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when your predictions are accurate enough—something happens. You cross a threshold where you should actually rethink your whole business model and product based on machine learning.…
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Ajay Agrawal (Power and Prediction: The Disruptive Economics of Artificial Intelligence)
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We have to go from what is essentially an industrial model of education, a manufacturing model, which is based on linearity and conformity and batching people. We have to move to a model that is based more on principles of agriculture. We have to recognize that human flourishing is not a mechanical process; it's an organic process. And you cannot predict the outcome of human development. All you can do, like a farmer, is create the conditions under which they will begin to flourish.
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Ken Robinson
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A theory is a good theory if it satisfies two requirements. It must accurately describe a large class of observations on the basis of a model that contains only a few arbitrary elements, and it must make definite predictions about the results of future observations.
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Stephen Hawking (A Brief History of Time)
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What does regression do? It finds a prediction based on the average of what has occurred in the past. For instance, if all you have to go on to determine whether it is going to rain tomorrow is what happened each day last week, your best guess might be an average. If it rained on two of the last seven days, you might predict that the probability of rain tomorrow is around two in seven, or 29 percent. Much of what we know about prediction has been making our calculations of the average better by building models that can take in more data about the context.
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Ajay Agrawal (Prediction Machines: The Simple Economics of Artificial Intelligence)
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breadth of training predicts breadth of transfer. That is, the more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example. Learners become better at applying their knowledge to a situation they’ve never seen before, which is the essence of creativity.
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David Epstein (Range: Why Generalists Triumph in a Specialized World)
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If there is one thing developmental psychologists have learned over the years, it is that parents don’t have to be brilliant psychologists to succeed. They don’t have to be supremely gifted teachers. Most of the stuff parents do with flashcards and special drills and tutorials to hone their kids into perfect achievement machines don’t have any effect at all. Instead, parents just have to be good enough. They have to provide their kids with stable and predictable rhythms. They need to be able to fall in tune with their kids’ needs, combining warmth and discipline. They need to establish the secure emotional bonds that kids can fall back upon in the face of stress. They need to be there to provide living examples of how to cope with the problems of the world so that their children can develop unconscious models in their heads.
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David Brooks (The Social Animal: The Hidden Sources of Love, Character, and Achievement)
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And the beauty of the anthropic principle is that it tells us, against all intuition, that a chemical model need only predict that life will arise on one planet in a billion billion to give us a good and entirely satisfying explanation for the presence of life here.
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Richard Dawkins
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All models are wrong,” the statistician George Box observed, “but some are useful.
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Philip E. Tetlock (Superforecasting: The Art and Science of Prediction)
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Conspiracy theory, like causality, works fantastically well as an explanatory model but only if you use it backwards. The fact that we cannot predict much about tomorrow strongly indicates that most of the explanations we develop about how something happened yesterday have (like history in general) a high bullshit content.
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Peter J. Carroll (Psybermagick: Advanced Ideas in Chaos Magic)
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Through prediction and correction, your brain continually creates and revises your mental model of the world. It’s a huge, ongoing simulation that constructs everything you perceive while determining how you act.
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Lisa Feldman Barrett (How Emotions Are Made: The Secret Life of the Brain)
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As the statistician George E. P. Box wrote, "All models are wrong, but some models are useful." What he meant by that is that all models are simplifications of the universe, as they must necessarily be. As another mathematician said, "The best model of a cat is a cat."
...
The key is in remembering that a model is a tool to help us understand the complexities of the universe, and never a substitute for the universe itself.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail—But Some Don't)
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The prediction models are more about persuasion than science.
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Scott Adams (Loserthink: How Untrained Brains Are Ruining America)
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There are two ways to handle such a world: try to predict, or try to prepare.
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Shane Parrish (The Great Mental Models: General Thinking Concepts)
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Something as superfluous as "play" is also an essential feature of our consciousness. If you ask children why they like to play, they will say, "Because it's fun." But that invites the next question: What is fun? Actually, when children play, they are often trying to reenact complex human interactions in simplified form. Human society is extremely sophisticated, much too involved for the developing brains of young children, so children run simplified simulations of adult society, playing games such as doctor, cops and robber, and school. Each game is a model that allows children to experiment with a small segment of adult behavior and then run simulations into the future. (Similarly, when adults engage in play, such as a game of poker, the brain constantly creates a model of what cards the various players possess, and then projects that model into the future, using previous data about people's personality, ability to bluff, etc. The key to games like chess, cards, and gambling is the ability to simulate the future. Animals, which live largely in the present, are not as good at games as humans are, especially if they involve planning. Infant mammals do engage in a form of play, but this is more for exercise, testing one another, practicing future battles, and establishing the coming social pecking order rather than simulating the future.)
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Michio Kaku (The Future of the Mind: The Scientific Quest to Understand, Enhance, and Empower the Mind)
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Fuzzy thinking can never be proven wrong. And only when we are proven wrong so clearly that we can no longer deny it to ourselves will we adjust our mental models of the world—producing a clearer picture of reality. Forecast, measure, revise: it is the surest path to seeing better.
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Philip E. Tetlock (Superforecasting: The Art and Science of Prediction)
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But if all maximizing models are really arguing is that “people will always seek to maximize something,” then they obviously can’t predict anything, which means employing them can hardly be said to make anthropology more scientific. All they really add to analysis is a set of assumptions about human nature. The assumption, most of all, that no one ever does anything primarily out of concern for others; that whatever one does, one is only trying to get something out of it for oneself. In common English, there is a word for this attitude. It’s called “cynicism.” Most of us try to avoid people who take it too much to heart. In economics, apparently, they call it “science.
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David Graeber (Toward An Anthropological Theory of Value: The False Coin of Our Own Dreams)
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Racism, at the individual level, can be seen as a predictive model whirring away in billions of human minds around the world. It is built from faulty, incomplete, or generalized data. Whether it comes from experience or hearsay, the data indicates that certain types of people have behaved badly. That generates a binary prediction that all people of that race will behave that same way. Needless to say, racists don’t spend a lot of time hunting down reliable data to train their twisted models. And once their model morphs into a belief, it becomes hardwired. It generates poisonous assumptions, yet rarely tests them, settling instead for data that seems to confirm and fortify them. Consequently, racism is the most slovenly of predictive models. It is powered by haphazard data gathering and spurious correlations, reinforced by institutional inequities, and polluted by confirmation bias.
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Cathy O'Neil (Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy)
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History cannot be explained deterministically and it cannot be predicted because it is chaotic. So many forces are at work and their interactions are so complex that extremely small variations in the strength of the forces and the way they interact produce huge differences in outcomes. Not only that, but history is what is called a ‘level two’ chaotic system. Chaotic systems come in two shapes. Level one chaos is chaos that does not react to predictions about it. The weather, for example, is a level one chaotic system. Though it is influenced by myriad factors, we can build computer models that take more and more of them into consideration, and produce better and better weather forecasts. Level two chaos is chaos that reacts to predictions about it, and therefore can never be predicted accurately. Markets, for example, are a level two chaotic system. What will happen if we develop a computer program that forecasts with 100 per cent accuracy the price of oil tomorrow? The price of oil will immediately react to the forecast, which would consequently fail to materialise. If the current price of oil is $90 a barrel, and the infallible computer program predicts that tomorrow it will be $100, traders will rush to buy oil so that they can profit from the predicted price rise. As a result, the price will shoot up to $100 a barrel today rather than tomorrow. Then what will happen tomorrow? Nobody knows.
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Yuval Noah Harari (Sapiens: A Brief History of Humankind)
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The problem nowadays is that, by and large, we do a pretty bad job of picking role models. We glorify actors, singers, athletes, and generic “celebrities,” only to be disappointed when—predictably—it turns out that their excellence at reciting, singing, playing basketball, or racking up Facebook likes and Twitter followers has pretty much nothing to do with their moral fiber.
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Massimo Pigliucci (How to Be a Stoic: Ancient Wisdom for Modern Living)
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I’ve said several times that the brain acts like a scientist. It forms hypotheses through prediction and tests them against the “data” of sensory input. It corrects its predictions by way of prediction error, like a scientist adjusts his or her hypotheses in the face of contrary evidence. When the brain’s predictions match the sensory input, this constitutes a model of the world in that instant, just like a scientist judges that a correct hypothesis is the path to scientific certainty.
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Lisa Feldman Barrett (How Emotions Are Made: The Secret Life of the Brain)
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theory is a good theory if it satisfies two requirements. It must accurately describe a large class of observations on the basis of a model that contains only a few arbitrary elements, and it must make definite predictions about the results of future observations.
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Stephen Hawking (A Brief History of Time)
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Instead, parents just have to be good enough. They have to provide their kids with stable and predictable rhythms. They need to be able to fall in tune with their kids’ needs, combining warmth and discipline. They need to establish the secure emotional bonds that kids can fall back upon in the face of stress. They need to be there to provide living examples of how to cope with the problems of the world so that their children can develop unconscious models in their heads.
