Predictive Programing Quotes

I have a foreboding of an America in my children's or grandchildren's time -- when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what's true, we slide, almost without noticing, back into superstition and darkness... The dumbing down of American is most evident in the slow decay of substantive content in the enormously influential media, the 30 second sound bites (now down to 10 seconds or less), lowest common denominator programming, credulous presentations on pseudoscience and superstition, but especially a kind of celebration of ignorance

I predict we will abolish suffering throughout the living world. Our descendants will be animated by gradients of genetically pre-programmed well-being that are orders of magnitude richer than today's peak experiences.

In general, I try and distinguish between what one calls the Future and “l’avenir” [the ‘to come]. The future is that which – tomorrow, later, next century – will be. There is a future which is predictable, programmed, scheduled, foreseeable. But there is a future, l’avenir (to come) which refers to someone who comes whose arrival is totally unexpected. For me, that is the real future. That which is totally unpredictable. The Other who comes without my being able to anticipate their arrival. So if there is a real future, beyond the other known future, it is l’avenir in that it is the coming of the Other when I am completely unable to foresee their arrival.

When I applied to graduate school many years ago, I wrote an essay expressing my puzzlement at how a country that could put a man on the moon could still have people sleeping on the streets. Part of that problem is political will; we could take a lot of people off the streets tomorrow if we made it a national priority. But I have also come to realize that NASA had it easy. Rockets conform to the unchanging laws of physics. We know where the moon will be at a given time; we know precisely how fast a spacecraft will enter or exist the earth's orbit. If we get the equations right, the rocket will land where it is supposed to--always. Human beings are more complex than that. A recovering drug addict does not behave as predictably as a rocket in orbit. We don't have a formula for persuading a sixteen-year-old not to drop out of school. But we do have a powerful tool: We know that people seek to make themselves better off, however they may define that. Our best hope for improving the human condition is to understand why we act the way we do and then plan accordingly. Programs, organizations, and systems work better when they get the incentives right. It is like rowing downstream.

And from the time I was a kid, I've had this internal monologue roaring through my head, which doesn't stop - unless I'm asleep. I'm sure every person has this; it's just that my monologue is particularly loud. And particularly troublesome. I'm constantly asking myself questions. And the problem with that is that your brain is like a computer: If you ask a question, it's programmed to respond, whether there's an answer or not. I'm constantly weighing everything in my mind and trying to predict how my actions will influence events. Or maybe manipulate events are the more appropriate words. It's like playing a game of chess with your own life. And I hate fucking chess!

A few years ago, for instance, the AARP asked some lawyers if they would offer less expensive services to needy retirees, at something like $30 an hour. The lawyers said no. Then the program manager from AARP had a brilliant idea: he asked the lawyers if they would offer free services to needy retirees. Overwhelmingly, the lawyers said yes. What was going on here? How could zero dollars be more attractive than $30? When money was mentioned, the lawyers used market norms and found the offer lacking, relative to their market salary. When no money was mentioned they used social norms and were willing to volunteer their time. Why didn’t they just accept the $30, thinking of themselves as volunteers who received $30? Because once market norms enter our considerations, the social norms depart.

The secularizing 'values' and events that have been predicted would happen in the Muslim world have now begun to unfold with increasing momentum and persistence due still to the Muslims' lack of understanding of the true nature and implications of secularization as a philosophical program.

You're an abnormality. People get scared when they come across something that doesn't behave the way they expect it to. People like labels and categories and things that they can predict. When people can't explain something, they assume it's because there's something wrong with it. They try to fix it or change it. They mess with it until it's translatable and they bring it down to their level. Trying to change someone is easier than trying to accept them. It's how they were programmed

Prediction in a complex world is a chancy business. Every decision that a survival machine takes is a gamble, and it is the business of genes to program brains in advance so that on average they take decisions that pay off. The currency used in the casino of evolution is survival, strictly gene survival, but for many purposes individual survival is a reasonable approximation.

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.

Habits are undeniably useful tools, relieving us of the need to run a complex mental operation every time we’re confronted with a new task or situation. Yet they also relieve us of the need to stay awake to the world: to attend, feel, think, and then act in a deliberate manner. (That is, from freedom rather than compulsion.) If you need to be reminded how completely mental habit blinds us to experience, just take a trip to an unfamiliar country. Suddenly you wake up! And the algorithms of everyday life all but start over, as if from scratch. This is why the various travel metaphors for the psychedelic experience are so apt. The efficiencies of the adult mind, useful as they are, blind us to the present moment. We’re constantly jumping ahead to the next thing. We approach experience much as an artificial intelligence (AI) program does, with our brains continually translating the data of the present into the terms of the past, reaching back in time for the relevant experience, and then using that to make its best guess as to how to predict and navigate the future. One of the things that commends travel, art, nature, work, and certain drugs to us is the way these experiences, at their best, block every mental path forward and back, immersing us in the flow of a present that is literally wonderful—wonder being the by-product of precisely the kind of unencumbered first sight, or virginal noticing, to which the adult brain has closed itself. (It’s so inefficient!) Alas, most of the time I inhabit a near-future tense, my psychic thermostat set to a low simmer of anticipation and, too often, worry. The good thing is I’m seldom surprised. The bad thing is I’m seldom surprised.

The efficiencies of the adult mind, useful as they are, blind us to the present moment. We’re constantly jumping ahead to the next thing. We approach experience much as an artificial intelligence (AI) program does, with our brains continually translating the data of the present into the terms of the past, reaching back in time for the relevant experience, and then using that to make its best guess as to how to predict and navigate the future.

An evolutionary perspective predicts that most diets and fitness programs will fail, as they do, because we still don’t know how to counter once-adaptive primal instincts to eat donuts and take the elevator.

What you have with Sadie is nothing like what I have with Sadie, so it doesn't even matter. You can fuck anyone," he says. "You can't make games with anyone, though." "I make games with both of you," you point out. "I named Ichigo, for God's sake. I have been with both of you every step of the way. You can't say I haven't been here." "You've been here, sure. But you're fundamentally unimportant. If you weren't here, it would be someone else. You're a tamer of horses. You're an NPC, Marx." An NPC is a character that is not playable by a gamer. It is an AI extra that gives a programmed world verisimilitude. The NPC can be a best friend, a talking computer, a child, a parent, a lover, a robot, a gruff platoon leader, or the villain. Sam, however, means this as an insult---in addition to calling you unimportant, he's saying you're boring and predictable. But the fact is, there is no game without the NPCs. "There's no game without the NPCs," you tell him. "There's just some bullshit hero, wandering around with no one to talk to and nothing to do.

