 Challenger, explosion of, 55–56, 56, 74, 107, 271 Chang’e 3 lunar probe, 143, 162 chemical fuels, 219–21, 220 chickens, research using, 26 chimpanzees, 14 genetic diversity of humans vs., 202 China: as averse to innovation, 109 in early attempts at space travel, 21–22, 22, 68, 139, 141 population dispersion into, 7 revolution in, 141 rocket development in, 23–24, 113 space program of, 139–44, 140, 161, 162, 195, 276 US relations with, 144 Christian, Fletcher, 202 Christianity, 20 Chuansheng Chen, 11 civilization: Type I, 253, 254, 257 Type II, 253–54, 254, 257 Type III, 253, 254, 257 Type IV, 253, 254, 255 Clarke, Arthur C., 149–50, 164, 185, 201, 252 climate change, 197–98, 286 Clinton, Bill, 154 cloning, 251 Clynes, Manfred, 205 Cocconi, Giuseppe, 187 Colbert, Stephen, 74, 117 Cold War, 35–39, 41–43, 50, 55, 73, 76, 139, 145, 197 Columbia, disintegration of, 55, 56, 107 Columbia Accident Investigation Board Report, 107 Columbus, Christopher, 243 comets, 183 Commercial Orbital Transportation Services (COTS), 275 Committee on the Peaceful Uses of Outer Space, 145 communication: with alien species, 52, 189, 234–35, 238, 239, 246, 253, 255, 259 by digital data transmission, 66–67, 77–80 latency and, 178 space technology in, 153–54 Compaq, 95 computation, future technology of, 258–62 confinement, psychological impact of, 169–70 Congress, US: legislation in, 78, 144 on space programs, 38, 41, 75, 156, 158 consciousness, simulation of, 259–61 conservation biology, 201 conspiracy theories, 238, 240 Constellation program, 104 Contact (film), 236–37, 242 Contact (Sagan), 236 contraception, 200 Copernicus, 19, 20, 127 Coriolis force, Coriolis effect, 152 cosmic rays, 115, 160, 160, 164, 167, 168, 204 cosmism, 27 cosmonauts, 141 disasters of, 108 records set by, 115 selection criteria for, 74 Cosmos 1, 184 cosmos, cosmology, ancient concepts of, 17–20 Cosmos Studios, 184 Cosmotheoros (Huygens), 163 counterfactual thinking, 14 Cronkite, Walter, 74 cryogenic suspension, 250–51 cryptobiosis, 123 cryptography, 231, 291 Cuban missile crisis, 41–42 CubeSat, 184–85 Cultural Revolution, Chinese, 141–42 Curiosity rover, 165, 167, 176, 181 cybernetics, 206–7 Cyborg Foundation, 288 cyborgs (cybernetic organisms), 204–8, 288 Cygnus capsule, 100 cytosine, 6 dark energy, 256 d’Arlandes, Marquis, 68 DARPANET, 78 Darwin, Charles, 265 “Darwin” (machine), 227 Death Valley, 118–19 deceleration, 222, 223 DeepSea Challenger sub, 120 deep space, 126–29 Defense Advanced Research Projects Agency (DARPA), 78, 224 Defense Department, US, 38, 78, 90, 153 De Garis, Hugo, 258 Delta rockets, 72, 113 Delta-V, 111 Democritus, 19 Destination Mir (reality show), 75 Diamandis, Peter, 90–94, 97–98, 147, 156 diamonds, 131, 231 Dick, Philip K., 204–5 Digital Equipment Corporation, 213 DNA, 6–7, 9, 19, 189, 202, 228, 251, 263, 265, 266 Do Androids Dream of Electric Sheep (Dick), 205 dogs: brains of, 13 in scientific research, 251 in space travel, 40, 47 Dolly (sheep), 251 Doomsday Clock, 197–98, 246, 286 dopamine, 10, 98 Doppler method, exoplanet detection and characterization by, 127, 128, 129, 130, 133, 215 Doppler shift, 127 Dora-Mittelbau concentration camp, 33 Downey, Robert, Jr., 95 drag, in flight, 68, 83, 223 Drake, Frank, 187–88, 235, 237 Drake equation, 188, 189, 233–35, 237, 241, 243, 244, 253, 291–92 DRD4 alleles, 7R mutation in, 10–12, 11, 15, 98 Drexler, Eric, 226 drones, 180–81 Druyan, Ann, 184 Duke, Charles, 45 Dunn, Tony, 225 Dyson, Freeman, 226–27, 253 Dyson sphere, 253–54, 254 Earth: atmosphere of, 8, 70–71, 70 early impacts on, 50, 172 geological evolution of, 172 as one of many worlds, 17–20 planets similar to, 122, 124–26, 129–33, 224, 235 projected demise of, 197–98 as round, 19 as suited for human habitation, 118–22, 121, 234 as viewed from space, 45, 53, 121, 185, 270 Earth Return Vehicle, 169 “Earthrise” (Anders), 270 Earth similarity index, 215–16 eBay, 79, 95 Economist, The, 105 ecosystem, sealed and self-contained, 192–97, 193, 285 Eiffel Tower, 27, 149 Einstein, Albert, 220, 228, 256 Eisenhower, Dwight D., 36–39, 73, 79 electric cars, 96 electric solar sails, 186 electromagnetic waves, 186 e-mail, 78 embryo transport, 251 Enceladus, 177, 182, 227 potential habitability of, 125, 278 Encyclopædia Britannica, 95, 283 Endangered Species Act (1973), 201 energy: aliens’ use of, 190 civilizations characterized by use of, 252–57, 254, 258 dark, 256 declining growth in world consumption of, 257 Einstein’s equation for, 220 production and efficiency of, 219–24, 220 as requirement for life, 123–24 in rocket equation, 110 Engines of Creation (Drexler), 226 environmental disasters, 245 environmental protection: as applied to space, 147 movement for, 45, 235, 263, 270 Epicureans, 18 Epsilon Eridani, 187 Eratosthenes, 19 ethane, 52, 125 Ethernet, 213 eukaryotes, 172 Euripides, 18 Europa, 52, 97–98 potential habitability of, 125, 125, 161, 278 Europa Clipper mission, 98 Europe: economic depression in, 28 population dispersion into, 7–8, 11, 15 roots of technological development in, 23–24 European Southern Observatory, 133 European Space Agency, 159, 178–79 European Union, bureaucracy of, 106 Eustace, Alan, 120, 272 Evenki people, 119–20 Everest, Mount, 120 evolution: genetic variation in, 6, 203, 265 geological, 172 of human beings, 16–17 off-Earth, 203–4 evolutionary divergence, 201–4 exoplanets: Earth-like, 129–33, 215–18 extreme, 131–32 formation of, 215, 216 incidence and detection of, 126–33, 128, 233 exploration: as basic urge of human nature, 7–12, 109, 218, 261–63 imagination and, 262–63 explorer gene, 86 Explorer I, 38 explosives, early Chinese, 21–23 extinction, 201–2 extraterrestrials, see aliens, extraterrestrial extra-vehicular activities, 179 extremophiles, 122–23 eyeborg, 205–6 Falcon Heavy rocket, 114 Falcon rockets, 96, 97, 101, 184 Federal Aviation Administration (FAA), 82, 93, 105–7, 154 Fédération Aéronautique Internationale, 272 Felix and Félicette (cats), 48–49 Fermi, Enrico, 239–41 Fermilab, 254 “Fermi question,” 240–41, 243 Feynman, Richard, 179–80, 230, 270, 280 F4 Phantom jet fighter, 82 51 Peg (star), 126, 133 55 Cancri (star), 131 F-117 Nighthawk, 69 fine-tuning, 256, 294 fire arrows, 23, 68 fireworks, 21–24, 31 flagella, 180 flight: first human, 68 first powered, 69 principles of, 67–73 stability in, 82–83 “Fly Me to the Moon,” 45 food: energy produced by, 219, 220 in sealed ecosystem, 194–95 for space travel, 115–16, 159, 170 Forward, Robert, 223 Foundation series (Asimov), 94 founder effect, 202–3 Fountains of Paradise, The (Clarke), 149 France, 48, 68, 90 Frankenstein monster, 206, 259 Fresnel lens, 223 From Earth to the Moon (Verne), 183 fuel-to-payload ratio, see rocket equation Fukuyama, Francis, 207 Fuller, Buckminster, 151, 192 fullerenes, 151 Futron corporation, 155 Future of Humanity Institute, 245 “futurology,” 248–52, 249 Fyodorov, Nikolai, 26, 27 Gagarin, Yuri, 40–41, 41, 66, 269 Gaia hypothesis, 286 galaxies: incidence and detection of, 235 number of, 255 see also Milky Way galaxy Galileo, 49–50, 183, 270 Gandhi, Mahatma, 147 Garn, Jake, 114 Garn scale, 114 Garriott, Richard, 92 gas-giant planets, 125, 126–29 Gauss, Karl Friedrich, 238 Gazenko, Oleg, 47 Gemini program, 42 Genesis, Book of, 148–49 genetic anthropology, 6 genetic code, 5–7, 123 genetic diversity, 201–3 genetic drift, 203 genetic engineering, 245, 249 genetic markers, 6–7 genetics, human, 6–7, 9–12, 120, 201–4 Genographic Project, 7, 265 genome sequencing, 93, 202, 292 genotype, 6 “adventure,” 11–12, 98 geocentrism, 17, 19–20, 49 geodesic domes, 192 geological evolution, 