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David Brooks (The Social Animal: The Hidden Sources Of Love, Character, And Achievement)
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The truth is creepier. It’s not that they are listening and then they can do targeted ad serving. It’s that their model of you is so accurate that it’s making predictions about you that you think are magic.
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Johann Hari (Stolen Focus: Why You Can't Pay Attention—and How to Think Deeply Again)
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The uncertainty principle signaled an end to Laplace's dream of a theory of science, a model of the universe that would be completely deterministic. We certainly cannot predict future events exactly if we cannot even measure the present state of the universe precisely!
We could still imagine that there is a set of laws that determine events completely for some supernatural being who, unlike us, could observe the present state of the universe without disturbing it. However, such models of the universe are not of much interest to us ordinary mortals. It seems better to employ the principle of economy known as Occam's razor and cut out all the features of the theory that cannot be observed.
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Stephen Hawking (A Briefer History of Time)
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most people don't know what they want unless they see it in context. We don't know what kind of racing bike we want—until we see a champ in the Tour de France ratcheting the gears on a particular model. We don't know what kind of speaker system we like—until we hear a set of speakers that sounds better than the previous one. We don't even know what we want to do with our lives—until we find a relative or a friend who is doing just what we think we should be doing.
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Dan Ariely (Predictably Irrational: The Hidden Forces That Shape Our Decisions)
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But forecasters often resist considering these out-of-sample problems. When we expand our sample to include events further apart from us in time and space, it often means that we will encounter cases in which the relationships we are studying did not hold up as well as we are accustomed to. The model will seem to be less powerful. It will look less impressive in a PowerPoint presentation (or a journal article or a blog post). We will be forced to acknowledge that we know less about the world than we thought we did. Our personal and professional incentives almost always discourage us from doing this.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don't)
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An agent does not have a model of its world - it is a model. In other words, the form, structure, and states of our embodied brains do not contain a model of the sensorium - they are that model. Every aspect of our brain and body can be predicted from our environment.
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Karl J. Friston
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All models are wrong, but some models are useful.”90 What he meant by that is that all models are simplifications of the universe, as they must necessarily be.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don't)
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The uncertainty principle signaled an end to Laplace’s dream of a theory of science, a model of the universe that would be completely deterministic: one certainly cannot predict future events exactly if one cannot even measure the present state of the universe precisely!
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Stephen Hawking (A Brief History of Time)
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The philosophical implications of "predictive coding" are deep and strange. The model suggests that our perceptions of the world offer us not a literal transcription of reality but rather a seamless illusion woven from both the data of our senses and the models in our memories.
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Michael Pollan (How to Change Your Mind: What the New Science of Psychedelics Teaches Us About Consciousness, Dying, Addiction, Depression, and Transcendence)
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The uncertainty principle signaled an end to Laplace’s dream of a theory of science, a model of the universe that would be completely deterministic: one certainly cannot predict future events exactly if one cannot even measure the present state of the universe precisely! We could still imagine that there is a set of laws that determine events completely for some supernatural being, who could observe the present state of the universe without disturbing it.
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Stephen Hawking (A Brief History of Time)
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A forecaster should almost never ignore data, especially when she is studying rare events like recessions or presidential elections, about which there isn’t very much data to begin with. Ignoring data is often a tip-off that the forecaster is overconfident, or is overfitting her model—that she is interested in showing off rather than trying to be accurate.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don't)
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Thus, they do not need to understand the statistical and mathematical models in depth. However, marketers need to understand the fundamental ideas behind a predictive model so that they can guide the technical teams to select data to use and which patterns to find.
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Philip Kotler (Marketing 5.0: Technology for Humanity)
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Research by media scholars Daniel Kreiss and Philip Howard indicates that the 2008 Obama campaign compiled significant data on more than 250 million Americans, including “a vast array of online behavioral and relational data collected from use of the campaign’s web site and third-party social media sites such as Facebook.…”96 Journalist Sasha Issenberg, who documented these developments in his book The Victory Lab, quotes one of Obama’s 2008 political consultants who likened predictive modeling to the tools of a fortune-teller: “We knew who… people were going to vote for before they decided.
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Shoshana Zuboff (The Age of Surveillance Capitalism)
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Why mental models? There is no system that can prepare us for all risks. Factors of chance introduce a level of complexity that is not entirely predictable. But being able to draw on a repertoire of mental models can help us minimize risk by understanding the forces that are at play. Likely consequences don’t have to be a mystery.
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Shane Parrish (The Great Mental Models: General Thinking Concepts)
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Summing up: Correctly interpreted, the simple economic model specifically predicts that people will be less selfish as voters than as consumers. Indeed, like diners at an all-you-can-eat buffet, we should expect voters to “stuff themselves” with moral rectitude. Once again, analogies between voting and shopping are deeply misleading.
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Bryan Caplan (The Myth of the Rational Voter: Why Democracies Choose Bad Policies)
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no simple mechanism could do the job as well or better. It might simply be that nobody has yet found the simpler alternative. The Ptolemaic system (with the Earth in the center, orbited by the Sun, the Moon, planets, and stars) represented the state of the art in astronomy for over a thousand years, and its predictive accuracy was improved over the centuries by progressively complicating the model: adding epicycles upon epicycles to the postulated celestial motions. Then the entire system was overthrown by the heliocentric theory of Copernicus, which was simpler and—though only after further elaboration by Kepler—more predictively accurate.63 Artificial intelligence methods are now used in more areas than it would make sense to review here, but mentioning a sampling of them will give an idea of the breadth of applications. Aside from the game AIs
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Nick Bostrom (Superintelligence: Paths, Dangers, Strategies)
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So ecological duress can increase or decrease aggression. This raises the key issue of what global warming will do to our best and worst behaviors. There will definitely be some upsides. Some regions will have longer growing seasons, increasing the food supply and reducing tensions. Some people will eschew conflict, being preoccupied with saving their homes from the encroaching ocean or growing pineapples in the Arctic. But amid squabbling about the details in predictive models, the consensus is that global warming won’t do good things to global conflict. For starters, warmer temperatures rile people up—in cities during the summers, for every three degree increase in temperature, there was a 4 percent increase in interpersonal violence and 14 percent in group violence. But global warming’s bad news is more global—desertification, loss of arable land due to rising seas, more droughts. One influential meta-analysis projected 16 percent and 50 percent increases in interpersonal and group violence, respectively, in some regions by 2050.
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Robert M. Sapolsky (Behave: The Biology of Humans at Our Best and Worst)
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But all predictive models share the same objective: They consider the various factors of an individual in order to derive a single predictive score for that individual. This score is then used to drive an organizational decision, guiding which action to take. Before using a model, we’ve got to build it. Machine learning builds the predictive model:
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Eric Siegel (Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die)
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It’s that their model of you is so accurate that it’s making predictions about you that you think are magic.
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Johann Hari (Stolen Focus: Why You Can't Pay Attention—and How to Think Deeply Again)
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All models are wrong, but some are useful.’ CHAPTER 6 Algorithms, Analytics and Prediction
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David Spiegelhalter (The Art of Statistics: Learning from Data)
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An economic model conditioned on the notion that nothing major will change is a useless one.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don't)
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We study the past ecological history, with the conscience of the present ecological conditions, the only window to predict the future environmental and climate changes.
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Lailah Gifty Akita (Think Great: Be Great! (Beautiful Quotes, #1))
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predicted a few years ago that there would be an increase in violent behavior by young females from their exposure to the bombardment of violent, female role models in the media.
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Dave Grossman (On Combat: The Psychology and Physiology of Deadly Conflict in War and Peace)
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The best model of a cat is a cat.”91 Everything else is leaving out some sort of detail.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don't)
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And only when we are proven wrong so clearly that we can no longer deny it to ourselves will we adjust our mental models of the world—producing a clearer picture of reality. Forecast,
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Philip E. Tetlock (Superforecasting: The Art and Science of Prediction)
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The brain is an organ that builds models and makes creative predictions, but its models and predictions can as easily be specious as valid. Our brains are always looking at patterns and making analogies. If correct correlations cannot be found, the brain is more than happy to accept false ones. Pseudoscience, bigotry, faith, and intolerance are often rooted in false analogy.