The library was still giving trouble: a few books in some of the more obscure corners of the stacks retained some autonomy, dating back to an infamous early experiment with flying books, and lately they'd begun to breed. Shocked undergraduates had stumbled on books in the very act. Which sounded interesting, but so far the resulting offspring had either been predictably derivative (in fiction) or stunningly boring (nonfiction); hybrid pairings between fiction and nonfiction were the most vital. The librarian thought the problem was just that the right books weren't breeding with each other and proposed a forced mating program. The library committee had an epic secret meeting about the ethics of literary eugenics which ended in a furious deadlock.

But even if such a prediction were true, our inability to distinguish between a virtual reality simulation and the real world will have less to do with the increasing fidelity of simulation than the decreasing perceptual abilities of us humans.

Gary Klein is a renowned and expert researcher on decision-making and cites the following aspects that experts have the ability to see which novices do not.196 1. Experts see patterns that novices do not detect. 2. Experts see anomalies—events that did not happen. 3. Experts see the big picture (situational awareness). 4. Experts create opportunities and improvisations. 5. Experts have the ability to predict future events using their previous experiences. 6. Experts see differences too small for novices to detect. 7. Experts know their own limitations. With an understanding of the differences between the experienced and the novice, we can begin to design a plan to overcome the shortfalls. Fortunately, understanding that it isn’t a “matter of intelligence, but a matter of experience” means that we can systematically set about gaining the experience necessary.

Even if we have a reliable criterion for detecting design, and even if that criterion tells us that biological systems are designed, it seems that determining a biological system to be designed is akin to shrugging our shoulders and saying God did it. The fear is that admitting design as an explanation will stifle scientific inquiry, that scientists will stop investigating difficult problems because they have a sufficient explanation already. But design is not a science stopper. Indeed, design can foster inquiry where traditional evolutionary approaches obstruct it. Consider the term "junk DNA." Implicit in this term is the view that because the genome of an organism has been cobbled together through a long, undirected evolutionary process, the genome is a patchwork of which only limited portions are essential to the organism. Thus on an evolutionary view we expect a lot of useless DNA. If, on the other hand, organisms are designed, we expect DNA, as much as possible, to exhibit function. And indeed, the most recent findings suggest that designating DNA as "junk" merely cloaks our current lack of knowledge about function. For instance, in a recent issue of the Journal of Theoretical Biology, John Bodnar describes how "non-coding DNA in eukaryotic genomes encodes a language which programs organismal growth and development." Design encourages scientists to look for function where evolution discourages it. Or consider vestigial organs that later are found to have a function after all. Evolutionary biology texts often cite the human coccyx as a "vestigial structure" that hearkens back to vertebrate ancestors with tails. Yet if one looks at a recent edition of Gray’s Anatomy, one finds that the coccyx is a crucial point of contact with muscles that attach to the pelvic floor. The phrase "vestigial structure" often merely cloaks our current lack of knowledge about function. The human appendix, formerly thought to be vestigial, is now known to be a functioning component of the immune system.

I can confidently predict that if the world is saved, it will not be because some old minds came up with some new programs. Programs never stop the things they're launched to stop. No program has ever stopped poverty, drug abuse, or crime, and no program ever will stop them. And no program will ever stop us from devastating the world.

If our style is masterful, if it is fluid and at the same time complete, then we can re-create ourselves, or rather, we can re-create the Infinite Goof within us. We can live on top of content, float above the predictable responses, social programming and hereditary circuitry, letting the bits of color and electricity and light filter up to us, where we may incorporate them at will into our actions. That's what the voices said. They said that content is what a man harbors but does not parade. And I love a parade.

The wolf reintroduction has gone so well that, somewhat ironically, the wolves are now threatened by their own success. Indeed, virtually all the conditions for strong public support that were evident in the early years of the program remain intact. The scientific and economic studies cited above support the original predictions of benefits, and agency officials remain committed to the policy. Yet some political actors remain hostile to the program. As NPS management assistant Sacklin said, "No amount of good science will stop a politician.

Modern society is large and complex, with institutions wielding great power over the lives of many. This is why Johnson and Fowler added a dire parting shot in their predictions. Since you are programmed to become increasingly overconfident the less you understand about any given scenario, you can expect to find the most destructive overconfidence in places that are exceedingly complicated and unpredictable.

Prediction in a complex world is a chancy business. Every decision that a survival machine takes is a gamble, and it is the business of genes to program brains in advance so that on average they take decisions that pay off.

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.

Political bodies endlessly debate the pros and cons of every action that will improve the lives of the weak and the oppressed. The resulting legislation is usually a watered down version of charitable actions directed at uplifting the poor. Any government invariably tailors its allocation of resources and alignment of power to protect the pocketbooks of the wealthy and powerful. Consequently, the true benefactors of any government’s socioeconomic programs are prominent people and rich corporations. Thomas Jefferson said, ‘I predict future happiness for Americans, if they can prevent the government from wasting the labors of the people under the pretense of taking care of them.

A very distinct pattern has emerged repeatedly when policies favored by the anointed turn out to fail. This pattern typically has four stages: STAGE 1. THE “CRISIS”: Some situation exists, whose negative aspects the anointed propose to eliminate. Such a situation is routinely characterized as a “crisis,” even though all human situations have negative aspects, and even though evidence is seldom asked or given to show how the situation at hand is either uniquely bad or threatening to get worse. Sometimes the situation described as a “crisis” has in fact already been getting better for years. STAGE 2. THE “SOLUTION”: Policies to end the “crisis” are advocated by the anointed, who say that these policies will lead to beneficial result A. Critics say that these policies will lead to detrimental result Z. The anointed dismiss these latter claims as absurd and “simplistic,” if not dishonest. STAGE 3. THE RESULTS: The policies are instituted and lead to detrimental result Z. STAGE 4. THE RESPONSE: Those who attribute detrimental result Z to the policies instituted are dismissed as “simplistic” for ignoring the “complexities” involved, as “many factors” went into determining the outcome. The burden of proof is put on the critics to demonstrate to a certainty that these policies alone were the only possible cause of the worsening that occurred. No burden of proof whatever is put on those who had so confidently predicted improvement. Indeed, it is often asserted that things would have been even worse, were it not for the wonderful programs that mitigated the inevitable damage from other factors. Examples of this pattern are all too abundant. Three will be considered here. The first and most general involves the set of social welfare policies called “the war on poverty” during the administration of President Lyndon B. Johnson, but continuing under other labels since then. Next is the policy of introducing “sex education” into the public schools, as a means of reducing teenage pregnancy and venereal diseases. The third example will be policies designed to reduce crime by adopting a less punitive approach, being more concerned with preventive social policies beforehand and rehabilitation afterwards, as well as showing more concern with the legal rights of defendants in criminal cases.