172 George III, king of England, 147 German Aerospace Center, 178 Germany, Germans, 202, 238 rocket development by, 28, 30–34, 141 in World War II, 30–35 g-forces, 46–49, 48, 89, 111, 114 GJ 504b (exoplanet), 131 GJ 1214b (exoplanet), 132 glaciation, 172 Glenn Research Center, 219 global communications industry, 153–54 Global Positioning System (GPS), 144, 153–54 God, human beings in special relationship with, 20 Goddard, Robert, 28–32, 29, 36, 76, 78, 81–82, 94, 268 Goddard Space Flight Center, 178 gods, 20 divine intervention of, 18 Golden Fleece awards, 238 Goldilocks zone, 122, 126, 131 Gonzalez, Antonin, 215 Goodall, Jane, 14 Google, 80, 92, 185, 272, 275 Lunar X Prize, 161 Gopnik, Alison, 10, 13 Grasshopper, 101 gravity: centrifugal force in, 26, 114, 150 in flight, 68 of Mars, 181, 203 Newton’s theory of, 25, 267 and orbits, 25, 114–15, 127, 128, 149–50, 267 in rocket equation, 110 of Sun, 183 waves, 255 see also g-forces; zero gravity Gravity, 176 gravity, Earth’s: first object to leave, 40, 51 human beings who left, 45 as obstacle for space travel, 21, 105, 148 as perfect for human beings, 118 simulation of, 168–69 Great Art of Artillery, The (Siemienowicz), 267 Great Britain, 86, 106, 206, 227 “Great Filter,” 244–47 Great Leap Forward, 15–16 “Great Silence, The,” of SETI, 236–39, 240–41, 243–44 Greece, ancient, 17–19, 163 greenhouse effect, 171, 173 greenhouse gasses, 132, 278 Griffin, Michael, 57, 147, 285–86 grinders (biohackers), 207 Grissom, Gus, 43 guanine, 6 Guggenheim, Daniel, 81, 268 Guggenheim, Harry, 81 Guggenheim Foundation, 30, 81–82, 268 gunpowder, 21–24, 267 Guth, Alan, 257 habitable zone, 122, 124–26, 130–31, 132, 188, 241, 246, 277–78, 286, 291 defined, 124 Hadfield, Chris, 142 hair, Aboriginal, 8 “Halfway to Pluto” (Pettit), 273 Hanson, Robin, 247 haptic technology, 178 Harbisson, Neil, 205, 288 Harvard Medical School, 90 Hawking, Stephen, 88, 93, 198, 259 HD 10180 (star), 127 Heinlein, Robert, 177 Heisenberg compensator, 229 Heisenberg’s uncertainty principle, 229–30 heliocentrism, 19 helium, 68 helium 3, 161–62 Herschel, William, 163 Higgs particle, 256 High Frontier, 146–47 Hilton, Paris, 88, 101–2 Hilton hotels, 145 Hinduism, 20 Hiroshima, 222 Hitler, Adolf, 32, 34 Hope, Dennis M., 145, 147 Horowitz, Paul, 237–38 hot Jupiters, 127–28, 130 Hubble Space Telescope, 56–57, 65, 218, 225 Huffington, Arianna, 92 human beings: as adaptable to challenging environments, 118–22 as alien simulations, 260–61, 260 creative spirit of, 73, 248 early global migration of, 5–12, 9, 11, 15, 19, 118, 120, 186, 202, 218, 262, 265 Earth as perfectly suited for, 118–22, 121 exploration intrinsic to nature of, 7–12, 109, 218, 261–63 first appearance of, 5, 15, 172, 234 impact of evolutionary divergence on, 201–4 as isolated species, 241–42 as lone intelligent life, 241, 243 merger of machines and, see cyborgs minimal viable population in, 201–2, 251 off-Earth, 203–4, 215, 250–52 requirements of habitability for, 122, 124–26, 129, 130–31 sense of self of, 232, 261 space as inhospitable to, 53–54, 114–17, 121, 123 space exploration by robots vs., 53–57, 66, 98, 133, 161, 177–79, 179, 208, 224–28 space travel as profound and sublime experience for, 45, 53, 117, 122 speculation on future of, 93, 94, 204, 207–8, 215, 244–47, 248–63, 249 surpassed by technology, 258–59 threats to survival of, 94, 207–8, 244–47, 250, 259–62, 286, 293 timeline for past and future of, 248–50, 249 transforming moment for, 258–59 Huntsville, Ala., US Space and Rocket Center in, 48 Huygens, Christiaan, 163 Huygens probe, 53 hybrid cars, 96 hydrogen, 110, 156, 159, 161, 187, 219, 222 hydrogen bomb, 36 hydrosphere, 173 hyperloop aviation concept, 95 hypothermia, 251 hypothetical scenarios, 15–16 IBM, 213 Icarus Interstellar, 224 ice: on Europa, 125 on Mars, 163–65, 227 on Moon, 159–60 ice ages, 7–8 ice-penetrating robot, 98 IKAROS spacecraft, 184 imagination, 10, 14, 20 exploration and, 261–63 immortality, 259 implants, 206–7 inbreeding, 201–3 India, 159, 161 inflatable modules, 101–2 inflation theory, 255–57, 255 information, processing and storage of, 257–60 infrared telescopes, 190 Inspiration Mars, 170–71 Institute for Advanced Concepts, 280 insurance, for space travel, 106–7 International Academy of Astronautics, 152 International Geophysical Year (1957–1958), 37 International Institute of Air and Space Law, 199 International MicroSpace, 90 International Scientific Lunar Observatory, 157 International Space Station, 55, 64–65, 64, 71, 75, 91, 96, 100, 102, 142, 143, 144, 151, 153, 154, 159, 178–79, 179, 185, 272, 275 living conditions on, 116–17 as staging point, 148 supply runs to, 100–101, 104 International Space University, 90 International Traffic in Arms Regulation (ITAR), 105–6, 144 Internet: Congressional legislation on, 78, 144 development of, 76–77, 77, 94, 95, 271 erroneous predictions about, 213–14 limitations of, 66–67 robotics and, 206 space travel compared to, 76–80, 77, 80 Internet Service Providers (ISPs), 78 interstellar travel, 215–18 energy technology for, 219–24 four approaches to, 251–52 scale model for, 219 Intrepid rovers, 165 Inuit people, 120 Io, 53, 177 property rights on, 145 “iron curtain,” 35 Iron Man, 95 isolation, psychological impact of, 169–70 Jacob’s Ladder, 149 Jade Rabbit (“Yutu”), 139, 143, 161 Japan, 161, 273 Japan Aerospace Exploration Agency (JAXA), 184 Jefferson, Thomas, 224 Jemison, Mae, 224 jet engines, 69–70 Jet Propulsion Laboratory, 141 Johnson, Lyndon, 38, 42, 45, 158, 269 Johnson Space Center, 76, 104, 179, 206, 229, 269 see also Mission Control Jones, Stephanie Tubbs, 74 Joules per kilogram (MJ/kg), 219–20, 222 Journalist in Space program, 74 “junk” DNA, 10, 266 Juno probe, 228 Jupiter, 126, 127, 177, 217, 270 distance from Earth to, 50 moons of, 97, 125, 125 probes to, 51–52, 228 as uninhabitable, 125 Justin (robot), 178 Kaku, Michio, 253 Karash, Yuri, 65 Kardashev, Nikolai, 253 Kardashev scale, 253, 254, 258 Kármán line, 70, 70, 101 Kennedy, John F., 41–43, 45 Kepler, Johannes, 183 Kepler’s law, 127 Kepler spacecraft and telescope, 128, 128, 129–31, 218, 278 Khrushchev, Nikita, 42, 47 Kickstarter, 184 Killian, James, 38 Kline, Nathan, 205 Knight, Pete, 71 Komarov, Vladimir, 43, 108 Korean War, 141 Korolev, Sergei, 35, 37 Kraft, Norbert, 200 Krikalev, Sergei, 115 Kunza language, 119 Kurzweil, Ray, 94, 207, 259 Laika (dog), 47, 65, 269 Laliberté, Guy, 75 landings, challenges of, 51, 84–85, 170 Lang, Fritz, 28, 268 language: of cryptography, 291 emergence of, 15, 16 of Orcas, 190 in reasoning, 13 Lansdorp, Bas, 170–71, 198–99, 282 lasers, 223, 224, 225–26, 239 pulsed, 190, 243 last common ancestor, 6, 123, 265 Late Heavy Bombardment, 172 latency, 178 lava tubes, 160 legislation, on space, 39, 78, 90, 144, 145–47, 198–200 Le Guin, Ursula K., 236–37 Leonov, Alexey, 55 L’Garde Inc., 284 Licancabur volcano, 119 Licklider, Joseph Carl Robnett “Lick,” 76–78 life: appearance and evolution on Earth of, 172 artificial, 258 detection of, 216–18 extension of, 26, 207–8, 250–51, 259 extraterrestrial, see aliens, extraterrestrial intelligent, 190, 235, 241, 243, 258 requirements of habitability for, 122–26, 125, 129, 131–33, 241, 256–57 lifetime factor (L), 234–335 lift, in flight, 68–70, 83 lift-to-drag ratio, 83 light: from binary stars, 126 as biomarker, 217 Doppler shift of, 127 momentum and energy from, 183 speed of, 178, 228–29, 250, 251 waves, 66 Lindbergh, Charles, 30, 81–82, 90–91, 268 “living off the land,” 166, 200 logic, 14, 18 Long March, 141 Long March rockets, 113, 142, 143 Long Now Foundation, 293 Los Alamos, N.