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Jeff Hawkins (On Intelligence: How a New Understanding of the Brain Will Lead to the Creation of Truly Intelligent Machines)
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What I’m about to tell you,” Elliott told me, “ninety-nine percent of people in the world will never understand.” For the first time all week, it was just the two of us. Elliott had told Austin he wanted to talk to me one-on-one. We were standing on a rooftop lounge during sunset, looking out at the Manhattan skyline. “You see, most people live a linear life,” he continued. “They go to college, get an internship, graduate, land a job, get a promotion, save up for a vacation each year, work toward their next promotion, and they just do that their whole lives. Their lives move step by step, slowly and predictably. “But successful people don’t buy into that model. They opt into an exponential life. Rather than going step by step, they skip steps. People say that you first need to ‘pay your dues’ and get years of experience before you can go out on your own and get what you truly want. Society feeds us this lie that you need to do x, y, and z before you can achieve your dream. It’s bullshit. The only person whose permission you need to live an exponential life is your own. “Sometimes an exponential life lands in your lap, like with a child prodigy. But most of the time, for people like you and me, we have to seize it for ourselves. If you actually want to make a difference in the world, if you want to live a life of inspiration, adventure, and wild success—you need to grab on to that exponential life—and hold on to it with all you’ve got.
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Alex Banayan (The Third Door: The Wild Quest to Uncover How the World's Most Successful People Launched Their Careers)
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A person’s “like” pattern even makes a decent proxy for intelligence—this model could reliably predict someone’s score on a standard (separately administered) IQ test, without the person answering a single direct question.
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Christian Rudder (Dataclysm: Who We Are (When We Think No One’s Looking))
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What if one were to want to hunt for these hidden presences? You can’t just rummage around like you’re at a yard sale. You have to listen. You have to pay attention. There are certain things you can’t look at directly. You need to trick them into revealing themselves. That’s what we’re doing with Walter, Jaz. We’re juxtaposing things, listening for echoes. It’s not some silly cybernetic dream of command and control, modeling the whole world so you can predict the outcome. It’s certainly not a theory of everything. I don’t have a theory of any kind. What I have is far more profound.’
‘What’s that?’
‘A sense of humor.’
Jaz looked at him, trying to find a clue in his gaunt face, in the clear gray eyes watching him with such - what? Amusement? Condescension? There was something about the man which brought on a sort of hermeneutic despair. He was a forest of signs.
‘We’re hunting for jokes.’ Bachman spoke slowly, as if to a child. ‘Parapraxes. Cosmic slips of the tongue. They’re the key to the locked door. They’ll help us discover it.’
‘Discover what?’
‘The face of God. What else would we be looking for?
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Hari Kunzru (Gods Without Men)
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The difference between the Platonic theory and the morphic-resonance hypothesis can be illustrated by analogy with a television set. The pictures on the screen depend on the material components of the set and the energy that powers it, and also on the invisible transmissions it receives through the electromagnetic field. A sceptic who rejected the idea of invisible influences might try to explain everything about the pictures and sounds in terms of the components of the set – the wires, transistors, and so on – and the electrical interactions between them. Through careful research he would find that damaging or removing some of these components affected the pictures or sounds the set produced, and did so in a repeatable, predictable way. This discovery would reinforce his materialist belief. He would be unable to explain exactly how the set produced the pictures and sounds, but he would hope that a more detailed analysis of the components and more complex mathematical models of their interactions would eventually provide the answer. Some mutations in the components – for example, by a defect in some of the transistors – affect the pictures by changing their colours or distorting their shapes; while mutations of components in the tuning circuit cause the set to jump from one channel to another, leading to a completely different set of sounds and pictures. But this does not prove that the evening news report is produced by interactions among the TV set’s components. Likewise, genetic mutations may affect an animal’s form and behaviour, but this does not prove that form and behaviour are programmed in the genes. They are inherited by morphic resonance, an invisible influence on the organism coming from outside it, just as TV sets are resonantly tuned to transmissions that originate elsewhere.
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Rupert Sheldrake (The Science Delusion: Freeing the Spirit of Enquiry (NEW EDITION))
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Machine learning takes many different forms and goes by many different names: pattern recognition, statistical modeling, data mining, knowledge discovery, predictive analytics, data science, adaptive systems, self-organizing systems, and more.
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Pedro Domingos (The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World)
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That’s why behavior-based econometric models are pretty good at predicting the near-term performance of the economy, quite bad at predicting the longer-term performance, and terrible at telling one how to improve the performance of the economy.
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Donella H. Meadows (Thinking in Systems: A Primer)
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But then human beings only understood each other in the first place by pretending. You didn't make predictions about people by modeling the hundred trillion synapses in their brain as separate objects. Ask the best social manipulator on Earth to build you an Artificial Intelligence from scratch, and they'd just give you a dumb look. You predicted people by telling your brain to act like theirs. You put yourself in their place. If you wanted to know what an angry person would do, you activated your own brain's anger circuitry, and whatever that circuitry output, that was your prediction. What did the neural circuitry for anger actually look like inside? Who knew? The best social manipulator on Earth might not know what neurons were, and neither might the best Legilimens.
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Eliezer Yudkowsky (Harry Potter and the Methods of Rationality)
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If you’re asking the schools to be the answer, you’re also asking a lot. If you take a kid from a bad background and expect the overburdened teachers to turn him around in seven hours a day, it might or might not happen. What about the other seventeen hours in a day? People often ask us if, through our research and experience, we can now predict which children are likely to become dangerous in later life. Roy Hazelwood’s answer is, “Sure. But so can any good elementary school teacher.” And if we can get them treatment early enough and intensively enough, it might make a difference. A significant role-model adult during the formative years can make a world of difference. Bill Tafoya, the special agent who served as our “futurist” at Quantico, advocated a minimum of a ten-year commitment of money and resources on the magnitude of what we sent into the Persian Gulf. He calls for a wide-scale reinstatement of Project Head Start, one of the most effective long-term, anticrime programs in history. He doesn’t think more police are the answer, but he would bring in “an army of social workers” to provide assistance for battered women, homeless families with children, to find good foster homes. And he would back it all up with tax incentive programs. I’m not sure this is the total answer, but it would certainly be an important start. Because the sad fact is, the shrinks can battle all they want, and my people and I can use psychology and behavioral science to help catch the criminals, but by the time we get to use our stuff, the severe damage has already been done.
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John E. Douglas (Mind Hunter: Inside the FBI's Elite Serial Crime Unit (Mindhunter #1))
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Most statistical models are built on the notion that there are independent variables and dependent variables, inputs and outputs, and they can be kept pretty much separate from one another.39 When it comes to the economy, they are all lumped together in one hot mess.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail-but Some Don't)
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The current crisis in particle physics springs from the fact that the theories have gone beyond the standard model in the last thirty years fall into two categories. Some were falsifiable, and they were falsified. The rest are untested-either because they make no clean predictions or because the predictions they do make are not testable with current technology. Over the last three decades, theorists have proposed at least a dozen new approaches. Each approach is motivated by a compelling hypothesis, but none has so far succeeded. In the realm of particle physics, these include Technicolor, preon models, and supersymmetry. In the realm of spacetime, they include twistor theory, causal sets, supergravity, dynamical triangulations, and loop quantum gravity. Some of these ideas are as exotic as they sound
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Lee Smolin (The Trouble with Physics: The Rise of String Theory, the Fall of a Science and What Comes Next)
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Reality is never what you imagined it would be. Sometimes it’s better. Sometimes it’s worse. And sometimes it’s just different. It’s not worth wasting time and energy trying to predict how things are going to turn out. Just go with the flow and keep your eyes and ears peeled.
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Abby Rosmarin (I'm Just Here for the Free Scrutiny: One Model's Tale of Insanity and Inanity in the Wonderful World of Fashion)
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Big data is based on the feedback economy where the Internet of Things places sensors on more and
more equipment. More and more data is being generated as medical records are digitized, more stores have loyalty cards to track consumer purchases, and people are wearing health-tracking devices. Generally, big data is more about looking at behavior, rather than monitoring transactions, which is the domain of traditional relational databases. As the cost of storage is dropping, companies track more and more data to look for patterns and build predictive models".
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Neil Dunlop
“
The assumption that economic expansion is driven by consumer demand—more consumers equals more growth—is a fundamental part of the economic theories that underlie the model. In other words, their conclusions are predetermined by their assumptions.
What the model actually tries to do is to use neoclassical economic theory to predict how much economic growth will result from various levels of population growth, and then to estimate the emissions growth that would result. Unfortunately, as Yves Smith says about financial economics, any computer model based on mainstream economic theory “rests on a seemingly rigorous foundation and elaborate math, much like astrology.”
In short, if your computer model assumes that population growth causes emissions growth, then it will tell you that fewer people will produce fewer emissions. Malthus in, Malthus out.
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Ian Angus (Too Many People?: Population, Immigration, and the Environmental Crisis)
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This example highlights two aspects of choice that the standard model of indifference curves does not predict. First, tastes are not fixed; they vary with the reference point. Second, the disadvantages of a change loom larger than its advantages, inducing a bias that favors the status quo.