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.

We have seen segments of our Government, in their attitudes and action, adopt tactics unworthy of a democracy, and occasionally reminiscent of totalitarian regimes. We have seen a consistent pattern in which programs initiated with limited goals, such as preventing criminal violence or identifying foreign spies, were expanded to what witnesses characterized as "vacuum cleaners", sweeping in information about lawful activities of American citizens. The tendency of intelligence activities to expand beyond their initial scope is a theme which runs through every aspect of our investigative findings. Intelligence collection programs naturally generate ever-increasing demands for new data. And once intelligence has been collected, there are strong pressures to use it against the target.

We needed a man to repair the machines, to keep them going and everything. And the army was always going to send this fellow they had, but he was always delayed. Now, we always were in a hurry. Everything we did, we tried to do as quickly as possible. In this particular case, we worked out all the numerical steps that the machines were supposed to do—multiply this, and then do this, and subtract that. Then we worked out the program, but we didn’t have any machine to test it on. So we set up this room with girls in it. Each one had a Marchant: one was the multiplier, another was the adder. This one cubed—all she did was cube a number on an index card and send it to the next girl. We went through our cycle this way until we got all the bugs out. It turned out that the speed at which we were able to do it was a hell of a lot faster than the other way, where every single person did all the steps. We got speed with this system that was the predicted speed for the IBM machine. The only difference is that the IBM machines didn’t get tired and could work three shifts. But the girls got tired after a while.

It was not easy to go from being one of the seven righteous pillars holding up the whole planet and human race to being just another mental patient. I remember talking to a woman who was ending racism and asking her if it was part of a bigger program or if racism was the whole deal. As someone who had gone back to the beginning of time and dealt with issues of whether or not life itself was a good idea, I wasn’t sure that just getting rid of racism was a big enough prize. ....In the eighties when I was called out of retirement to defeat communism, it was over my strenuous objections. “I don’t even dislike communism all that much,” I objected. “It seems so beside the point.” “The Republicans are going to take credit for this and ride it into the ground,” I correctly predicted. After winning many many preliminary rounds which I honestly hoped I’d lose, I was smuggled into what was thought to be just another psychiatric hospital where the Russian bear took one look at me, declined to dance, and the rest is history. My delusional world always felt kind of tinny and hollow, but that never helped me get out of it.

The assistant director of the Office of Economic Opportunity, Hyman Bookbinder, in a frank statement on December 29, 1966, declared that the long-range costs of adequately implementing programs to fight poverty, ignorance and slums will reach one trillion dollars. He was not awed or dismayed by this prospect but instead pointed out that the growth of the gross national product during the same period makes this expenditure comfortably possible. It is, he said, as simple as this: “The poor can stop being poor if the rich are willing to become even richer at a slower rate.” Furthermore, he predicted that unless a “substantial sacrifice is made by the American people,” the nation can expect further deterioration of the cities, increased antagonisms between races and continued disorders in the streets. He asserted that people are not informed enough to give adequate support to antipoverty programs, and he leveled a share of the blame at the government because it “must do more to get people to understand the size of the problem.

Living in survival entails living in stress and functioning as a materialist, believing that the outer world is more real than the inner world. When you are under the gun of the fight-or-flight nervous system, being run by its cocktail of intoxicating chemicals, you are programmed to be concerned only about your body, the things or people in your environment, and your obsession with time. Your brain and body are out of balance. You are living a predictable life. However, when you are truly in the elegant state of creation, you are no body, no thing, no time—you forget about yourself. You become pure consciousness, free from the chains of the identity that needs the outer reality to remember who it thinks it is.

As a thought experiment, von Neumann's analysis was simplicity itself. He was saying that the genetic material of any self-reproducing system, whether natural or artificial, must function very much like a stored program in a computer: on the one hand, it had to serve as live, executable machine code, a kind of algorithm that could be carried out to guide the construction of the system's offspring; on the other hand, it had to serve as passive data, a description that could be duplicated and passed along to the offspring. As a scientific prediction, that same analysis was breathtaking: in 1953, when James Watson and Francis Crick finally determined the molecular structure of DNA, it would fulfill von Neumann's two requirements exactly. As a genetic program, DNA encodes the instructions for making all the enzymes and structural proteins that the cell needs in order to function. And as a repository of genetic data, the DNA double helix unwinds and makes a copy of itself every time the cell divides in two. Nature thus built the dual role of the genetic material into the structure of the DNA molecule itself.

It might be possible to code technology to predict human speech patterns or program artificial intelligence to respond back to our questions. We might suffer a migraine when we’re stressed—a dagger at our temple—but when our souls are irreparably damaged, it’s not our minds that hurt. It’s right there in the violent wanting of our chests. You know this because yours has just broken.

Steven Alm, a judge who devised a “probation with enforcement” program, summed up the reason for the program’s success: “When the system isn’t consistent and predictable, when people are punished randomly, they think, My probation officer doesn’t like me, or, Someone’s prejudiced against me, rather than seeing that everyone who breaks a rule is treated equally, in precisely the same way.

Bitcoin can be best understood as distributed software that allows for transfer of value using a currency protected from unexpected inflation without relying on trusted third parties. In other words, Bitcoin automates the functions of a modern central bank and makes them predictable and virtually immutable by programming them into code decentralized among thousands of network members, none of whom can alter the code without the consent of the rest.

Like every other area of life, we have come to believe that growth in Christ — as individuals or as churches — can and should be programmed to generate predictable outcomes that are unrealistic and are not even justified biblically. We want big results — sooner rather than later. And we’ve forgotten that God showers his extraordinary gifts through ordinary means of grace, loves us through ordinary fellow image bearers, and sends us out into the world to love and serve others in ordinary callings.

Who can tell us—poems, do they only predict or do they, God help us, construct our future for us—summoning from the teeming multitude of possibilities within it that one, which they name? And if this is really so—if we, blind maniacs, program our own lives in advance, pleased as punch at how cleverly we’ve written it all down!—and thus make our lives what they are, then this is a truly frightening gift, Lord, like a bomb in the hands of a five-year-old—and how does one pray to be released? Who (what) writes through us?

One result of the federal government’s student financial aid programs is higher tuition costs at our nation’s colleges and universities.” Although paradoxical, this result could have been predicted from basic economic theory: when students can come up with more money for college, thanks to the government’s efforts, colleges can afford to increase their tuition. “The empirical evidence is consistent with that—federal loans, Pell grants, and other assistance programs result in higher tuition for students at our nation’s colleges and universities.