pages: 356 words: 105,533

Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market by Scott Patterson

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algorithmic trading, automated trading system, banking crisis, bash_history, Bernie Madoff, butterfly effect, buttonwood tree, cloud computing, collapse of Lehman Brothers, Donald Trump, Flash crash, Francisco Pizarro, Gordon Gekko, Hibernia Atlantic: Project Express, High speed trading, Joseph Schumpeter, latency arbitrage, Long Term Capital Management, Mark Zuckerberg, market design, market microstructure, pattern recognition, pets.com, Ponzi scheme, popular electronics, prediction markets, quantitative hedge fund, Ray Kurzweil, Renaissance Technologies, Sergey Aleynikov, Small Order Execution System, South China Sea, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stochastic process, transaction costs, Watson beat the top human players on Jeopardy!

Progress Software, a firm that tracks algorithmic trading, predicted that a financial institution would lose one billion dollars or more in 2012 when a rogue algorithm went “into an infinite loop … which cannot be shut down.” And since the computer programs were now linked across markets—stock trades were synced to currencies and commodities and futures and bonds—and since many of the programs were very similar and were massively leveraged, the fear haunting the minds of the Plumbers was that the entire system could snap like a brittle twig in a matter of minutes. A chaotic butterfly effect could erase everyone’s hard-earned savings in an eyeblink and, for kicks, throw the global economy into yet another Wall Street–spawned tailspin. The pieces were already in place. Exchanges from Singapore to China to Europe to the United States were linking up through a vast web of algo traders dabbling in every tradable security in the world. The threat had grown so tangible that it even had a name: the Splash Crash.

The full interview can be found here: http://www.hftreview.com/pg/blog/mike/read/27568. DAVE CLIFF: It’s a big change that’s happened in the last 10 or 15 years as everything has become computerized and as every computer can talk to any other computer. Suddenly, in principle, an error or a failure in one system, that would have been an isolated event, can have negative effects that ripple out in a chain reaction over a whole network. HFTR: And then you have the whole “butterfly effect”? CLIFF: Yes exactly. And one of the things that we have focused on in that project for the last five years is the extent on which the global financial markets are now essentially a single, planetary-wide, ultra-large scale complex IT system. And the extent to which there are failure modes like those I saw in FX back in 2005 might, in principle, ripple out over the entire system and cause big problems.


pages: 823 words: 220,581

Debunking Economics - Revised, Expanded and Integrated Edition: The Naked Emperor Dethroned? by Steve Keen

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accounting loophole / creative accounting, banking crisis, banks create money, barriers to entry, Benoit Mandelbrot, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, butterfly effect, capital asset pricing model, cellular automata, central bank independence, citizen journalism, clockwork universe, collective bargaining, complexity theory, correlation coefficient, credit crunch, David Ricardo: comparative advantage, debt deflation, diversification, double entry bookkeeping, en.wikipedia.org, Eugene Fama: efficient market hypothesis, experimental subject, Financial Instability Hypothesis, Fractional reserve banking, full employment, Henri Poincaré, housing crisis, Hyman Minsky, income inequality, invisible hand, iterative process, John von Neumann, laissez-faire capitalism, liquidity trap, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, market clearing, market microstructure, means of production, minimum wage unemployment, open economy, place-making, Ponzi scheme, profit maximization, quantitative easing, RAND corporation, random walk, risk tolerance, risk/return, Robert Shiller, Robert Shiller, Ronald Coase, Schrödinger's Cat, scientific mainstream, seigniorage, six sigma, South Sea Bubble, stochastic process, The Great Moderation, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, total factor productivity, tulip mania, wage slave

Not only does it ignore uncertainty, even prediction of what a model itself will do in the future is only possible if the model is ‘ergodic’ – meaning that the past history of the model is a reliable guide to its future behavior. The complex dynamic models we considered in Chapter 9, such as Lorenz’s model of atmospheric turbulence, are non-ergodic.34 The past history of a complex model is not a reliable guide to its future behavior, because where the model will evolve to is dependent on where it starts from – the so-called ‘Butterfly Effect’ applies. Two situations with differences in initial conditions that are too small to be distinguished from each other will have drastically different outcomes in the future: they will be similar for a short while (which is why weather forecasting is accurate only about a week in advance) but then diverge completely. Only if models of the economy are not of this class are ‘rational expectations’ possible even within the model.

It is properly defined by the Wiktionary (en.wiktionary.org/wiki/ergodic), and the Wikipedia entry on ergodic Theory (en.wikipedia.org/wiki/ergodic_theory) makes the important point that ‘For the special class of ergodic systems, the time average is the same for almost all initial points: statistically speaking, the system that evolves for a long time “forgets” its initial state.’ This is not the case for complex or chaotic models, which show ‘sensitive dependence on initial conditions’ (see en.wikipedia.org/wiki/Butterfly_effect and en.wikipedia.org/wiki/Chaos_theory). 35 I can think of no more apt term to describe the group that led the campaign to make macroeconomics a branch of neoclassical microeconomics. Certainly the neoclassical attitude to researchers who refused to use ‘rational expectations’ in their models approached the old mafia cliché of ‘an offer you can’t refuse’: ‘assume rational expectations, or your paper won’t get published in a leading journal.’ 36 This is based on the belief that output would be higher (and prices lower) under competition than under monopoly, which I showed to be false in Chapter 4. 37 a rule of thumb that asserts that the central bank can control inflation by increasing real interest rates roughly twice as much as any increase in inflation.

assumptions; ancillary; and logic; domain assumptions; heuristic assumptions; importance of, to economists; negligibility assumptions; taxonomy of see also ceteris paribus assumption auctioneer, Walras model of Australia, cash handout in Austrian school of economics; weaknesses of Automatic Earth, The Axioms of Revealed Preference Bagehot, Walter bailout: of banks; of firms; of individuals bankers, as separate class bankruptcy banks; bailout of; controlling lending of; creation of new money; distinct from firms; electronic transfer banking; profit from debt; reserves of; role of barter economy Basel Rules Behavioral Finance Bentham, Jeremy; ‘In defence of usury’ Bernanke, Ben; as chairman of Federal Reserve; Essays on the Great Depression Bertrand model Bezemer, Dirk; ‘No one saw this coming’ Bhaduri, A. bicycle riding, learning of Big Bang theory Big Government Biggs, M. Black Swan events Blanchard, Olivier Blatt, John Blaug, Mark Bliley, Thomas J. Blinder, Alan Blodget, Henry Bohm, David Bose, Arun Brahe, Tycho de budget constraints budget deficits Buffet, Warren business cycle; in USA; real Butterfly Effect calculus; use of Cambridge controversies capacity; capacity utilization capital: as amorphous mass; circulating; definition of; different meanings of; fixed; measurement of; theory of capital assets pricing model (CAPM); failure of capitalism: as joint enterprise; demise of, imagined; monetary model of; response to disequilibrium; value as social system Carpenter, Seth, ‘Money, reserves, and the transmission of monetary policy’ ceteris paribus assumption chain reaction of depression chain rule chaos; concept of; exponential sensitivity of situations chaos theory Chiarella, Carl circuit of capital Clark, J.