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Daniel Kahneman (Thinking, Fast and Slow)
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For four decades, since my time as a graduate student, I have been preoccupied by these kinds of stories about the myriad ways in which people depart from the fictional creatures that populate economic models. It has never been my point to say that there is something wrong with people; we are all just human beings—homo sapiens. Rather, the problem is with the model being used by economists, a model that replaces homo sapiens with a fictional creature called homo economicus, which I like to call an Econ for short. Compared to this fictional world of Econs, Humans do a lot of misbehaving, and that means that economic models make a lot of bad predictions, predictions that can have much more serious consequences than upsetting a group of students. Virtually no economists saw the financial crisis of 2007–08 coming,* and worse, many thought that both the crash and its aftermath were things that simply could not happen.
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Richard H. Thaler (Misbehaving: The Making of Behavioural Economics)
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In describing how we think and decide, modern psychologists often deploy a dual-system model that partitions our mental universe into two domains. System 2 is the familiar realm of conscious thought. It consists of everything we choose to focus on. By contrast, System 1 is largely a stranger to us. It is the realm of automatic perceptual and cognitive operations—like those you are running right now to transform the print on this page into a meaningful sentence or to hold the book while reaching for a glass and taking a sip. We have no awareness of these rapid-fire processes but we could not function without them. We would shut down.
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Philip E. Tetlock (Superforecasting: The Art and Science of Prediction)
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An admonition like "The more complex you make the model, the worse the forecast gets." is equivalent to saying "Never add too much salt to the recipe." How much complexity-how much salt-did you begin with? If you want to get good at forecasting, you'll need to immerse yourself in the craft and trust your own taste buds.
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Nate Silver (The Signal and the Noise: Why So Many Predictions Fail—But Some Don't)
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However, questions arise. Are there people who aren't naive realists, or special situations in which naive realism disappears? My theory—the self-model theory of subjectivity—predicts that as soon as a conscious representation becomes opaque (that is, as soon as we experience it as a representation), we lose naive realism. Consciousness without naive realism does exist. This happens whenever, with the help of other, second-order representations, we become aware of the construction process—of all the ambiguities and dynamical stages preceding the stable state that emerges at the end. When the window is dirty or cracked, we immediately realize that conscious perception is only an interface, and we become aware of the medium itself. We doubt that our sensory organs are working properly. We doubt the existence of whatever it is we are seeing or feeling, and we realize that the medium itself is fallible. In short, if the book in your hands lost its transparency, you would experience it as a state of your mind rather than as an element of the outside world. You would immediately doubt its independent existence. It would be more like a book-thought than a book-perception. Precisely this happens in various situations—for example, In visual hallucinations during which the patient is aware of hallucinating, or in ordinary optical illusions when we suddenly become aware that we are not in immediate contact with reality. Normally, such experiences make us think something is wrong with our eyes. If you could consciously experience earlier processing stages of the representation of the book In your hands, the image would probably become unstable and ambiguous; it would start to breathe and move slightly. Its surface would become iridescent, shining in different colors at the same time. Immediately you would ask yourself whether this could be a dream, whether there was something wrong with your eyes, whether someone had mixed a potent hallucinogen into your drink. A segment of the wall of the Ego Tunnel would have lost its transparency, and the self-constructed nature of the overall flow of experience would dawn on you. In a nonconceptual and entirely nontheoretical way, you would suddenly gain a deeper understanding of the fact that this world, at this very moment, only appears to you.
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Thomas Metzinger (The Ego Tunnel: The Science of the Mind and the Myth of the Self)
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There’s good reason for such worries. About a year after Pole created his pregnancy prediction model, a man walked into a Minnesota Target and demanded to see the manager. He was clutching an advertisement. He was very angry. “My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?” The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture, and pictures of smiling infants gazing into their mothers’ eyes. The manager apologized profusely, and then called, a few days later, to apologize again. The father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of.” He took a deep breath. “She’s due in August. I owe you an apology.
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Charles Duhigg (The Power of Habit: Why We Do What We Do and How to Change)
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The hypothesis advanced by the propaganda model, excluded from debate as unthinkable, is that in dealing with the American wars in Indochina, the media were "unmindful", but highly "patriotic" in the special and misleading sense that they kept -- and keep -- closely to the perspective of official Washington and the closely related corporate elite, in conformity to the general "journalistic-literary-political culture" from which "the left" (meaning dissident opinion that questions jingoist assumptions) is virtually excluded. The propaganda model predicts that this should be generally true not only of the choice of topics covered and the way they are covered, but also, and far more crucially, of the general background of the presuppositions within which the issues are framed and the news presented. Insofar as there is debate among dominant elites, it will be reflected within the media, which in this narrow sense, may adopt an "adversarial stance" with regard to those holding office, reflecting elite dissatisfaction with current policy. Otherwise the media will depart from elite consensus only rarely and in limited ways. Even when large parts of the general public break free of the premises of the doctrinal system, as finally happened during the Indochina wars, real understanding based upon an alternative conception of the evolving history can be developed only with considerable effort by the most diligent and skeptical. And such understanding as can be reached through serious and often individual effort will be difficult to sustain or apply elsewhere, an extremely important matter for those who are truly concerned with democracy at home and "the influence of democracy abroad," in the real sense of these words.
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Noam Chomsky (Manufacturing Consent: The Political Economy of the Mass Media)
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Roney (2003) hypothesized that mere exposure to attractive women would activate cognitive adaptations in men designed to embody the qualities that women want in a mate. Specifically, he predicted that exposure to young attractive women would (1) increase the importance men place on their own financial success, (2) experience feeling more ambitious, and (3) produce self-descriptions that correspond to what women want. Using a cover story to disguise the purpose of the study, Roney had one group of men rate the effectiveness of advertisements containing young, attractive models and another group of men rate the effectiveness of ads containing older, less-attractive models. Following this exposure, the men responded to the key measures to test his hypotheses.
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David M. Buss (Evolutionary Psychology: The New Science of the Mind)
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The difference between human dynamics and data mining boils down to this: Data mining predicts our behaviors based on records of our patterns of activity; we don't even have to understand the origins of the patterns exploited by the algorithm. Students of human dynamics, on the other hand, seek to develop models and theories to explain why, when, and where we do the things we do with some regularity.
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Albert-László Barabási (Bursts: The Hidden Pattern Behind Everything We Do)
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Although Jung's concept of a collective unconscious has had an enormous impact on psychology and is now embraced by untold thousands of psychologists and psychiatrists, our current understanding of the universe provides no mechanism for explaining its existence. The interconnectedness of all things predicted by the holographic model, however, does offer an explanation. In a universe in which all things are infinitely interconnected, all consciousnesses are also interconnected. Despite appearances, we are beings without borders. Or as Bohm puts it, "Deep down the consciousness of mankind is one. "1 If each of us has access to the unconscious knowledge of the entire human race, why aren't we all walking encyclopedias? Psychologist Robert M. Anderson, Jr., of the Rensselaer Polytechnic Institute in Troy, New York, believes it is because we are only able to tap into information in the implicate order that is directly relevant to our memories. Anderson calls this selective process personal resonance and likens it to the fact that a vibrating tuning fork will resonate with (or set up a vibration in) another tuning fork only if the second tuning fork possesses a similar structure, shape, and size. "Due to personal resonance, relatively few of the almost infinite variety of 'images' in the implicate holographic structure of the universe are available to an individual's personal consciousness, " says Anderson. "Thus, when enlightened persons glimpsed this unitive consciousness centuries ago, they did not write out relativity theory because they were not studying physics in a context similar to that in which Einstein studied physics.
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Michael Talbot (The Holographic Universe)
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My favorite chick was the tawny-colored Buff Orpington. She promised to one day be a bodacious plus-sized model of a chicken, wearing fluffy pantaloons under full feathery skirts and with as charming a personality as her appearance suggested. Predictably named Buffy, she didn’t mind being handled and rather seemed to enjoy the company, clucking softly with a closed beak as I picked her up and stroked her silky feathers.
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Lucie B. Amundsen (Locally Laid: How We Built a Plucky, Industry-changing Egg Farm - from Scratch)
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Eventually, the performance of a classifier, computational power as well as predictive power, depends heavily on the underlying data that are available for learning. The five main steps that are involved in training a machine learning algorithm can be summarized as follows: Selection of features. Choosing a performance metric. Choosing a classifier and optimization algorithm. Evaluating the performance of the model. Tuning the algorithm.
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Sebastian Raschka (Python Machine Learning: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics)
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we map things, he said, and chart things, observing and modeling and predicting, because we have no other choice, and this is the language we have agreed, collectively, to use. Because we have agreed, collectively, that to proceed without knowledge or understanding is a stupid kind of bravery, an impulsive kind of blindness, but that to be alone without wonder or curiosity is to chip away any possible value we might discover in existing.