Bitcoin can be best understood as distributed software that allows for transfer of value using a currency protected from unexpected inflation without relying on trusted third parties. In other words, Bitcoin automates the functions of a modern central bank and makes them predictable and virtually immutable by programming them into code decentralized among thousands of network members, none of whom can alter the code without the consent of the rest. This makes Bitcoin the first demonstrably reliable operational example of digital cash and digital hard money.

When you are under the gun of the fight-or-flight nervous system, being run by its cocktail of intoxicating chemicals, you are programmed to be concerned only about your body, the things or people in your environment, and your obsession with time. Your brain and body are out of balance. You are living a predictable life. However, when you are truly in the elegant state of creation, you are no body, no thing, no time—you forget about yourself. You become pure consciousness, free from the chains of the identity that needs the outer reality to remember who it thinks it is.

The factory has programmed that adventurous impulse out of us. The economic imperative of the last century has been to avoid risk, avoid change, and most of all, avoid exploration and the new. An efficient factory fears change because change means retooling and risk and a blip in productivity. Sure, we’ll put up with change if we have to, and welcome the predictable incremental change of productivity improvement, but please leave us alone when it comes to the word “bold.” Avoiding risk worked then but doesn’t work now. Now “what’s next?” is in fact the driving force for individuals and for organizations. Ever onward, ever faster.

Here’s a simple definition of ideology: “A set of beliefs about the proper order of society and how it can be achieved.”8 And here’s the most basic of all ideological questions: Preserve the present order, or change it? At the French Assembly of 1789, the delegates who favored preservation sat on the right side of the chamber, while those who favored change sat on the left. The terms right and left have stood for conservatism and liberalism ever since. Political theorists since Marx had long assumed that people chose ideologies to further their self-interest. The rich and powerful want to preserve and conserve; the peasants and workers want to change things (or at least they would if their consciousness could be raised and they could see their self-interest properly, said the Marxists). But even though social class may once have been a good predictor of ideology, that link has been largely broken in modern times, when the rich go both ways (industrialists mostly right, tech billionaires mostly left) and so do the poor (rural poor mostly right, urban poor mostly left). And when political scientists looked into it, they found that self-interest does a remarkably poor job of predicting political attitudes.9 So for most of the late twentieth century, political scientists embraced blank-slate theories in which people soaked up the ideology of their parents or the TV programs they watched.10 Some political scientists even said that most people were so confused about political issues that they had no real ideology at all.11 But then came the studies of twins. In the 1980s, when scientists began analyzing large databases that allowed them to compare identical twins (who share all of their genes, plus, usually, their prenatal and childhood environments) to same-sex fraternal twins (who share half of their genes, plus their prenatal and childhood environments), they found that the identical twins were more similar on just about everything.12 And what’s more, identical twins reared in separate households (because of adoption) usually turn out to be very similar, whereas unrelated children reared together (because of adoption) rarely turn out similar to each other, or to their adoptive parents; they tend to be more similar to their genetic parents. Genes contribute, somehow, to just about every aspect of our personalities.13 We’re not just talking about IQ, mental illness, and basic personality traits such as shyness. We’re talking about the degree to which you like jazz, spicy foods, and abstract art; your likelihood of getting a divorce or dying in a car crash; your degree of religiosity, and your political orientation as an adult. Whether you end up on the right or the left of the political spectrum turns out to be just as heritable as most other traits: genetics explains between a third and a half of the variability among people on their political attitudes.14 Being raised in a liberal or conservative household accounts for much less. How can that be? How can there be a genetic basis for attitudes about nuclear power, progressive taxation, and foreign aid when these issues only emerged in the last century or two? And how can there be a genetic basis for ideology when people sometimes change their political parties as adults? To answer these questions it helps to return to the definition of innate that I gave in chapter 7. Innate does not mean unmalleable; it means organized in advance of experience. The genes guide the construction of the brain in the uterus, but that’s only the first draft, so to speak. The draft gets revised by childhood experiences. To understand the origins of ideology you have to take a developmental perspective, starting with the genes and ending with an adult voting for a particular candidate or joining a political protest. There are three major steps in the process. Step

The Brits call this sort of thing Functional Neurological Symptoms, or FNS, the psychiatrists call it conversion disorder, and almost everyone else just calls it hysteria. There are three generally acknowledged, albeit uncodified, strategies for dealing with it. The Irish strategy is the most emphatic, and is epitomized by Matt O’Keefe, with whom I rounded a few years back on a stint in Ireland. “What are you going to do?” I asked him about a young woman with pseudoseizures. “What am I going to do?” he said. “I’ll tell you what I’m goin’ to do. I’m going to get her, and her family, and her husband, and the children, and even the feckin’ dog in a room, and tell ’em that they’re wasting my feckin’ time. I want ’em all to hear it so that there is enough feckin’ shame and guilt there that it’ll keep her the feck away from me. It might not cure her, but so what? As long as I get rid of them.” This approach has its adherents even on these shores. It is an approach that Elliott aspires to, as he often tells me, but can never quite marshal the umbrage, the nerve, or a sufficiently convincing accent, to pull off. The English strategy is less caustic, and can best be summarized by a popular slogan of World War II vintage currently enjoying a revival: “Keep Calm and Carry On.” It is dry, not overly explanatory, not psychological, and does not blame the patient: “Yes, you have something,” it says. “This is what it is [insert technical term here], but we will not be expending our time or a psychiatrist’s time on it. You will have to deal with it.” Predictably, the American strategy holds no one accountable, involves a brain-centered euphemistic explanation coupled with some touchy-feely stuff, and ends with a recommendation for a therapeutic program that, very often, the patient will ignore. In its abdication of responsibility, motivated by the fear of a lawsuit, it closely mirrors the beginning of the end of a doomed relationship: “It’s not you, it’s … no wait, it’s not me, either. It just is what it is.” Not surprisingly, estimates of recurrence of symptoms range from a half to two-thirds of all cases, making this one of the most common conditions that a neurologist will face, again and again.