pages: 404 words: 134,430

Why People Believe Weird Things: Pseudoscience, Superstition, and Other Confusions of Our Time by Michael Shermer

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Albert Einstein, Alfred Russel Wallace, anesthesia awareness, anthropic principle, butterfly effect, cognitive dissonance, complexity theory, conceptual framework, correlation does not imply causation, cosmological principle, discovery of DNA, false memory syndrome, Gary Taubes, invention of the wheel, Isaac Newton, laissez-faire capitalism, life extension, Murray Gell-Mann, out of africa, Richard Feynman, Richard Feynman, Search for Extraterrestrial Intelligence, Silicon Valley, Stephen Hawking, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, the scientific method, Thomas Kuhn: the structure of scientific revolutions

Those events are mostly human actions, so history is a product of the way individual human actions come together to produce the future, however constrained by certain previous conditions, such as laws of nature, economic forces, demographic trends, and cultural mores. We are free, but not to do just anything. And the significance of a human action is also restricted by when in the historical sequence the action is taken. The earlier the action is in a sequence, the more sensitive the sequence is to minor changes—the so-called butterfly effect. The key to historical transcendence is that since you cannot know when in the sequence you are (since history is contiguous) and what effects present actions may have on future outcomes, positive change requires that you choose your actions wisely—all of them. What you do tomorrow could change the course of history, even if only long after you are gone. Think of all the famous people of the past who died relatively unknown.

Until these are taken into account, I cannot say exactly how much information can in fact be extracted from the past." The problem of the irrecoverable past is serious, since history is a conjuncture of events compelling a certain course of action by constraining prior events. History often turns on tiny contingencies, very few of which we know about. Given the sensitive dependence on initial conditions—the butterfly effect—how does Omega/God resurrect all the butterflies? This perception of history derails Drs. Tipler and Pangloss, as Voltaire noted at the end of Candide: Pangloss sometimes said to Candide: "All events are linked up in this best of all possible worlds; for, if you had not been expelled from the noble castle by hard kicks in your backside for love of Mademoiselle Cunegonde, if you had not been clapped into the Inquisition, if you had not wandered about America on foot, if you had not stuck your sword in the Baron, if you had not lost all your sheep from the land of Eldorado, you would not be eating candied citrons and pistachios here......Tis well said," replied Candide, "but we must cultivate our gardens." (1985, p. 328) Namely, whatever the sequence of contingencies and necessities in our lives and in history, the outcome would have seemed equally inevitable.


pages: 298 words: 43,745

Understanding Sponsored Search: Core Elements of Keyword Advertising by Jim Jansen

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AltaVista, barriers to entry, Black Swan, bounce rate, business intelligence, butterfly effect, call centre, Claude Shannon: information theory, complexity theory, correlation does not imply causation, en.wikipedia.org, first-price auction, information retrieval, inventory management, life extension, linear programming, megacity, Nash equilibrium, Network effects, PageRank, place-making, price mechanism, psychological pricing, random walk, Schrödinger's Cat, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, sentiment analysis, social web, software as a service, stochastic process, telemarketer, the market place, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Vickrey auction, yield management

., systems that follow a fixed rule over time), where the system is highly dependent on Bringing It All Together initial conditions. This means that very slight fluctuations in the initial conditions can radically affect the end state of the system. So, a ball balancing on a hilltop (using the classic example) may fall in many directions depending on very slightly changing atmospheric conditions. Known commonly as the butterfly effect, these small changes in initial conditions make long-term prediction impossible. However, a chaotic system is not random. These systems are dynamical so their future state is determined by the initial state. These systems only appear to be random because slight changes are amplified so much over time. So, how do we address chaotic systems? We continually sample data and measure the system to do short-term predictions.

., 131 bounded rationality, 98, 100 Boyce, Rick, 10 brand, 6, 14–15, 25, 69–70, 74, 95, 103, 111–122, 126–127, 129–130, 140–142, 144, 201, 207, 221, 223, 225 brand advertising, 126 Brand attitude, 116 brand awareness, 113 brand equity, 114 brand familiarity, 116 brand image, 1, 14–15, 70, 103, 112–114, 117, 120, 141 Brand recall, 114, 117 Brand recognition, 113, 117 Brand relationship, 114–115, 117 273 274 Index Brand trust, 116–117 branded keyphrases, 119–120, 141, 183, 187 branded terms, 41, 69–70, 186 branding, xiii, 16, 65, 69, 103, 106, 111–114, 116–118, 120–121, 126, 128–129, 131, 135, 140–142, 149, 171, 177, 190, 199, 203, 207–209, 213, 227 Brewer, Jeffrey, 11 Brin, Sergey, 206, 217–218 Broder, Andrei, 44 Brooks, Nico, 76–77 Bullington, Brett, 12 butterfly effect, 205 buying decision, 98–99, 130 buying funnel, 86, 93–98, 101, 103–106, 129–130, 210, 213 Capitani, 74 Caples, John, 127 CA$HVERTISING, 125 causation, 153 caveat emptor, 179 chaos theory, 204 check-in applications, 224 choice set, 71, 79, 94, 120, 130 Choice uncertainty, 99 classic advertising appeals, 124 click fraud, 167–168, 170, 221 Click potential, 76 clickthrough lift, 124 click-through rate, 24, 74–75, 178, See€clickthrough rate, 14–15 The Cluetrain Manifesto, 129 Commercial Alert, 21 communication process, 32–33, 36, 54, 86, 101–103, 105–106, 111, 207, 210, 213 communication theory, 86 complexity theory, 204 comScore, 152 concept of chunking, 42 concept of technological innovation, 5 consumer behavior, xiii, 86, 89, 94, 96, 98, 101, 103, 105–106, 129 consumer buying behavior, 98, 103 consumer buying process, 94, 98, 100–101, 104, 106 consumer decision making, 86, 93–95, 101, 105, 208, 213 consumer purchasing behavior, 86 consumer search process, 48, 90, 93, 98 consumer searching, 41, 47, 63, 86–87, 90, 93, 95, 98–99, 210 consumer searching behavior, 41, 86, 95, 210 content targeting, 19 context, ix, x, xiii, xix, xx, xxi, 1, 11, 32–33, 36, 43, 69, 86, 88, 91–92, 97, 100–103, 106, 112, 114–115, 119, 126–128, 131, 157, 159–164, 166, 177, 187, 212, 217, 220, 224, 226 contextual advertising, xii, 19, 225 Conversion potential, 76 Corporate branding, 112 Correlation, 153 Credence goods, 39–40 creditability, 150 Culliton, James, 131 curiosity, i, ix, x, xiv, 46, 125 Customer brand image, 120 customer market segmentation, 120 Database of Intentions, 31 dayparting, 184, 186 Delhagen, Kate, 12 determinants, 92–93, 98, 118 Direct Hit Technologies, 21 direct response, 126 direct response advertising, 126 Doc Seals, 129 dominate, 125 east, 22, 24, 72 ebay, 179 Ebbinghaus, H., 74 economic theory, 49, 91 effectiveness, 24, 35, 113, 118, 145, 149, 151, 159, 170, 180, 210 efficiency, 62, 151, 170, 180, 210 empirical methods, xii erosion, 159–160 escape, 125 Esch, F.


pages: 512 words: 162,977

New Market Wizards: Conversations With America's Top Traders by Jack D. Schwager

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backtesting, Benoit Mandelbrot, Berlin Wall, Black-Scholes formula, butterfly effect, commodity trading advisor, Elliott wave, fixed income, full employment, implied volatility, interest rate swap, Louis Bachelier, margin call, market clearing, market fundamentalism, paper trading, pattern recognition, placebo effect, prediction markets, Ralph Nelson Elliott, random walk, risk tolerance, risk/return, Saturday Night Live, Sharpe ratio, the map is not the territory, transaction costs, War on Poverty

., systems that never exactly repeat themselves and hence never find a steady state, such as weather or the markets—slight differences in variable values or measurements can be magnified to have huge effects over increasing periods of time. The technical name for this phenomenon—sensitive dependence on initial conditions—has become better known as the Butterfly Effect. As James Gleick described it in his excellent book, Chaos: Making a New Science, “In weather, for example, this translates into what is only half-jokingly known as the Butterfly Effect—the notion that a butterfly stirring the air today in Peking can transform storm systems next month in New York.”) There are too many unpredictable things that can happen within 300 / The New Market Wizard two months. To me, the ideal trade lasts ten days, but I approach every trade as if I’m only going to hold it two or three days.


pages: 455 words: 138,716

The Divide: American Injustice in the Age of the Wealth Gap by Matt Taibbi

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banking crisis, Bernie Madoff, butterfly effect, collapse of Lehman Brothers, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, Edward Snowden, ending welfare as we know it, forensic accounting, Gordon Gekko, greed is good, illegal immigration, information retrieval, London Interbank Offered Rate, London Whale, naked short selling, offshore financial centre, Ponzi scheme, profit motive, regulatory arbitrage, short selling, telemarketer, too big to fail, War on Poverty

Breuer was here repeating Holder’s mantra that before moving against an industry target, the Justice Department essentially had to ask industry experts for advice. He was also now expanding the possible collateral consequences to include a “ripple effect” that would impact the whole economy, including innocent victims not just within the target firm, but perhaps also in other firms as well. If we press charges, in other words, we just don’t know what might happen—to everybody! We were now officially in the realm of an Edward Lorenz “butterfly effect” theory of crime fighting: a single indictment might be felt all the way around the world, and forever. This interview startled even the most hardened observers of politics in Washington. Two U.S. senators, Republican Chuck Grassley of Iowa and Ohio Democrat Sherrod Brown, were so appalled that they sent Holder a letter demanding an explanation for Breuer’s Frontline interview. It didn’t take long for them to get their answer.