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Olivie Blake (Alone With You in the Ether)
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In the first case it emerges that the evidence that might refute a theory can often be unearthed only with the help of an incompatible alternative: the advice (which goes back to Newton and which is still popular today) to use alternatives only when refutations have already discredited the orthodox theory puts the cart before the horse. Also, some of the most important formal properties of a theory are found by contrast, and not by analysis. A scientist who wishes to maximize the empirical content of the views he holds and who wants to understand them as clearly as he possibly can must therefore introduce other views; that is, he must adopt a pluralistic methodology. He must compare ideas with other ideas rather than with 'experience' and he must try to improve rather than discard the views that have failed in the competition. Proceeding in this way he will retain the theories of man and cosmos that are found in Genesis, or in the Pimander, he will elaborate them and use them to measure the success of evolution and other 'modern' views. He may then discover that the theory of evolution is not as good as is generally assumed and that it must be supplemented, or entirely replaced, by an improved version of Genesis. Knowledge so conceived is not a series of self-consistent theories that converges towards an ideal view; it is not a gradual approach to truth. It is rather an ever increasing ocean of mutually incompatible alternatives, each single theory, each fairy-tale, each myth that is part of the collection forcing the others in greater articulation and all of them contributing, via this process of competition, to the development of our consciousness. Nothing is ever settled, no view can ever be omitted from a comprehensive account. Plutarch or Diogenes Laertius, and not Dirac or von Neumann, are the models for presenting a knowledge of this kind in which the history of a science becomes an inseparable part of the science itself - it is essential for its further development as well as for giving content to the theories it contains at any particular moment. Experts and laymen, professionals and dilettani, truth-freaks and liars - they all are invited to participate in the contest and to make their contribution to the enrichment of our culture. The task of the scientist, however, is no longer 'to search for the truth', or 'to praise god', or 'to synthesize observations', or 'to improve predictions'. These are but side effects of an activity to which his attention is now mainly directed and which is 'to make the weaker case the stronger' as the sophists said, and thereby to sustain the motion of the whole.
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Paul Karl Feyerabend (Against Method)
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How well our models fit the real world is of great importance. If our models are poor, we will make bad predictions about the future and subsequently bad choices. Poor models of reality may be caused by many things: not having enough information, difficulty with abstract thinking, or the stubborn persistence of wrong assumptions. Such bad assumptions may be so harmful that they lead to psychiatric illnesses such as anxiety and depression.
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Daniel Z. Lieberman (The Molecule of More: How a Single Chemical in Your Brain Drives Love, Sex, and Creativity―and Will Determine the Fate of the Human Race)
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At a higher level of abstraction, the behavioral correlates of life history strategies can be framed within the five-factor model of personality. Among the Big Five, agreeableness and conscientiousness show the most consistent pattern of associations with slow traits such as restricted sociosexuality, long-term mating orientation, couple stability, secure attachment to parents in infancy and romantic partners in adulthood, reduced sex drive, low impulsivity, and risk aversion across domains. Conscientiousness and (to a smaller extent) agreeableness are also the most reliable personality predictors of physical health and longevity; the contribution of neuroticism is mixed and may depend on the specific facets considered. The life history correlates of neuroticism are much less straightforward; for example, high neuroticism tends to predict increased short-term mating in women but reduced short-term mating in men, with much cross-cultural variation. There is also evidence that slow life history–related traits can be associated with social anxiety and insecurity, which is consistent with a general profile of risk aversion and behavioral inhibition. As a first approximation, then, metatrait alpha can be treated as a broadband correlate of slow strategies, with the caveat that neuroticism may be elevated at both ends of the continuum.
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Marco del Giudice (Evolutionary Psychopathology: A Unified Approach)
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In the history of science we have discovered a sequence of better and better theories or models, from Plato to the classical theory of Newton to modern quantum theories. It is natural to ask: Will this sequence eventually reach an end point, an ultimate theory of the universe, that will include all forces and predict every observation we can make, or will we continue forever finding better theories, but never one that cannot be improved upon? We do not yet have a definitive answer to this question, but we now have a candidate for the ultimate theory of everything, if indeed one exists, called M-theory. M-theory is the only model that has all the properties we think the final theory ought to have, and it is the theory upon which much of our later discussion is based.
M-theory is not a theory in the usual sense. It is a whole family of different theories, each of which is a good description of observations only in some range of physical situations.
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Stephen Hawking (The Grand Design)
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Most decisions, and nearly all human interaction, can be incorporated into a contingencies model. For example, a President may start a war, a man may sell his business, or divorce his wife. Such an action will produce a reaction; the number of reactions is infinite but the number of probable reactions is manageably small. Before making a decision, an individual can predict various reactions, and he can assess his original, or primary-mode, decision more effectively. But there is also a category which cannot be analyzed by contingencies. This category involves events and situations which are absolutely unpredictable, not merely disasters of all sorts, but those also including rare moments of discovery and insight, such as those which produced the laser, or penicillin. Because these moments are unpredictable, they cannot be planned for in any logical manner. The mathematics are wholly unsatisfactory. We may only take comfort in the fact that such situations, for ill or for good, are exceedingly rare.
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Michael Crichton (The Andromeda Strain)
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I have used the theologians and their treatment of apocalypse as a model of what we might expect to find not only in more literary treatments of the same radical fiction, but in the literary treatment of radical fictions in general. The assumptions I have made in doing so I shall try to examine next time. Meanwhile it may be useful to have some kind of summary account of what I've been saying. The main object: is the critical business of making sense of some of the radical ways of making sense of the world. Apocalypse and the related themes are strikingly long-lived; and that is the first thing to say tbout them, although the second is that they change. The Johannine acquires the characteristics of the Sibylline Apocalypse, and develops other subsidiary fictions which, in the course of time, change the laws we prescribe to nature, and specifically to time. Men of all kinds act, as well as reflect, as if this apparently random collocation of opinion and predictions were true. When it appears that it cannot be so, they act as if it were true in a different sense. Had it been otherwise, Virgil could not have been altissimo poeta in a Christian tradition; the Knight Faithful and True could not have appeared in the opening stanzas of "The Faerie Queene". And what is far more puzzling, the City of Apocalypse could not have appeared as a modern Babylon, together with the 'shipmen and merchants who were made rich by her' and by the 'inexplicable splendour' of her 'fine linen, and purple and scarlet,' in The Waste Land, where we see all these things, as in Revelation, 'come to nought.' Nor is this a matter of literary allusion merely. The Emperor of the Last Days turns up as a Flemish or an Italian peasant, as Queen Elizabeth or as Hitler; the Joachite transition as a Brazilian revolution, or as the Tudor settlement, or as the Third Reich. The apocalyptic types--empire, decadence and renovation, progress and catastrophe--are fed by history and underlie our ways of making sense of the world from where we stand, in the middest.
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Frank Kermode (The Sense of an Ending: Studies in the Theory of Fiction)
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If a model did anything too obviously bizarre—flooded the Sahara or tripled interest rates—the programmers would revise the equations to bring the output back in line with expectation. In practice, econometric models proved dismally blind to what the future would bring, but many people who should have known better acted as though they believed in the results. Forecasts of economic growth or unemployment were put forward with an implied precision of two or three decimal places. Governments and financial institutions paid for such predictions and acted on them, perhaps out of necessity or for want of anything better. Presumably they knew that such variables as “consumer optimism” were not as nicely measurable as “humidity” and that the perfect differential equations had not yet been written for the movement of politics and fashion. But few realized how fragile was the very process of modeling flows on computers, even when the data was reasonably trustworthy and the laws were purely physical, as in weather forecasting.
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James Gleick (Chaos: Making a New Science)
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System 1 is generally very good at what it does: its models of familiar situations are accurate, its short-term predictions are usually accurate as well, and its initial reactions to challenges are swift and generally appropriate. System 1 has biases, however, systematic errors that it is prone to make in specified circumstances. As we shall see, it sometimes answers easier questions than the one it was asked, and it has little understanding of logic and statistics. One further limitation of System 1 is that it cannot be turned off.
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Daniel Kahneman (Thinking, Fast and Slow)
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Although cascading failures may appear random and unpredictable,
they follow reproducible laws that can be quantified and even predicted using the tools of network science.
First, to avoid damaging cascades, we must understand the structure of the network on which the cascade propagates. Second, we must be able
to model the dynamical processes taking place on these networks, like the flow of electricity. Finally, we need to uncover how the interplay between
the network structure and dynamics affects the robustness of the whole system.
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Albert-László Barabási (Network Science)
“
There is nothing that the media could say to me that would justify the way they’ve acted. You can hound me. You can follow me, but in no way should you frighten those around me. To harm my wife and potentially harm my daughter—there is no excuse that could put any of you on the right side of morality. I met Rose when I was fifteen and she was fourteen, and through what she would call fate and I’d call circumstance of our hobbies, we’d cross paths dozens of times over the course of a decade. At seventeen, I attended the same national Model UN conference as Rose, and a delegate for Greenland locked us in a janitorial closet. He also stole our phones. He had to beat us dishonorably because he couldn’t beat us any other way. Rose said being locked in a confined space with me was the worst two hours of her life" They look bemused, brows furrowing. I can’t help but smile.