It’s time to recognize that a broad, multidisciplinary, multi-institutional, multinational initiative, guided by a broader, more integrated and unified perspective, should be playing a central role in guiding our scientific agenda in addressing this issue and informing policy. We need a broad and more integrated scientific framework that encompasses a quantitative, predictive, mechanistic theory for understanding the relationship between human-engineered systems, both social and physical, and the “natural” environment—a framework I call a grand unified theory of sustainability. It’s time to initiate a massive international Manhattan-style project or Apollo-style program dedicated to addressing global sustainability in an integrated, systemic sense.1

Some researchers, such as psychologist Jean Twenge, say this new world where compliments are better than sex and pizza, in which the self-enhancing bias has been unchained and allowed to gorge unfettered, has led to a new normal in which the positive illusions of several generations have now mutated into full-blown narcissism. In her book The Narcissism Epidemic, Twenge says her research shows that since the mid-1980s, clinically defined narcissism rates in the United States have increased in the population at the same rate as obesity. She used the same test used by psychiatrists to test for narcissism in patients and found that, in 2006, one in four U.S. college students tested positive. That’s real narcissism, the kind that leads to diagnoses of personality disorders. In her estimation, this is a dangerous trend, and it shows signs of acceleration. Narcissistic overconfidence crosses a line, says Twenge, and taints those things improved by a skosh of confidence. Over that line, you become less concerned with the well-being of others, more materialistic, and obsessed with status in addition to losing all the restraint normally preventing you from tragically overestimating your ability to manage or even survive risky situations. In her book, Twenge connects this trend to the housing market crash of the mid-2000s and the stark increase in reality programming during that same decade. According to Twenge, the drive to be famous for nothing went from being strange to predictable thanks to a generation or two of people raised by parents who artificially boosted self-esteem to ’roidtastic levels and then released them into a culture filled with new technologies that emerged right when those people needed them most to prop up their self-enhancement biases. By the time Twenge’s research was published, reality programming had spent twenty years perfecting itself, and the modern stars of those shows represent a tiny portion of the population who not only want to be on those shows, but who also know what they are getting into and still want to participate. Producers with the experience to know who will provide the best television entertainment to millions then cull that small group. The result is a new generation of celebrities with positive illusions so robust and potent that the narcissistic overconfidence of the modern American teenager by comparison is now much easier to see as normal.

A moth is such a simple machine in the animal world - the go-kart to the modern car - and it takes a lot of glitches to prevent it going. It's this intriguing simplicity, the idea that you could pull it into its constituent parts and put it back together in the same rainy day, that if you pulled back the skin, you could watch the inner workings, that makes a moth such an absorbing creature to study. Moths have a universal character: there are no individuals. Each reacts to a precise condition or stimulus in a predictable and replicable way. They are pre-programmed robots, unable to learn from experience. For instance, we know they will allways react to a smell, a pheromone or a particular spectrum of light in the same way. I can mimic the scent of a flower so that a moth will direct itself towards that scent ...

Imagine a life without uncertainty. Hope, according to Aeschylus, comes from the lack of certainty of fate; perhaps hope is inherently blind. Imagine how dull life would be if variables assessed for admission to a professional school, graduate program, or executive training program really did predict with great accuracy who would succeed and who would fail. Life would be intolerable—no hope, no challenge. Thus, we have a paradox. While we all strive to reduce the uncertainties of our existence and of the environment, ultimate success—that is, a total elimination of uncertainty—would be horrific. Knowing pleasant outcomes with certainty would also detract from life’s joy. An essential part of knowledge is to shrink the domain of the unpredictable. But while we pursue this goal, its ultimate attainment would not be at all desirable.

This approach is flawed on multiple levels. First, when institutions conflate racial and gender diversity metrics with diversity of thought in their organizations, they implicitly reinforce the incorrect assumption that genetic characteristics predict something important about the way that a person thinks—the most fundamental assumption underlying racism itself. Second, this approach empowers entrenched managers to create the visible appearance of diversity in their organizations while avoiding the need to engage with true diversity of thought, including challenges to their incumbency. Third, when a narrow conception of diversity is implemented through affirmative action or other quota-based systems, that fuels racism and sexism by fostering tokenism in the workplace and animus among communities that fail to benefit from these programs.

Instead of relying on the Newtonian metaphor of clockwork predictability, complexity seems to be based on metaphors more closely akin to the growth of a plant from a tiny seed, or the unfolding of a computer program from a few lines of code, or perhaps even the organic, self-organized flocking of simpleminded birds. That's certainly the kind of metaphor that Chris Langton has in mind with artificial life: his whole point is that complex, lifelike behavior is the result of simple rules unfolding from the bottom up. And it's likewise the kind of metaphor that influenced Arthur in the Santa Fe economics program: "If I had a purpose, or a vision, it was to show that the messiness and the liveliness in the economy can grow out of an incredibly simple, even elegant theory. That's why we created these simple models of the stock market where the market appears moody, shows crashes, takes off in unexpected directions, and acquires something that you could describe as a personality.

Search engine query data is not the product of a designed statistical experiment and finding a way to meaningfully analyse such data and extract useful knowledge is a new and challenging field that would benefit from collaboration. For the 2012–13 flu season, Google made significant changes to its algorithms and started to use a relatively new mathematical technique called Elasticnet, which provides a rigorous means of selecting and reducing the number of predictors required. In 2011, Google launched a similar program for tracking Dengue fever, but they are no longer publishing predictions and, in 2015, Google Flu Trends was withdrawn. They are, however, now sharing their data with academic researchers... Google Flu Trends, one of the earlier attempts at using big data for epidemic prediction, provided useful insights to researchers who came after them... The Delphi Research Group at Carnegie Mellon University won the CDC’s challenge to ‘Predict the Flu’ in both 2014–15 and 2015–16 for the most accurate forecasters. The group successfully used data from Google, Twitter, and Wikipedia for monitoring flu outbreaks.

Corvallis sometimes thought back on the day, three decades ago, when Richard Forthrast had reached down and plucked him out of his programming job at Corporation 9592 and given him a new position, reporting directly to Richard. Corvallis had asked the usual questions about job title and job description. Richard had answered, simply, “Weird stuff.” When this proved unsatisfactory to the company’s ISO-compliant HR department, Richard had been forced to go downstairs and expand upon it. In a memorable, extemporaneous work of performance art in the middle of the HR department’s open-plan workspace, he had explained that work of a routine, predictable nature could and should be embodied in computer programs. If that proved too difficult, it should be outsourced to humans far away. If it was somehow too sensitive or complicated for outsourcing, then “you people” (meaning the employees of the HR department) needed to slice it and dice it into tasks that could be summed up in job descriptions and advertised on the open employment market. Floating above all of that, however, in a realm that was out of the scope of “you people,” was “weird stuff.” It was important that the company have people to work on “weird stuff.” As a matter of fact it was more important than anything else. But trying to explain “weird stuff” to “you people” was like explaining blue to someone who had been blind since birth, and so there was no point in even trying. About then, he’d been interrupted by a spate of urgent text messages from one of the company’s novelists, who had run aground on some desolate narrative shore and needed moral support, and so the discussion had gone no further. Someone had intervened and written a sufficiently vague job description for Corvallis and made up a job title that would make it possible for him to get the level of compensation he was expecting. So it had all worked out fine. And it made for a fun story to tell on the increasingly rare occasions when people were reminiscing about Dodge back in the old days. But the story was inconclusive in the sense that Dodge had been interrupted before he could really get to the essence of what “weird stuff” actually was and why it was so important. As time went on, however, Corvallis understood that this very inconclusiveness was really a fitting and proper part of the story.