Holder during this Senate hearing did not mention that he had come up with this idea fourteen years earlier, long before too-big-to-fail was even imaginable. He went on. The problem comes, he said, “when we are hit with indications that if you do prosecute, if you do bring a criminal charge, it will have a negative impact on the national economy, perhaps even the world economy.” This was a variation on Breuer’s “butterfly effect” interview. We just don’t know what will happen if we press charges, so … let’s not. It was a stunning series of admissions. Even Barron’s was appalled. “The nation’s chief law-enforcement official admitted the decision to prosecute depends not on the law, but the impact on the financial markets,” wrote columnist Randall Forsyth. Breuer, meanwhile, was in the process of moving back to private practice.


pages: 1,205 words: 308,891

Bourgeois Dignity: Why Economics Can't Explain the Modern World by Deirdre N. McCloskey

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Admiral Zheng, agricultural Revolution, Albert Einstein, BRICs, British Empire, butterfly effect, Carmen Reinhart, clockwork universe, computer age, Corn Laws, dark matter, David Ricardo: comparative advantage, Donald Trump, Edward Lorenz: Chaos theory, European colonialism, experimental economics, financial innovation, Fractional reserve banking, full employment, George Akerlof, germ theory of disease, Gini coefficient, greed is good, Howard Zinn, income per capita, interchangeable parts, invention of agriculture, invention of air conditioning, invention of writing, invisible hand, Isaac Newton, James Watt: steam engine, John Maynard Keynes: technological unemployment, John Snow's cholera map, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, means of production, Naomi Klein, New Economic Geography, New Urbanism, purchasing power parity, rent-seeking, road to serfdom, Robert Gordon, Ronald Coase, Ronald Reagan, Scientific racism, Scramble for Africa, Shenzhen was a fishing village, Simon Kuznets, Slavoj Žižek, spinning jenny, Steven Pinker, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, total factor productivity, transaction costs, tulip mania, union organizing, Upton Sinclair, urban renewal, V2 rocket, very high income, working poor, World Values Survey, Yogi Berra

“Sensitive dependence on initial conditions” is the technical term for some “nonlinear” models—a piece of so called “chaos theory.” But under such 87 circumstances a history becomes untellable. 30 It may be so—the world may be in fact nonlinear dynamic, as Basil Moore argues. But then we will need to give up our project of telling its history, because the true causes will consist of lost horseshoe nails and butterfly effects too small to be detected. The reasons are the same as those that make it impossible to forecast distant weather: “Current forecasts are useful for about five days,” writes a leading student of such matters, “but it is theoretically impossible to extend the window more than two weeks into the future.” 31 It is “theoretically” impossible because the fluid mechanics, the radiative transfer, the photochemistry, the air-sea interactions, and so forth “are violently non-linear and strongly coupled.”

Quoted in Mokyr 1999a, p. 4. 21. Macaulay 1830: I, ii, p. 185. 22. Schumpeter 1954, p. 572n5. 23. Wex 2006, p. 95. 24. Schumpeter 1954, p. 572. 25. Macaulay 1830, p. 185. 26. Carus-Wilson 1941, p. 41. 27. Adams 1907 (1918), p. 498. 28. Jones 1981, 1988; Mokyr 1990. 29. Mokyr 1985, p. 44. 30. McCloskey 1991a. 31. Boyd 2008, p. 16. The two-week limit is why below I use three weeks as the timing of the "butterfly effect." 32. Mitchell 1962, p. 60. Marx made a similar calculation, using the 1861 census to support his claim that machinery disemployed workers (Marx 1867 [1887], p. 488). 33. Clapham 1926, p. 67. 34. Clapham 1926, p. 74. 35. Berg 1985; Hudson 1986, 1992; Hudson, ed. 1989,. 36. Musson 1978, pp. 8, 61, 167 8. By the way, the usual identification of Blake's image with cotton mills, used here, is doubtful.


pages: 482 words: 147,281

A Crack in the Edge of the World: America and the Great California Earthquake of 1906 by Simon Winchester

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Albert Einstein, butterfly effect, California gold rush, Golden Gate Park, index card, indoor plumbing, Loma Prieta earthquake, Menlo Park, place-making, risk tolerance, Silicon Valley, South of Market, San Francisco, supervolcano, The Chicago School, transcontinental railway, wage slave, Works Progress Administration

Much the same now appears to have happened in 2004, by far the most dangerous year of the young century that has followed. It began with an immense earthquake in Iran; a series of shocks and volcanoes then shuddered all around the world for much of the twelve months following; and then the catastrophic Sumatran Tsunami struck precisely one year after it all began. Geologists looking at the statistics have lately started to wonder if some cruel butterfly effect might be at work – a pattern that might permit a ferocious event on one side of the planet to trigger a similar disaster far away on the other. Those who believe in the ideas of Gaia think this might be so: as the plates shifting against one another are all interconnected, jostlings on one part of the planet’s surface might well create sympathetic movements elsewhere. Thus far there is no firm evidence – only the numbers, and the anecdotes, that show incontrovertibly that some years are seismically very much more dangerous than others.

Even though the two places – the Yellowstone caldera and the Denali Fault – are separated by 1,800 miles of rock and mountain and river and lake, the occurrence of trauma in one place seems to have an effect on the other, as though the whole of Western America were ringing like an immense brass bell. Which brought me back to the premise with which this account began – the notion that this fragile planet, suspended in the blackness of space, is now something to be considered as an immense whole, with all of its elements interlinked and interconnected, the one happenstance triggering another and another and another, for as long as the world exists. The butterfly effect, written into the rocks of the American West, and into the rest of the world as well. One day the researcher who discovered the effects of Alaskan quakes on Yellowstone geysers took me to see Daisy: might it signal by its timing some event in the distant West? So I waited with him in the late-spring sunshine, looking at my wristwatch, gazing across from behind a pinewood palisade towards the yellow patch of sulphur on the ground, surrounded by pools of blue groundwater.

Science...For Her! by Megan Amram

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Albert Einstein, blood diamonds, butterfly effect, crowdsourcing, dark matter, Dmitri Mendeleev, double helix, Google Glasses, Isaac Newton, Kickstarter, Mark Zuckerberg, pez dispenser, Schrödinger's Cat, Steve Jobs, Ted Kaczynski, the scientific method, Wall-E, wikimedia commons

Before someone makes a joke about the tree probably being from the “Beyond” section, I have to warn you—the tree is also a bath! So it’s from the “Bath” section! There’s a hollow in the center that you can fill with hot water and carefully bathe one leg in at a time. It’s a fake tree, obviously, but I would still throw it away and buy a new one every year to get the full Christmas effect® (not to be confused with The Butterfly Effect® starring Ashton Kutcher®, a Jew®). Christmas ornaments are the part of Christmas that I find most confusing. Who needs Christmas ornaments when nature has provided her own ornaments: bird’s nests, Frisbees, and plums that I sometimes Scotch-tape onto non-plum trees for fun? Still, decorating the tree was pretty cool. Xander provided the colored orbs. I provided the ol’ tape-plums. Garfield provided the laughs.


pages: 239 words: 56,531

The Secret War Between Downloading and Uploading: Tales of the Computer as Culture Machine by Peter Lunenfeld