“You’re confused because you don’t know whether she was exaggerating or whether she was being truthful. But the truth is that we are complex people with the ability to love to hate and to hate to love, and I wouldn’t trade her for any other person. So that day, stuck beside mops and dirtied towels, I could’ve picked the lock five minutes in and let her go. Instead, I purposefully spent two hours with a girl who wore passion like a dress made of diamonds and hair made of flames. Every day of my life, I am enamored. Every day of my life, I am bewitched. And every day of my life, I spend it with her.”
My chest swells with more power, lifting me higher.
“I’ve slept with many different kinds of people, and yes, the three that spoke to the press are among them. Rose is the only person I’ve ever loved, and through that love, we married and started a family. There is no other meaning behind this, and for you to conjure one is nothing less than a malicious attack against my marriage and my child. Anything else has no relevance. I can’t be what you need me to be. So you’ll have to accept this version or waste your time questioning something that has no answer. I know acceptance isn’t easy when you’re unsure of what you’re accepting, but all I can say is that you’re accepting me as me. I leave them with a quote from Sylvia Plath.
“‘I took a deep breath and listened to the old brag of my heart.’” My lips pull higher, into a livelier smile. “‘I am, I am, I am.’”
With this, I step away from the podium, and I exit to a cacophony of journalists shouting and asking me to clarify.
Adapt to me.
I’m satisfied, more than I even predicted.
Some people will rewind this conference on their television, to listen closely and try to understand me. I don’t need their understanding, but my daughter will—and I hope the minds of her peers are wide open with vibrant hues of passion.
I hope they all paint the world with color.
”
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Krista Ritchie (Fuel the Fire (Calloway Sisters #3))
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What, then, can Shakespearean tragedy, on this brief view, tell us about human time in an eternal world? It offers imagery of crisis, of futures equivocally offered, by prediction and by action, as actualities; as a confrontation of human time with other orders, and the disastrous attempt to impose limited designs upon the time of the world. What emerges from Hamlet is--after much futile, illusory action--the need of patience and readiness. The 'bloody period' of Othello is the end of a life ruined by unseasonable curiosity. The millennial ending of Macbeth, the broken apocalypse of Lear, are false endings, human periods in an eternal world. They are researches into death in an age too late for apocalypse, too critical for prophecy; an age more aware that its fictions are themselves models of the human design on the world. But it was still an age which felt the human need for ends consonant with the past, the kind of end Othello tries to achieve by his final speech; complete, concordant. As usual, Shakespeare allows him his tock; but he will not pretend that the clock does not go forward. The human perpetuity which Spenser set against our imagery of the end is represented here also by the kingly announcements of Malcolm, the election of Fortinbras, the bleak resolution of Edgar.
In apocalypse there are two orders of time, and the earthly runs to a stop; the cry of woe to the inhabitants of the earth means the end of their time; henceforth 'time shall be no more.' In tragedy the cry of woe does not end succession; the great crises and ends of human life do not stop time. And if we want them to serve our needs as we stand in the middest we must give them patterns, understood relations as Macbeth calls them, that defy time. The concords of past, present, and future towards which the soul extends itself are out of time, and belong to the duration which was invented for angels when it seemed difficult to deny that the world in which men suffer their ends is dissonant in being eternal. To close that great gap we use fictions of complementarity. They may now be novels or philosophical poems, as they once were tragedies, and before that, angels.
What the gap looked like in more modern times, and how more modern men have closed it, is the preoccupation of the second half of this series.
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Frank Kermode (The Sense of an Ending: Studies in the Theory of Fiction)
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Aided by the advancement and increasing use of AI, the human mind is accessing new vistas, bringing previously unattainable goals within sight. These include models with which to predict and mitigate natural disasters, deeper knowledge of mathematics, and fuller understanding of the universe and the reality in which it resides. But these and other possibilities are being purchased — largely without fanfare — by altering the human relationship with reason and reality. This is a revolution for which existing philosophical concepts and societal institutions leave us largely unprepared.
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Daniel Huttenlocher (The Age of AI and Our Human Future)
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Why are the fundamental laws as we have described them? The ultimate theory must be consistent and must predict finite results for quantities that we can measure. We’ve seen that there must be a law like gravity, and we saw in Chapter 5 that for a theory of gravity to predict finite quantities, the theory must have what is called supersymmetry between the forces of nature and the matter on which they act. M-theory is the most general supersymmetric theory of gravity. For these reasons M-theory is the only candidate for a complete theory of the universe. If it is finite—and this has yet to be proved—it will be a model of a universe that creates itself. We must be part of this universe, because there is no other consistent model.
M-theory is the unified theory Einstein was hoping to find. The fact that we human beings—who are ourselves mere collections of fundamental particles of nature—have been able to come this close to an understanding of the laws governing us and our universe is a great triumph. But perhaps the true miracle is that abstract considerations of logic lead to a unique theory that predicts and describes a vast universe full of the amazing variety that we see. If the theory is confirmed by observation, it will be the successful conclusion of a search going back more than 3,000 years. We will have found the grand design.
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Stephen Hawking (The Grand Design)
“
In Webvan’s case premature scaling was an integral part of the company culture and the prevailing venture capital “get big fast” mantra. Webvan spent $18 million to develop proprietary software and $40 million to set up its first automated warehouse before it had shipped a single item. Premature scaling had dire consequences since Webvan’s spending was on a scale that ensures it will be taught in business school case studies for years to come. As customer behavior continued to differ from the predictions in Webvan’s business plan, the company slowly realized it had overbuilt and over-designed. The business model made sense only at the high volumes predicted on the spreadsheet.
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Steve Blank (The Four Steps to the Epiphany: Successful Strategies for Startups That Win)
“
The same kind of situation complicates many public debates, like that over global warming. Many scientists predict that altered atmospheric conditions will raise the average global temperature by several degrees. But such changes can also cause extreme weather, which may mean worse snowstorms in the southern United States. Global warming may alter ocean currents like the Gulf Stream and ultimately turn northern Europe into a much colder Siberian-type icebox. Anomalies like this fuel the global warming naysayers: scientists say the world is getting hotter, but you’ve just suffered through the biggest snowstorm in your region’s history. How should you respond? A judicious response is that nature is amazing—rich, varied, complex, and intricately interconnected, with a messy, long history. Anomalies, whether in planetary orbits or North American weather, are not just inconvenient details to brush aside: they are the very essence of understanding what really happened—how things really work. We develop grand and general models of how nature works, and then we use the odd details to refine the original imperfect model (or if the exceptions overwhelm the rule, we regroup around a new model). That’s why good scientists revel in anomalies. If we understood everything, if we could predict everything, there’d be no point in getting up in the morning and heading to the lab.
”
”
Robert M. Hazen (The Story of Earth: The First 4.5 Billion Years, from Stardust to Living Planet)
“
Why don't you make everybody an Alpha Double Plus while you're about it?"
Mustapha Mond laughed. "Because we have no wish to have our throats cut," he answered. "We believe in happiness and stability. A society of Alphas couldn't fail to be unstable and miserable. Imagine a factory staffed by Alphas–that is to say by separate and unrelated individuals of good heredity and conditioned so as to be capable (within limits) of making a free choice and assuming responsibilities. Imagine it!" he repeated.
The Savage tried to imagine it, not very successfully.
"It's an absurdity. An Alpha-decanted, Alpha-conditioned man would go mad if he had to do Epsilon Semi-Moron work–go mad, or start smashing things up. Alphas can be completely socialized–but only on condition that you make them do Alpha work. Only an Epsilon can be expected to make Epsilon sacrifices, for the good reason that for him they aren't sacrifices; they're the line of least resistance. His conditioning has laid down rails along which he's got to run. He can't help himself; he's foredoomed. Even after decanting, he's still inside a bottle–an invisible bottle of infantile and embryonic fixations. Each one of us, of course," the Controller meditatively continued, "goes through life inside a bottle. But if we happen to be Alphas, our bottles are, relatively speaking, enormous. We should suffer acutely if we were confined in a narrower space. You cannot pour upper-caste champagne-surrogate into lower-caste bottles. It's obvious theoretically. But it has also been proved in actual practice. The result of the Cyprus experiment was convincing."
"What was that?" asked the Savage.