In an effort to control their populations, both China and India adopted family planning programs in the 1970s. China created a one-child policy, and India turned to policies that included sterilization. In the 1960s and ’70s, population control was embraced in US foreign policy based on predictions that overpopulation would lead to mass famine and starvation and possibly to large-scale migration because of a lack of food. Earlier in the twentieth century, birth control advocates in the United States had also pressed their case, many of them hoping to help the poor avoid having unwanted children. Some of these advocates were eugenicists who wanted to eliminate “the unfit” and urged certain groups to have fewer children, or none at all. Sanger herself supported some eugenicist positions. Eugenics is morally nauseating, as well as discredited by science. Yet this history is being used to confuse the conversation on contraceptives today. Opponents of contraception try to discredit modern contraceptives by bringing up the history of eugenics, arguing that because contraceptives have been used for certain immoral purposes, they should not be used for any purpose, even allowing a mother to wait before having another child.

It is very impressive, to notice that whatsoever you make a person believe about you, that person will rush to represent within his role, as if he or she was mentally programmed to play the drama being offered. People are so trapped within their mind, that they end up always acting inside a theatre, in which their part has been foreseen long before they entered the roles they represent. Likewise, they become easily predictable, programmable, influenceable, manipulated, played like a string puppet. And these puppets become funnier, when mentioning mental programming, fearing mental programing and attacking mental programming, while not realizing that they are doing it, using the words, and gestures, and even phrases, that they were programmed to do, by those who program them. The one with a poor conscience is always a poor actor within his own life. He perfectly represents it, without any awareness. If he had any, he would probably not do it. But what else could he do? As prisoners in a cell with an open door, they ask when presented with freedom: “What shall I do if all I know is this?” And so, they remain inside of it, waiting for someone to tell them an answer they cannot ever understand before they see it for themselves.

Not long ago, Malthusian thinking was revived with a vengeance. In 1967 William and Paul Paddock wrote Famine 1975!, and in 1968 the biologist Paul R. Ehrlich wrote The Population Bomb, in which he proclaimed that “the battle to feed all of humanity is over” and predicted that by the 1980s sixty-five million Americans and four billion other people would starve to death. New York Times Magazine readers were introduced to the battlefield term triage (the emergency practice of separating wounded soldiers into the savable and the doomed) and to philosophy-seminar arguments about whether it is morally permissible to throw someone overboard from a crowded lifeboat to prevent it from capsizing and drowning everyone.10 Ehrlich and other environmentalists argued for cutting off food aid to countries they deemed basket cases.11 Robert McNamara, president of the World Bank from 1968 to 1981, discouraged financing of health care “unless it was very strictly related to population control, because usually health facilities contributed to the decline of the death rate, and thereby to the population explosion.” Population-control programs in India and China (especially under China’s one-child policy) coerced women into sterilizations, abortions, and being implanted with painful and septic IUDs.12

Bergson felt the event of the First World War this way. Before it broke out, it appeared both possible and impossible (the similarity with the suspense surrounding the Iraq war is total), and at the same time he experienced a sense of stupefaction at the ease with which such a fearful eventuality could pass from the abstract to the concrete, from the virtual to the real. We see the same paradox again in the mix of jubilation and terror that characterized, in a more or less unspoken way, the event of 11 September. It is the feeling that seizes us when faced with the occurrence of something that happens without having been possible. In the normal course of events, things first have to be possible and can only actualize themselves afterwards. This is the logical, chronological order. But they are not, in that case, events in the strong sense. This is the case with the Iraq war, which has been so predicted, programmed, anticipated, prescribed and modelled that it has exhausted all its possibilities before even taking place. There is no longer anything of the event in it. There is no longer anything in it of that sense of exaltation and horror felt in the radical event of 11 September, which resembles the sense of the sublime spoken of by Kant. The non-event of the war leaves merely a sense of mystification and nausea.

The main ones are the symbolists, connectionists, evolutionaries, Bayesians, and analogizers. Each tribe has a set of core beliefs, and a particular problem that it cares most about. It has found a solution to that problem, based on ideas from its allied fields of science, and it has a master algorithm that embodies it. For symbolists, all intelligence can be reduced to manipulating symbols, in the same way that a mathematician solves equations by replacing expressions by other expressions. Symbolists understand that you can’t learn from scratch: you need some initial knowledge to go with the data. They’ve figured out how to incorporate preexisting knowledge into learning, and how to combine different pieces of knowledge on the fly in order to solve new problems. Their master algorithm is inverse deduction, which figures out what knowledge is missing in order to make a deduction go through, and then makes it as general as possible. For connectionists, learning is what the brain does, and so what we need to do is reverse engineer it. The brain learns by adjusting the strengths of connections between neurons, and the crucial problem is figuring out which connections are to blame for which errors and changing them accordingly. The connectionists’ master algorithm is backpropagation, which compares a system’s output with the desired one and then successively changes the connections in layer after layer of neurons so as to bring the output closer to what it should be. Evolutionaries believe that the mother of all learning is natural selection. If it made us, it can make anything, and all we need to do is simulate it on the computer. The key problem that evolutionaries solve is learning structure: not just adjusting parameters, like backpropagation does, but creating the brain that those adjustments can then fine-tune. The evolutionaries’ master algorithm is genetic programming, which mates and evolves computer programs in the same way that nature mates and evolves organisms. Bayesians are concerned above all with uncertainty. All learned knowledge is uncertain, and learning itself is a form of uncertain inference. The problem then becomes how to deal with noisy, incomplete, and even contradictory information without falling apart. The solution is probabilistic inference, and the master algorithm is Bayes’ theorem and its derivates. Bayes’ theorem tells us how to incorporate new evidence into our beliefs, and probabilistic inference algorithms do that as efficiently as possible. For analogizers, the key to learning is recognizing similarities between situations and thereby inferring other similarities. If two patients have similar symptoms, perhaps they have the same disease. The key problem is judging how similar two things are. The analogizers’ master algorithm is the support vector machine, which figures out which experiences to remember and how to combine them to make new predictions.