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Albert Einstein, Andrew Keen, Apple II, Berlin Wall, British Empire, Brownian motion, Buckminster Fuller, Burning Man, butterfly effect, computer age, crowdsourcing, cuban missile crisis, Dissolution of the Soviet Union, don't be evil, Douglas Engelbart, Dynabook, East Village, Edward Lorenz: Chaos theory, Fall of the Berlin Wall, Francis Fukuyama: the end of history, Frank Gehry, Grace Hopper, gravity well, Guggenheim Bilbao, Honoré de Balzac, Howard Rheingold, invention of movable type, Isaac Newton, Jacquard loom, Jacquard loom, Jane Jacobs, Jeff Bezos, John von Neumann, Mark Zuckerberg, Marshall McLuhan, Mercator projection, Mother of all demos, mutually assured destruction, Network effects, new economy, Norbert Wiener, PageRank, pattern recognition, planetary scale, Plutocrats, plutocrats, Post-materialism, post-materialism, Potemkin village, RFID, Richard Feynman, Richard Feynman, Richard Stallman, Robert X Cringely, Schrödinger's Cat, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, social software, spaced repetition, Steve Ballmer, Steve Jobs, Steve Wozniak, Ted Nelson, the built environment, The Death and Life of Great American Cities, the medium is the message, Thomas L Friedman, Turing machine, Turing test, urban planning, urban renewal, Vannevar Bush, walkable city, Watson beat the top human players on Jeopardy!, William Shockley: the traitorous eight

Pendulums or pistons have relatively simple attractors. More complex systems (like weather, the stock market, or human culture) rely on a huge number of attractors and can be better thought of as “phase spaces.” In phase spaces, repetitions and differences lead to constantly shifting equilibriums. A minor change in the original condition can effect a hugely different outcome—better known as the “butterfly effect”—and can also create a different attractor, collapsing it into a fixed solution or tumbling it back into apparent chaos before a new strange attractor establishes itself. This effect is readily visible when you watch an animation of the strange attractor, many of which are now available on the World Wide Web. Disequilibrium can fall into a dynamic equilibrium with a slight shift, and can again be thrown into a new disequilibrium by yet another shift.


pages: 202 words: 72,857

The Wealth Dragon Way: The Why, the When and the How to Become Infinitely Wealthy by John Lee

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8-hour work day, Albert Einstein, barriers to entry, Bernie Madoff, butterfly effect, buy low sell high, California gold rush, Donald Trump, financial independence, high net worth, Mark Zuckerberg, passive income, payday loans, self-driving car, Snapchat, Stephen Hawking, Steve Jobs, Tony Hsieh, Y2K

And however much you learn, you will still make mistakes, but you may as well save time by not making the same mistakes that others have made! If you're not reading Forbes, you should be reading Forbes. If you are going to be financially successful, you have to read what financially successful people are reading and read about what they are doing. Action creates attraction. Like the ripples that occur in a pond when you throw a stone into it and break the clear surface, every action you take has a butterfly effect. The little waves we make when we take action create ripples in the universe and we attract back to us the results of those actions. Watch the ripples on the pond after you've thrown in a stone. At first it seems as if they are only moving outwards, but if you look carefully you'll see miniature circular waves being cast back to the centre. For every action there is a reaction. So the message here is…keep taking action!


pages: 855 words: 178,507

The Information: A History, a Theory, a Flood by James Gleick

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Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, bank run, bioinformatics, Brownian motion, butterfly effect, citation needed, Claude Shannon: information theory, clockwork universe, computer age, conceptual framework, crowdsourcing, death of newspapers, discovery of DNA, double helix, Douglas Hofstadter, en.wikipedia.org, Eratosthenes, Fellow of the Royal Society, Gödel, Escher, Bach, Henri Poincaré, Honoré de Balzac, index card, informal economy, information retrieval, invention of the printing press, invention of writing, Isaac Newton, Jacquard loom, Jacquard loom, Jaron Lanier, jimmy wales, John von Neumann, Joseph-Marie Jacquard, Louis Daguerre, Marshall McLuhan, Menlo Park, microbiome, Milgram experiment, Network effects, New Journalism, Norbert Wiener, On the Economy of Machinery and Manufactures, PageRank, pattern recognition, phenotype, pre–internet, Ralph Waldo Emerson, RAND corporation, reversible computing, Richard Feynman, Richard Feynman, Simon Singh, Socratic dialogue, Stephen Hawking, Steven Pinker, stochastic process, talking drums, the High Line, The Wisdom of Crowds, transcontinental railway, Turing machine, Turing test, women in the workforce

Alan Turing may have noticed this first: observing that the computer, like the universe, is best seen as a collection of states, and the state of the machine at any instant leads to the state at the next instant, and thus all the future of the machine should be predictable from its initial state and its input signals. The universe is computing its own destiny. Turing noticed that Laplace’s dream of perfection might be possible in a machine but not in the universe, because of a phenomenon which, a generation later, would be discovered by chaos theorists and named the butterfly effect. Turing described it this way in 1950: The system of the “universe as a whole” is such that quite small errors in initial conditions can have an overwhelming effect at a later time. The displacement of a single electron by a billionth of a centimetre at one moment might make the difference between a man being killed by an avalanche a year later, or escaping.♦ If the universe is a computer, we may still struggle to access its memory.

., 6.1, 6.2 Berry’s paradox, 6.1, 6.2, 12.1, 12.2, 12.3 Bible Bierce, Ambrose Bigelow, Julian binary operations coding systems for, 5.1, 5.2 representation of relay circuits as in telegraphy, 7.1, 8.1 in use of alphabetical ordering systems see also bit(s) biology entropy and, 9.1, 9.2, 9.3, 9.4 evolutionary, 10.1, 11.1 fundamental particles of of human ecosystem, 10.1, 10.2 information processing in, prl.1, prl.2, 10.1, 10.2, 10.3, 10.4 molecular, 9.1, 10.1, 10.2, 10.3 purposeful action in processes of, 9.1, 9.2 see also genetics; neurophysiology biosphere, 11.1, 11.2, 11.3 bit(s) as basis of physics, prl.1, prl.2, 13.1, 13.2 biological measurements cost of information processing data compression strategies, 12.1, 12.2 decision-making requirements definition of, prl.1, 7.1 first usage growth of measuring units, 14.1, 14.2 meaning and measurement of cosmos in, prl.1, 14.1 purpose transmission by fire beacon, 1.1, 1.2 black holes, prl.1, 13.1, 13.2, 13.3, 13.4 Blair, Ann Blair, Earl Bletchley Park, 7.1, 7.2, 8.1 Blount, Thomas, 3.1, 3.2 Bodleian Library, 3.1, 3.2, 6.1 Bohr, Niels, prl.1, 6.1, 13.1 Boltzmann, Ludwig, 9.1, 9.2 Bombe machine book burning Boole, George, prl.1, 5.1, 5.2, 5.3, 5.4, 5.5, 6.1, 6.2, 8.1, 8.2, 12.1 Borges, Jorge Luis, 14.1, 14.2, epl.1, epl.2 botanical dictionaries, 14.1, 14.2, 15.1 Bradley, Henry, 3.1, 3.2 Brahe, Tycho, 4.1, 15.1 brain; see neurophysiology Brassard, Gilles, 13.1, 13.2 “Breakdown of Physics in Gravitational Collapse, The” (Hawking) Brecht, Bertolt Breguet, Abraham-Louis, 5.1, 5.2 Brenner, Sydney, 10.1, 10.2, 10.3 Brewster, David, 4.1, 8.1 Bridenbaugh, Carl, 15.1, 15.2, 15.3 Briggs, Henry, 4.1, 4.2, 4.3, 4.4, 4.5 Brillouin, Léon, 9.1, 9.2, 9.3 Brin, Sergey, 14.1, epl.1 Broadbent, Donald, 8.1, 8.2 Brosin, Henry Brown, Robert Browne, Thomas, 1.1, 1.2, 5.1 Brownian motion, 6.1, 6.2, 8.1 Brunel, Isambard Kingdom Buchanan, James Bullokar, John Burgess, Anthony Burney, Venetia Burton, Robert, 15.1, 15.2, 15.3 Bush, Vannevar, prl.1, prl.2, 5.1n, 6.1, 6.2, 6.3, 6.4, 7.1 Butler, Samuel, 2.1, 10.1, 10.2 butterfly effect Byron, Augusta Ada; see Lovelace, Ada Byron, George Gordon, Lord, 4.1, 4.2 bytes Cage, John, 12.1, 12.2 Cairns-Smith, Alexander, 10.1, 10.2 calculators, calculating machines analog and digital Babbage’s Analytical Engine, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 4.10, 4.11, 4.12, 6.1, 7.1, 8.1 Babbage’s Difference Engine, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 4.10, 4.11, 4.12, 4.13, 4.14, 4.15, 4.16, 4.17, 4.18, 6.1 definition of “calculation,” 7.1 Differential Analyzer, 6.1, 6.2, 6.3, 6.4 in evolution of information technology, prl.1, 4.1 use of relay circuits in see also computation; computer(s); machines calculus, 4.1, 4.2, 4.3, 4.4, epl.1 Campbell, George, prl.1, prl.2 “Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?”