Mustapha Mond smiled. "Well, you can call it an experiment in rebottling if you like. It began in A.F. 473. The Controllers had the island of Cyprus cleared of all its existing inhabitants and re-colonized with a specially prepared batch of twenty-two thousand Alphas. All agricultural and industrial equipment was handed over to them and they were left to manage their own affairs. The result exactly fulfilled all the theoretical predictions. The land wasn't properly worked; there were strikes in all the factories; the laws were set at naught, orders disobeyed; all the people detailed for a spell of low-grade work were perpetually intriguing for high-grade jobs, and all the people with high-grade jobs were counter-intriguing at all costs to stay where they were. Within six years they were having a first-class civil war. When nineteen out of the twenty-two thousand had been killed, the survivors unanimously petitioned the World Controllers to resume the government of the island. Which they did. And that was the end of the only society of Alphas that the world has ever seen."
The Savage sighed, profoundly.
"The optimum population," said Mustapha Mond, "is modelled on the iceberg–eight-ninths below the water line, one-ninth above."
"And they're happy below the water line?"
"Happier than above it.
”
”
Aldous Huxley (Brave New World)
“
VaR has been called “potentially catastrophic,” “a fraud,” and many other things not fit for a family book about statistics like this one. In particular, the model has been blamed for the onset and severity of the financial crisis. The primary critique of VaR is that the underlying risks associated with financial markets are not as predictable as a coin flip or even a blind taste test between two beers. The false precision embedded in the models created a false sense of security. The VaR was like a faulty speedometer, which is arguably worse than no speedometer at all. If you place too much faith in the broken speedometer, you will be oblivious to other signs that your speed is unsafe. In contrast, if there is no speedometer at all, you have no choice but to look around for clues as to how fast you are really going.
”
”
Charles Wheelan (Naked Statistics: Stripping the Dread from the Data)
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But what separates human consciousness from the consciousness of animals? Humans are alone in the animal kingdom in understanding the concept of tomorrow. Unlike animals, we constantly ask ourselves “What if?” weeks, months, and even years into the future, so I believe that Level III consciousness creates a model of its place in the world and then simulates it into the future, by making rough predictions. We can summarize this as follows: Human consciousness is a specific form of consciousness that creates a model of the world and then simulates it in time, by evaluating the past to simulate the future. This requires mediating and evaluating many feedback loops in order to make a decision to achieve a goal. By the time we reach Level III consciousness, there are so many feedback loops that we need a CEO to sift through them in order to simulate the future and make a final decision. Accordingly, our brains differ from those of other animals, especially in the expanded prefrontal cortex, located just behind the forehead, which allows us to “see” into the future. Dr. Daniel Gilbert, a Harvard psychologist, has written, “The greatest achievement of the human brain is its ability to imagine objects and episodes that do not exist in the realm of the real, and it is this ability that allows us to think about the future. As one philosopher noted, the human brain is an ‘anticipation machine,’ and ‘making the future’ is the most important thing it does.” Using brain scans, we can even propose a candidate for the precise area of the brain where simulation of the future takes place. Neurologist Michael Gazzaniga notes that “area 10 (the internal granular layer IV), in the lateral prefrontal cortex, is almost twice as large in humans as in apes. Area 10 is involved with memory and planning, cognitive flexibility, abstract thinking, initiating appropriate behavior, and inhibiting inappropriate behavior, learning rules, and picking out relevant information from what is perceived through the senses.” (For this book, we will refer to this area, in which decision making is concentrated, as the dorsolateral prefrontal cortex, although there is some overlap with other areas of the brain.)
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Michio Kaku (The Future of the Mind: The Scientific Quest to Understand, Enhance, and Empower the Mind)
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Roughly 25 percent of humanity is Muslim. For every Jew, there are roughly one hundred twenty-five Muslims. Judaism is about 2500 years older than Islam, and yet it has not been able to attract nearly as many followers. If we construe religions as memeplexes (a collection of interconnected memes), to borrow Richard Dawkin's term, the Islamic memeplex has been extraordinarily more successful than its Jewish counterpart (from an epidemiological perspective, that is). Why is that? To answer this important question, we must look at the contents of the two respective memeplexes to examine why one is more "infectious" than the other. Let us explore the rules for converting into the two religions and apostatizing out of them. In Judaism, the religious process for conversion is onerous, requiring several years of commitment and an absence of ulterior motive. (For example, converting to Judaism because you are marrying a Jewish person is considered an ulterior motive). Not surprisingly, given the barriers to entry, relatively few people convert to Judaism. On the other hand, to convert to Islam simply requires that one proclaim openly the sentence, the shahada (the testimony): "There is no true god but Allah, and Muhammad is the Messenger of Allah." It does not require a sophisticated epidemiological model to predict which memeplex will spread more rapidly. Let us now suppose that one wishes to leave the religion. While the Old Testament does mention the death penalty for apostasy, it has seldom been applied throughout Jewish history, whereas to this day apostasy from Islam does lead to the death penalty in several Islamic countries. But perhaps the most important difference is that Judaism does not promote or encourage proselytizing, whereas it is a central religious obligation in Islam. According to Islam, the world is divided into dar al-hard (the house of war) and dar al-Islam (the house of Islam). Peace will arrive when the entire world is united under the flag of Allah. Hence, it is imperative to Islamize the nations within dar al-harb. There is only one Jewish country in the world, Israel, and it has a sizeable non-Jewish minority. But there are fifty-seven member states of the Organization of Islamic Cooperation.
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Gad Saad (Parasitic Mind: How Infectious Ideas Are Killing Common Sense)
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Determinism is appealing because it implies that our world and our beliefs are a natural and inevitable product of history. It is natural and inevitable that we live in nation states, organise our economy along capitalist principles, and fervently believe in human rights. To acknowledge that history is not deterministic is to acknowledge that it is just a coincidence that most people today believe in nationalism, capitalism and human rights. History cannot be explained deterministically and it cannot be predicted because it is chaotic. So many forces are at work and their interactions are so complex that extremely small variations in the strength of the forces and the way they interact produce huge differences in outcomes. Not only that, but history is what is called a ‘level two’ chaotic system. Chaotic systems come in two shapes. Level one chaos is chaos that does not react to predictions about it. The weather, for example, is a level one chaotic system. Though it is influenced by myriad factors, we can build computer models that take more and more of them into consideration, and produce better and better weather forecasts.
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Yuval Noah Harari (Sapiens and Homo Deus: The E-book Collection: A Brief History of Humankind and A Brief History of Tomorrow)
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In Haraway’s work, queering animals means not only showing that animals sometimes have unreproductive sex. It means showing the political value of unhinging animality from its heretofore seamless relationship to the concept of a ‘nature’ that is stable, predictable, and controllable.
Feminism has barely begun to denaturalize or queer animal sexualities. For instance, Carol Adams persuasively argues that the sexual objectification and consumption of animals and of women follow the same models…She proposes that feminism approach the animalizing of women and the feminization of animals in patriarchal culture as a unique opportunity, namely the chance to study the oppression of animals as a particular symptom of androcentric social organization. However, Adams’s work on the visual culture aspect of meat consumption is devoted to exposing the logic and structure of a pattern of oppression and exploitation, a position depending on one important assumption: that humans are the only actors in this practice. The structure of her argument makes power and privilege pretty unambiguously distinguishable from subjugation. In that sense, it offers rather limited resources for a post- or neo-Foucauldian feminist analysis of power, desire, and norms, the production of truths and practices, and the complexities of self-care.
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Margret Grebowicz (Beyond the Cyborg: Adventures with Donna Haraway)
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If dimensions are virtual like the particles in quantum foam are virtual then, entanglement is information that is in more than one location (hologram).
There are no particles, they may be wave packets but the idea of quantum is, a precise ratio of action in relationship to the environment.
Feynman's path integral is not infinite, it is fractal.
If you look at a star many light years away, the photon that hits your eye leaves the star precisely when the timing for the journey will end at your eye because the virtual dimension of the journey is zero distance or zero time. Wheeler said that if your eye is not there to receive the photon then it won't leave the star in the distant past. If the dimension in the direction of travel is zero, you have a different relationship then if it is zero time in terms of the property of the virtual dimensions.
Is a particle really a wave packet?
Could something like a "phase transition" involve dimensions that are more transitory then we imagined.
Example; a photon as a two dimensional sheet is absorbed by an electron so that the photon becomes a part of the geometry of the electron in which the electrons dimensions change in some manner.
Could "scale" have more variation and influence on space and time that our models currently predict?
Could information, scale, and gravity be intimately related?
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R.A. Delmonico
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The attachment voids experienced by immigrant children are profound. The hardworking parents are focused on supporting their families economically and, unfamiliar with the language and customs of their new society, they are not able to orient their children with authority or confidence. Peers are often the only people available for such children to latch on to. Thrust into a peer-oriented culture, immigrant families may quickly disintegrate. The gulf between child and parent can widen to the point that becomes unbridgeable. Parents of these children lose their dignity, their power, and their lead.