You know the logics setup. You got a logic in your house. It looks like a vision receiver used to, only it's got keys instead of dials and you punch the keys for what you wanna get. It's hooked in to the tank, which has the Carson Circuit all fixed up with relays. Say you punch "Station SNAFU" on your logic. Relays in the tank take over an' whatever vision-program SNAFU is telecastin' comes on your logic's screen. Or you punch "Sally Hancock's Phone" an' the screen blinks an' sputters an' you're hooked up with the logic in her house an' if somebody answers you got a vision-phone connection. But besides that, if you punch for the weather forecast or who won today's race at Hialeah or who was mistress of the White House durin' Garfield's administration or what is PDQ and R sellin' for today, that comes on the screen too. The relays in the tank do it. The tank is a big buildin' full of all the facts in creation an' all the recorded telecasts that ever was made—an' it's hooked in with all the other tanks all over the country—an' everything you wanna know or see or hear, you punch for it an' you get it. Very convenient. Also it does math for you, an' keeps books, an' acts as consultin' chemist, physicist, astronomer, an' tea-leaf reader, with a "Advice to the Lovelorn" thrown in. The only thing it won't do is tell you exactly what your wife meant when she said, "Oh, you think so, do you?" in that peculiar kinda voice. Logics don't work good on women. Only on things that make sense. (1949)

You were taught that even when the charism of celibacy and chastity is present and embraced, the attractions, the impulses, the desires will still be present. So the first thing you need to do is be aware that you are a human being, and no matter how saintly or holy you are, you will never remove yourself from those passions. But the idea was making prudent choices. You just walk away. Celibacy is a radical call, and you’ve made a decision not to act on your desire.” Today, seminaries say they screen applicants rigorously. In Boston, for example, a young man must begin conversations with the vocations director a year before applying for admissions, and then the application process takes at least four months. Most seminaries require that applicants be celibate for as long as five years before starting the program, just to test out the practice, and students are expected to remain celibate throughout seminary as they continue to discern whether they are cut out to lead the sexless life of an ordained priest. Some seminaries screen out applicants who say they are sexually attracted to other men, but most do not, arguing that there is no evidence linking sexual orientation to one’s ability to lead a celibate life. The seminaries attempt to weed out potential child abusers, running federal and local criminal background checks, but there is currently no psychological test that can accurately predict whether a man who has never sexually abused a child is likely to do so in the future. So seminary officials say that in the screening process, and throughout seminary training, they are alert to any sign that a man is not forming normal relationships with adults, or seems abnormally interested in children. Many potential applicants are turned away from seminaries, and every year some students are forced out. “Just because there’s a shortage doesn’t mean we should lessen our standards,” said Rev. Edward J. Burns,

The fascination with automation in part reflected the country’s mood in the immediate postwar period, including a solid ideological commitment to technological progress. Representatives of industry (along with their counterparts in science and engineering) captured this mood by championing automation as the next step in the development of new production machinery and American industrial prowess. These boosters quickly built up automation into “a new gospel of postwar economics,” lauding it as “a universal ideal” that would “revolutionize every area of industry.” 98 For example, the November 1946 issue of Fortune magazine focused on the prospects for “The Automatic Factory.” The issue included an article titled “Machines without Men” that envisioned a completely automated factory where virtually no human labor would be needed. 99 With visions of “transforming the entire manufacturing sector into a virtually labor-free enterprise,” factory owners in a range of industries began to introduce automation in the postwar period. 100 The auto industry moved with particular haste. After the massive wave of strikes in 1945–46, automakers seized on automation as a way to replace workers with machines. 101 As they converted back to civilian auto production after World War II, they took the opportunity to install new labor-saving automatic production equipment. The two largest automakers, Ford and General Motors, set the pace. General Motors introduced the first successful automated transfer line at its Buick engine plant in Flint in 1946 (shortly after a 113-day strike, the longest in the industry’s history). The next year Ford established an automation department (a Ford executive, Del S. Harder, is credited with coining the word “automation”). By October 1948 the department had approved $ 3 million in spending on 500 automated devices, with early company estimates predicting that these devices would result in a 20 percent productivity increase and the elimination of 1,000 jobs. Through the late 1940s and 1950s Ford led the way in what became known as “Detroit automation,” undertaking an expensive automation program, which it carried out in concert with the company’s plans to decentralize operations away from the city. A major component of this effort was the Ford plant in the Cleveland suburb of Brook Park, a $ 2 billion engine-making complex that attracted visitors from government, industry, and labor and became a national symbol of automation in the 1950s. 102

While the research and applications are in its early days, many experts see probabilistic programming as an alternative approach in areas where deep learning performs poorly, such as concept formulation using sparse or medium-sized data. Probabilistic programs have been used successfully in applications such as medical imaging, machine perception, financial predictions, and econometric and atmospheric forecasting.

We stand too close to the most recent generation of school reform to know where the future lies. There was nothing inevitable about the creation of the public school systems in the nineteenth century, and there is nothing inevitable about their survival or transformation in the coming decades. No one could have guessed in the early twentieth century that urban schools, widely regarded by professional educators as the model for schools everywhere, would soon fall from grace. No one could have predicted that the civil rights movement and rights revolution would bring poor and disadvantaged youngsters into systems that once excluded or mistreated them. No one could have known that the old idea of the school as a melting pot would be discredited, especially in professional training programs. History can offer perspective but not identify the pathways to the future. Like the past, the future will be full of surprises.

Meanwhile in Iran and Israel the violence is an open wound on TV, so predictable and it’s bloodiness of the mutilated children and howling women become a spectacle you shatter it briefly before zapping over to some Japanese game show. The well-meaning optimism of those Entertainement programs, with their perky nerdiness and banana-skin tomfoolery, provides a counterpoint to the real world grief. Their crude hilarities flit through my head while I swim my laps, like my Spanish Kahlo mantra or fragments of some absurd erotic fantasy, poignantly irrelevant.

And in the late summer of 1998, the bond-trading crowd was extremely fearful, especially of risky credits. The professors hadn't modeled this. They had programmed the market for a cold predictability that it had never had; they had forgotten the predatory, acquisitive, and overwhelming protective instincts that govern real-life traders. They had forgotten the human factor.

strife. Family conflict at ages 7–15 years predicts insomnia at age 18, and marital strife at age 9 months predicts a child’s sleep problems at 4½ years.

Sleep problems at age 8 years predict depressive symptoms at age 10 years.

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. Politics, too, is a second-order chaotic system. Many people criticise Sovietologists for failing to predict the 1989 revolutions and castigate Middle East experts for not anticipating the Arab Spring revolutions of 2011. This is unfair. Revolutions are, by definition, unpredictable. A predictable revolution never erupts.