pages: 460 words: 107,712

A Devil's Chaplain: Selected Writings by Richard Dawkins

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Albert Einstein, Alfred Russel Wallace, Buckminster Fuller, butterfly effect, Claude Shannon: information theory, complexity theory, Desert Island Discs, double helix, Douglas Hofstadter, epigenetics, experimental subject, Fellow of the Royal Society, gravity well, Necker cube, out of africa, phenotype, placebo effect, random walk, Richard Feynman, Richard Feynman, Silicon Valley, stem cell, Stephen Hawking, Steven Pinker, the scientific method

Quantum mechanics, that brilliantly successful flagship theory of modern science, is deeply mysterious and hard to understand. Eastern mystics have always been deeply mysterious and hard to understand. Therefore eastern mystics must have been talking about quantum theory all along. Similar mileage is made of Heisenberg’s Uncertainty Principle (‘Aren’t we all, in a very real sense, uncertain?’), Fuzzy Logic (‘Yes, it’s OK for you to be fuzzy too’), Chaos and Complexity Theory (the butterfly effect, the platonic, hidden beauty of the Mandelbrot Set – you name it, somebody has mysticized it and turned it into dollars). You can buy any number of books on ‘quantum healing’, not to mention quantum psychology, quantum responsibility, quantum morality, quantum aesthetics, quantum immortality and quantum theology. I haven’t found a book on quantum feminism, quantum financial management or Afro-quantum theory, but give it time.


pages: 363 words: 101,082

Earth Wars: The Battle for Global Resources by Geoff Hiscock

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Admiral Zheng, Asian financial crisis, Bakken shale, Bernie Madoff, BRICs, butterfly effect, clean water, cleantech, corporate governance, demographic dividend, Deng Xiaoping, Edward Lorenz: Chaos theory, energy security, energy transition, eurozone crisis, Exxon Valdez, flex fuel, global rebalancing, global supply chain, hydraulic fracturing, Long Term Capital Management, Malacca Straits, Masdar, megacity, Menlo Park, Mohammed Bouazizi, new economy, oil shale / tar sands, oil shock, Panamax, purchasing power parity, Ralph Waldo Emerson, RAND corporation, Shenzhen was a fishing village, Silicon Valley, smart grid, South China Sea, sovereign wealth fund, special economic zone, spice trade, trade route, uranium enrichment, urban decay, working-age population, Yom Kippur War

But he was more positive about the United States, calling it “a pragmatic nation that doesn’t give up easily, and has the determination and the optimism to keep trying new things until it solves a problem.” As for China, du Plessis had little doubt that its long-term growth rate remained in place, “keeping China firmly in position as the world’s primary engine of growth.”17 This is the human element of the Earth wars, but there is a natural element at play as well. In classic chaos theory, tiny differences at the start of a sequence of events lead to vastly different outcomes—the so-called butterfly effect popularised by the U.S. mathematician and meteorologist Edward Lorenz in his work on computerised weather prediction in the 1960s. Lorenz, a professor emeritus at Massachusetts University of Technology (MIT) when he died in 2008 at the age of 90, wrote a paper in 1972 titled “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?” to explain his theory of sensitive dependence on initial conditions.


pages: 311 words: 94,732

The Rapture of the Nerds by Cory Doctorow, Charles Stross

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3D printing, Ayatollah Khomeini, butterfly effect, cognitive dissonance, combinatorial explosion, complexity theory, Credit Default Swap, dematerialisation, Drosophila, epigenetics, Extropian, gravity well, greed is good, haute couture, hive mind, margin call, phenotype, Plutocrats, plutocrats, rent-seeking, Richard Feynman, Richard Feynman, telepresence, Turing machine, Turing test, union organizing

Huw feels belligerent. “I do the same every time I do anything and everything. Every time I take any action, it ripples out to all the people who are affected by it, and all the people they effect. You’re saying that sensitivity to initial conditions means that you’re morally obliged never to change your mind. It’s rubbish. Just because causality runs backwards in this place doesn’t mean the butterfly effect becomes the first commandment. Now, what did I promise 639,219 before we arbed?” Bonnie and the djinni are both talking now, but Huw has literally tuned them out, so that they’ve faded out of her causal universe, unable to affect her. She’s really getting to like this capabilities wheeze. She tunes them back in. “Right,” she says, pointing at Bonnie. “You, talk.” “Look,” Bonnie says, “you’ve got this all wrong.”


pages: 416 words: 106,582

This Will Make You Smarter: 150 New Scientific Concepts to Improve Your Thinking by John Brockman

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23andMe, Albert Einstein, Alfred Russel Wallace, banking crisis, Barry Marshall: ulcers, Benoit Mandelbrot, Berlin Wall, biofilm, Black Swan, butterfly effect, Cass Sunstein, cloud computing, congestion charging, correlation does not imply causation, Daniel Kahneman / Amos Tversky, dark matter, data acquisition, David Brooks, delayed gratification, Emanuel Derman, epigenetics, Exxon Valdez, Flash crash, Flynn Effect, hive mind, impulse control, information retrieval, Isaac Newton, Jaron Lanier, John von Neumann, Kevin Kelly, mandelbrot fractal, market design, Mars Rover, Marshall McLuhan, microbiome, Murray Gell-Mann, Nicholas Carr, open economy, place-making, placebo effect, pre–internet, QWERTY keyboard, random walk, randomized controlled trial, rent control, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Schrödinger's Cat, security theater, Silicon Valley, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, the scientific method, Thorstein Veblen, Turing complete, Turing machine, Walter Mischel, Whole Earth Catalog

And while this can produce really important insights—even big emission reductions only delay the 2˚C fever for nineteen years—it leaves out all of those abrupt climate shifts observed since 1976, as when the world’s drought acreage doubled in 1982 and jumped from double to triple in 1997, then back to double in 2005. That’s like stairs, not a ramp. Even if we thoroughly understood the mechanism for an abrupt climate shift—likely a rearrangement of the winds that produce Deluge ’n’ Drought by delivering ocean moisture elsewhere, though burning down the Amazon rain forest should also trigger a big one—chaos theory’s butterfly effect says we still could not predict when a big shift will occur or what size it will be. That makes a climate surprise like a heart attack. You can’t predict when. You can’t say whether it will be minor or catastrophic. But you can often prevent it—in the case of climate, by cleaning up the excess CO2. Drawing down the CO2 is also typically excluded from the current climate framing. Mere emissions reduction now resembles locking the barn door after the horse is gone—worthwhile, but not exactly recovery.


pages: 297 words: 98,506

Deep Survival: Who Lives, Who Dies, and Why by Laurence Gonzales

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business climate, butterfly effect, complexity theory, Edward Lorenz: Chaos theory, impulse control, Lao Tzu, loose coupling, Louis Pasteur, V2 rocket

Run the equations two, four, eight times, and they may seem to be giving similar results. But the harder you drive the system, the more iterations result and the more unpredictable it becomes. Edward Lorenz, a meteorologist at MIT, was modeling weather systems on a computer in the early 1960s when he accidentally discovered that a tiny change in the initial state (1 part in 1,000) was enough to produce totally different weather patterns. That became known as the Butterfly Effect, “the notion that a butterfly stirring the air today in Peking can transform storm systems next month in New York,” as Gleick wrote in Chaos. Classical science aimed at predicting an outcome, then conducting an experiment to confirm it. But natural systems don’t behave so neatly. The specific details can be described, yet no one can predict the outcome. You can describe how the weather works with high school math and physics, but you can’t tell very far in advance when or even if it will rain.


pages: 383 words: 108,266

Predictably Irrational, Revised and Expanded Edition: The Hidden Forces That Shape Our Decisions by Dan Ariely

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air freight, Al Roth, Bernie Madoff, Burning Man, butterfly effect, Cass Sunstein, collateralized debt obligation, computer vision, corporate governance, credit crunch, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, endowment effect, financial innovation, fudge factor, Gordon Gekko, greed is good, housing crisis, invisible hand, lake wobegon effect, late fees, loss aversion, market bubble, Murray Gell-Mann, payday loans, placebo effect, price anchoring, Richard Thaler, second-price auction, Silicon Valley, Skype, The Wealth of Nations by Adam Smith, Upton Sinclair