Peers ultimately replace parents and gangs increasingly replace families. Again, immigration or the necessary relocation of people displaced by war or economic misery is not the problem. Transplanted to peer-driven North American society, traditional cultures succumb. We fail our immigrants because
of our own societal failure to preserve the child-parent relationship. In some parts of the country one still sees families, often from Asia, join together in multigenerational groups for outings. Parents, grandparents, and even frail great-grandparents mingle, laugh, and socialize with their children and their
children's offspring. Sadly, one sees this only among relatively recent immigrants.
As youth become incorporated into North American society, their connections with their elders fade. They distance themselves from their families. Their icons become the artificially created and hypersexualized figures mass-marketed by Hollywood and the U.S. music industry. They rapidly become alienated from the cultures that have sustained their ancestors for generation after generation. As we observe the rapid dissolution of immigrant families under the influence of the peer-oriented society, we witness, as if on fast-forward video, the cultural meltdown we ourselves have suffered in the past half century. It would be encouraging to believe that other parts of the world will successfully resist the trend toward peer orientation. The opposite is likely to be the case as the global economy exerts its corrosive influences on traditional cultures on other continents.
Problems of teenage alienation are now widely encountered in countries that have most closely followed upon the American model — Britain, Australia, and Japan. We may predict similar patterns elsewhere to result from economic changes and massive population shifts. For example, stress-related disorders are proliferating among Russian children. According to a report in the New York Times, since the collapse of the Soviet Union a little over a decade ago, nearly a third of Russia's estimated 143 million people — about 45 million — have changed residences. Peer orientation threatens to become one of the least welcome of all American cultural exports.
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Gabor Maté (Hold On to Your Kids: Why Parents Need to Matter More Than Peers)
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the present grandeur and prospective pre-eminence of that glorious American Republic, in which Europe enviously seeks its model and tremblingly foresees its doom. Selecting for an example of the social life of the United States that city in which progress advances at the fastest rate, I indulged in an animated description of the moral habits of New York. Mortified to see, by the faces of my listeners, that I did not make the favourable impression I had anticipated, I elevated my theme; dwelling on the excellence of democratic institutions, their promotion of tranquil happiness by the government of party, and the mode in which they diffused such happiness throughout the community by preferring, for the exercise of power and the acquisition of honours, the lowliest citizens in point of property, education, and character. Fortunately recollecting the peroration of a speech, on the purifying influences of American democracy and their destined spread over the world, made by a certain eloquent senator (for whose vote in the Senate a Railway Company, to which my two brothers belonged, had just paid 20,000 dollars), I wound up by repeating its glowing predictions of the magnificent future that smiled upon mankind—when the flag of freedom should float over an entire continent, and two hundred millions of intelligent citizens, accustomed from infancy to the daily use of revolvers, should apply to a cowering universe the doctrine of the Patriot Monroe.
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Edward Bulwer-Lytton (The Coming Race)
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Although a youth culture was in evidence by the 1950s, the first obvious and dramatic manifestation of a culture generated by peer-orientation was the hippie counterculture of the 1960s and 1970s. The Canadian media theorist Marshall McLuhan called it “the new tribalism of the Electric Age.” Hair and dress and music played a significant part in shaping this culture, but what defined it more than anything was its glorification of the peer attachment that gave rise to it. Friends took precedence over family. Physical contact and connection with peers were pursued; the brotherhood of the pop tribe was declared, as in the generation-based “Woodstock nation.” The peer group was the true home.
“Don't trust anyone over thirty” became the byword of youth who went far beyond a healthy critique of their elders to a militant rejection of tradition. The degeneration of that culture into alienation and drug use, on the one hand, and its co-optation for commercial purposes by the very mainstream institutions it was rebelling against were almost predictable. The wisdom of well-seasoned cultures has accumulated over hundreds and sometimes thousands of years. Healthy cultures also contain rituals and customs and ways of doing things that protect us from ourselves and safeguard values important to human life, even when we are not conscious of what such values are.
An evolved culture needs to have some art and music that one can grow into, symbols that convey deeper meanings to existence and models that inspire greatness. Most important of all, a culture must protect its essence and its ability to reproduce itself — the attachment of children to their parents. The culture generated by peer orientation contains no wisdom, does not protect its members from themselves, creates only fleeting fads, and worships idols hollow of value or meaning. It symbolizes only the undeveloped ego of callow youth and destroys child-parent attachments.
We may observe the cheapening of cultural values with each new peer-oriented generation. For all its self-delusion and smug isolation from the adult world, the Woodstock “tribe” still embraced universal values of peace, freedom, and brotherhood. Today's mass musical gatherings are about little more than style, ego, tribal exuberance, and dollars.
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Gabor Maté (Hold On to Your Kids: Why Parents Need to Matter More Than Peers)
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Unlike classically spinning bodies, such as tops, however, where the spin rate can assume any value fast or slow, electrons always have only one fixed spin. In the units in which this spin is measured quantum mechanically (called Planck's constant) the electrons have half a unit, or they are "spin-1/2" particles. In fact, all the matter particles in the standard model-electrons, quarks, neutrinos, and two other types called muons and taus-all have "spin 1/2." Particles with half-integer spin are known collectively as fermions (after the Italian physicist Enrico Fermi). On the other hand, the force carriers-the photon, W, Z, and gluons-all have one unit of spin, or they are "spin-1" particles in the physics lingo. The carrier of gravity-the graviton-has "spin 2," and this was precisely the identifying property that one of the vibrating strings was found to possess. All the particles with integer units of spin are called bosons (after the Indian physicist Satyendra Bose). Just as ordinary spacetime is associated with a supersymmetry that is based on spin. The predictions of supersymmetry, if it is truly obeyed, are far-reaching. In a universe based on supersymmetry, every known particle in the universe must have an as-yet undiscovered partner (or "superparrtner"). The matter particles with spin 1/2, such as electrons and quarks, should have spin 0 superpartners. the photon and gluons (that are spin 1) should have spin-1/2 superpartners called photinos and gluinos respectively. Most importantly, however, already in the 1970s physicists realized that the only way for string theory to include fermionic patterns of vibration at all (and therefore to be able to explain the constituents of matter) is for the theory to be supersymmetric. In the supersymmetric version of the theory, the bosonic and fermionic vibrational patters come inevitably in pairs. Moreover, supersymmetric string theory managed to avoid another major headache that had been associated with the original (nonsupersymmetric) formulation-particles with imaginary mass. Recall that the square roots of negative numbers are called imaginary numbers. Before supersymmetry, string theory produced a strange vibration pattern (called a tachyon) whose mass was imaginary. Physicists heaved a sigh of relief when supersymmetry eliminated these undesirable beasts.
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Mario Livio (The Equation That Couldn't Be Solved: How Mathematical Genius Discovered the Language of Symmetry)
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To a theoretician, all these criticisms are troublesome but not fatal. But what does cause problems for a theoretician is that the model seems to predict a multiverse of parallel universes, many of which are crazier than those in the imagination of a Hollywood scriptwriter. String theory has an infinite number of solutions, each describing a perfectly well-behaved finite theory of gravity, which do not resemble our universe at all. In many of these parallel universes, the proton is not stable, so it would decay into a vast cloud of electrons and neutrinos. In these universes, complex matter as we know it (atoms and molecules) cannot exist. They only consist of a gas of subatomic particles. (Some might argue that these alternate universes are only mathematical possibilities and are not real. But the problem is that the theory lacks predictive power, since it cannot tell you which of these alternate universes is the real one.) This problem is actually not unique to string theory. For example, how many solutions are there to Newton’s or Maxwell’s equations? There are an infinite number, depending on what you are studying. If you start with a light bulb or a laser and you solve Maxwell’s equations, you find a unique solution for each instrument. So Maxwell’s or Newton’s theories also have an infinite number of solutions, depending on the initial conditions—that is, the situation you start with. This problem is likely to exist for any theory of everything. Any theory of everything will have an infinite number of solutions depending on the initial conditions. But how do you determine the initial conditions of the entire universe? This means you have to input the conditions of the Big Bang from the outside, by hand. To many physicists this seems like cheating. Ideally, you want the theory itself to tell you the conditions that gave rise to the Big Bang. You want the theory to tell you everything, including the temperature, density, and composition of the original Big Bang. A theory of everything should somehow contain its own initial conditions, all by itself. In other words, you want a unique prediction for the beginning of the universe. So string theory has an embarrassment of riches. Can it predict our universe? Yes. That is a sensational claim, the goal of physicists for almost a century. But can it predict just one universe? Probably not. This is called the landscape problem. There are several possible solutions to this problem, none of them widely accepted. The first is the anthropic principle, which says that our universe is special because we, as conscious beings, are here to discuss this question in the first place. In other words, there might be an infinite number of universes, but our universe is the one that has the conditions that make intelligent life possible. The initial conditions of the Big Bang are fixed at the beginning of time so that intelligent life can exist today. The other universes might have no conscious life in them.
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Michio Kaku (The God Equation: The Quest for a Theory of Everything)