But one of the major lessons we’ve learned from the 2008 economic meltdown is that our financial fortunes are all tied together more tightly than anybody realized. What started as subprime mortgage loans to people with relatively bad credit ended up sucking the wealth out of the entire economy, and bringing almost every economic activity—from car loans to retail spending—to a near-halt. Even people with hefty retirement portfolios took a big hit. In the end, the economy is a complex dynamic system, a bit like the “butterfly effect” in chaos theory where events that happen to a small group of individuals (such as subprime borrowers) can have large and frightening effects down the road for everyone else. WHAT CAN WE, as individuals, do to overcome the challenges posed by the financial planning fallacy? First, of course, everyone needs to save more for a rainy day* and realize that rainy days are more common than we expect.


pages: 345 words: 86,394

Frequently Asked Questions in Quantitative Finance by Paul Wilmott

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Albert Einstein, asset allocation, Black-Scholes formula, Brownian motion, butterfly effect, capital asset pricing model, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, discrete time, diversified portfolio, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, fudge factor, implied volatility, incomplete markets, interest rate derivative, interest rate swap, iterative process, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, martingale, Norbert Wiener, quantitative trading / quantitative finance, random walk, regulatory arbitrage, risk/return, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, stochastic volatility, transaction costs, urban planning, value at risk, volatility arbitrage, volatility smile, Wiener process, yield curve, zero-coupon bond

Deterministic: The idea behind this approach is that our model will tell us everything about the future. Given enough data, and a big enough brain, we can write down some equations or an algorithm for predicting the future. Interestingly, the subjects of dynamical systems and chaos fall into this category. And, as you know, chaotic systems show such sensitivity to initial conditions that predictability is in practice impossible. This is the ‘butterfly effect,’ that a butterfly flapping its wings in Brazil will ‘cause’ rainfall over Manchester. (And what doesn’t!) A topic popular in the early 1990s, this has not lived up to its promises in the financial world. Discrete/Continuous: Whether probabilistic or deterministic the eventual model you write down can be discrete or continuous. Discrete means that asset prices and/or time can only be incremented in finite chunks, whether a dollar or a cent, a year or a day.


pages: 402 words: 110,972

Nerds on Wall Street: Math, Machines and Wired Markets by David J. Leinweber

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AI winter, algorithmic trading, asset allocation, banking crisis, barriers to entry, Big bang: deregulation of the City of London, butterfly effect, buttonwood tree, buy low sell high, capital asset pricing model, citizen journalism, collateralized debt obligation, corporate governance, Craig Reynolds: boids flock, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Danny Hillis, demand response, disintermediation, distributed generation, diversification, diversified portfolio, Emanuel Derman, en.wikipedia.org, experimental economics, financial innovation, Gordon Gekko, implied volatility, index arbitrage, index fund, information retrieval, Internet Archive, John Nash: game theory, Khan Academy, load shedding, Long Term Capital Management, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, market fragmentation, market microstructure, Mars Rover, moral hazard, mutually assured destruction, natural language processing, Network effects, optical character recognition, paper trading, passive investing, pez dispenser, phenotype, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Renaissance Technologies, Richard Stallman, risk tolerance, risk-adjusted returns, risk/return, Ronald Reagan, semantic web, Sharpe ratio, short selling, Silicon Valley, Small Order Execution System, smart grid, smart meter, social web, South Sea Bubble, statistical arbitrage, statistical model, Steve Jobs, Steven Levy, Tacoma Narrows Bridge, the scientific method, The Wisdom of Crowds, time value of money, too big to fail, transaction costs, Turing machine, Upton Sinclair, value at risk, Vernor Vinge, yield curve, Yogi Berra

Applications include asset allocation, quantitative equity portfolio management, market making, and currency trading. That was 1995. To hear how some of this turned out, keep reading the next chapter. Notes 1. One of those numerical meteorology problems led to the discovery of deterministic chaos, the strong dependence of a result on what was presumed to be meaninglessly small differences in the inputs. This was popularized as the so-called butterfly effect, A Little AI Goes a Long Way on Wall Str eet 179 since the seemingly insignificant pressure changes caused by a fluttering butterfly, well within the limits of error of barometers used to measure them, could result in wildly different simulated future weather and climate outcomes. James Gleick’s book, Chaos (New York: Viking Penguin, 1987), is the place to start for the story of chaos. 2.


pages: 470 words: 144,455

Secrets and Lies: Digital Security in a Networked World by Bruce Schneier

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Ayatollah Khomeini, barriers to entry, business process, butterfly effect, cashless society, Columbine, defense in depth, double entry bookkeeping, fault tolerance, game design, IFF: identification friend or foe, John von Neumann, knapsack problem, mutually assured destruction, pez dispenser, pirate software, profit motive, Richard Feynman, Richard Feynman, risk tolerance, Silicon Valley, Simon Singh, slashdot, statistical model, Steve Ballmer, Steven Levy, the payments system, Y2K, Yogi Berra

We could never have made the Internet as complex and interesting as it is today without modularity. But increased modularity means increased security flaws, because security often fails where two modules interact. The third reason is the interconnectedness of complex systems. Distributed and networked systems are inherently risky. Complexity leads to the coupling of systems, which can lead to butterfly effects (minor problems getting out of hand). We’ve already seen examples of this as everything becomes Internet-aware. For years we knew that Internet applications like sendmail and rlogin had to be secure, but the recent epidemic of macro viruses shows that Microsoft Word and Excel need to be secure. Java applets not only need to be secure for the uses they are intended for, but they also need to be secure for any other use an attacker might think of.


pages: 736 words: 147,021

Safe Food: The Politics of Food Safety by Marion Nestle

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biofilm, butterfly effect, clean water, double helix, Fellow of the Royal Society, illegal immigration, out of africa, Ralph Nader, Ronald Reagan, software patent, Upton Sinclair

Flynn L, Gillard MS. Pro-GM food scientist “threatened editor.” Guardian (London), November 1, 1999, at www.guardian.co.uk/science/1999/nov/01/gm.food. See: Correspondence: GM food debate. Lancet 1999;354:1725–1729. En-serink M. The Lancet scolded over Pusztai paper. Science 1999;286:656. 52. Losey JE, Rayor LS, Carter ME. Transgenic pollen harms monarch larvae. Nature 1999;399:214. 53. Stix G. The butterfly effect: new research findings and European jitters could cloud the future for genetically modified crops. Scientific American, August 1999:28–29. The finding inspired a book: Jack A. Imagine a World without Monarch Butterflies: Awakening to the Hazards of Genetically Altered Foods. Becket, MA: One Peaceful World Press, 1999. Kucinich DJ. Statement before the Senate Committee on Agriculture, Nutrition, and Forestry. 106th Congress, 1st Session, October 7, 1999, at http://agriculture.senate.gov/Hearings/Hearings_1999/kuc99107.htm. 54.


pages: 493 words: 172,533

Best of Kim Stanley Robinson by Kim Stanley Robinson

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Albert Einstein, butterfly effect, Edward Lorenz: Chaos theory, late capitalism, Murano, Venice glass, Richard Feynman, Richard Feynman

In 1987, the nation of Palestine raised its flag over the West Bank and parts of Jordan and Lebanon; a generation of camp children moved into homes. A child was born in Galilee. In 1990 Japan started its African Assistance League. The Hiroshima Peace Party had a billion members. And so on; so that by July 29th, 2045, no human on Earth was the same as those who would have lived if the nomad in Kirgiz had not stepped on the butterfly a century before. This phenomenon is known as the butterfly effect, and it is a serious problem for all other models of historical explanation; meaning trouble for you and for me. The scientific term for it is “sensitive dependence on initial conditions.” It is an aspect of chaos theory first studied by the meteorologist Edward Lorenz, who, while running computer simulations of weather patterns, discovered that the slightest change in the initial conditions of the simulation would quickly lead to completely different weather.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

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23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, offshore financial centre, optical character recognition, pattern recognition, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, WikiLeaks, Y Combinator, zero day

While there may be serendipitous benefits of such a network, there is also every chance many of its developments will be undesirable, negatively affecting global security, personal privacy, and human rights. Moreover, if you think the number of error messages and application crashes we face today are a problem, just wait until the Web is embedded in everything from your car to your sneakers to your microwave. Having to reboot your refrigerator, your thermostat, and your garage door in order to get them to run won’t be much fun either. If ever there were a technology that embodied the butterfly effect, it is surely the Internet of Things. In this world, it is impossible to know the consequences of connecting your home’s networked blender to the same information grid as an ambulance in Tokyo, a bridge in Sydney, or a Detroit auto manufacturer’s production line, and yet it will all be connected in one way or another. While some of the world’s smartest research and technology firms are rushing forward to build the Internet of Things (and claim their share of its multitrillion-dollar economic bounty), their colleagues back in the IT security department are frantically working to combat yesterday’s zero-day attack or the malware vulnerability crisis du jour.