As the years have gone by Lake Powell has continued to silt up, losing more than 100,000 acre-feet per year at last count, and hydrologists believe—as Abbey did—that silting will eventually lead to a pool of mud, not water. Michael Kellett is the program director of the Glen Canyon Institute, which was founded in 1996 with the help of David Brower with the goal of one day witnessing the Colorado flowing freely through the old Glen Canyon. At a time when western dams are actually being decommissioned so that rivers can flow, experts are wondering whether it is really viable to have two enormous evaporative and silting reservoirs, Powell and Mead. Kellett wrote in the summer of 2012: The trends of the last decade have dramatically changed the situation. Rising public water demand, relentless drought, and climate change have significantly reduced the flow of the Colorado River from that of the past century. Scientific studies have predicted that this situation will continue. Lake Powell reservoir, and Lake Mead reservoir downstream, are half empty. Most scientists believe that there will never again be enough water to fill both reservoirs. Which had led to proposals like the Fill Lake Mead First project, the idea being to keep the downstream reservoir, Mead, full while releasing the upstream Glen Canyon. In other words, for the first time Abbey’s wild fantasies are being considered as serious policy.

Much science in many disciplines consists of a toolkit of very simple mathematical models. To many not familiar with the subtle art of the simple model, such formal exercises have two seemingly deadly flaws. First, they are not easy to follow. […] Second, motivation to follow the math is often wanting because the model is so cartoonishly simple relative to the real world being analyzed. Critics often level the charge ‘‘reductionism’’ with what they take to be devastating effect. The modeler’s reply is that these two criticisms actually point in opposite directions and sum to nothing. True, the model is quite simple relative to reality, but even so, the analysis is difficult. The real lesson is that complex phenomena like culture require a humble approach. We have to bite off tiny bits of reality to analyze and build up a more global knowledge step by patient step. […] Simple models, simple experiments, and simple observational programs are the best the human mind can do in the face of the awesome complexity of nature. The alternatives to simple models are either complex models or verbal descriptions and analysis. Complex models are sometimes useful for their predictive power, but they have the vice of being difficult or impossible to understand. The heuristic value of simple models in schooling our intuition about natural processes is exceedingly important, even when their predictive power is limited. […] Unaided verbal reasoning can be unreliable […] The lesson, we think, is that all serious students of human behavior need to know enough math to at least appreciate the contributions simple mathematical models make to the understanding of complex phenomena. The idea that social scientists need less math than biologists or other natural scientists is completely mistaken.

These days, there are many different ways to enjoy yourself, and the interactive requirements vary considerably, so it wouldn’t be too hard to find a group or event that allows you to function at your own sociability level. As you move forward through this self-help program, remind yourself that interactive health contributes to your overall health and longevity. Talking with others—sharing yourself and your experiences—not only makes you more productive at work and fulfilled in your personal life, it actually lowers your risk of disease. So stay committed to this program, and start to envision yourself as part of an interactive network. And keep in mind that having fun—alone or with other people—is one of your goals. The bottom line with stress management is that all you can control is yourself. You cannot control others around you, which is especially important to understand. People do not always behave predictably or follow the course you would like them to. Situations are not always fair. But used appropriately, stress management can help you to control your reaction to these situations. Once you incorporate stress management into your life, you will find that it not only has the potential to improve the quality of your social interaction but it is also very much related to your overall health, feelings of well-being, and longevity.

The development of specific mechanisms of social controls also becomes necessary with the historicization and objectivation of institutions. Deviance from the institutionally “programmed” courses of action becomes likely once the institutions have become realities divorced from their original relevance in the concrete social processes from which they arose. To put this more simply, it is more likely that one will deviate from programs set up for one by others than from programs that one has helped establish oneself. The new generation posits a problem of compliance, and its socialization into the institutional order requires the establishment of sanctions. The institutions must and do claim authority over the individual, independently of the subjective meanings he may attach to any particular situation. The priority of the institutional definitions of situations must be consistently maintained over individual temptations at redefinition. The children must be “taught to behave” and, once taught, must be “kept in line.” So, of course, must the adults. The more conduct is institutionalized, the more predictable and thus the more controlled it becomes. If socialization into the institutions has been effective, outright coercive measures can be applied economically and selectively. Most of the time, conduct will occur “spontaneously” within the institutionally set channels. The more, on the level of meaning, conduct is taken for granted, the more possible alternatives to the institutional “programs” will recede, and the more predictable and controlled conduct will be. In

Many people fear that decriminalization and the controlled dispensing of drugs will lead to widespread substance use among people who are now deterred from becoming addicts only by existing legal prohibitions. Like other tenets of the War on Drugs, this view entirely lacks supporting evidence. Any data on the subject points to the opposite prediction. For example, for many decades in the United Kingdom, heroin has been dispensed, under legal supervision, to addicts. The same type of program has been offered on a limited basis in other countries as well, and nowhere has it been found that this measure served in any way to entice unaddicted people into addiction. That is not surprising, given that addiction is a response to life experience, not simply to a drug. People who do not suffer the searing emotional pain that drives hardcore drug addiction will rarely fall into dependency on chemicals, even if these were more readily available — and, once more, public access to habit-forming substances is not being proposed. The call for the decriminalization of drugs for personal use does not imply legal acceptance of drug dealing. Criminalization and prevention are not identical — if anything, the first undermines the other. Paradoxical though it may seem, current drug laws against possession make drugs more readily available to potential new users than decriminalization would. Only the War on Drugs creates the raison d’être of the international trafficking industry, most of whose wealth is based on satisfying the cravings of established drug addicts. Without the exorbitant profits yielded by supplying to addicted users desperate for their substances, the illegal market would shrink to a fragment of its present size. Further, much of the street-level front-line sales force of the illicit drug trade consists of users raising money to support their habit. With the decriminalization of possession for personal use and the medically supervised distribution of drugs, the incentive to sell to new “customers,” including young kids, would largely evaporate. Policing resources could then be concentrated on the remaining large-scale traffickers — if any.

I don’t predict the demise of object-oriented programming, by the way. Object-oriented programming offers a sustainable way to write spaghetti code.

But artificial intelligence has moved on since then.7 One of the vogue ideas is called temporal difference learning. When designers created TD-Gammon, a program to play backgammon, they did not provide it with any preprogrammed chess knowledge or capacity to conduct deep searches. Instead, it made moves, predicted what would happen next, and then looked at how far its expectations were wide of the mark. That enabled it to update its expectations, which it took into the next game. In effect, TD-Gammon was a trial-and-error program. It was left to play day and night against itself, developing practical knowledge. When it was let loose on human opponents, it defeated the best in the world. The software that enabled it to learn from error was sophisticated, but its main strength was that it didn’t need to sleep, so could practice all the time.

More sophisticated methods exist, of course. A potentially more powerful method is collaborative filtering. It gathers data about what users have bought in the past and uses AI to predict what people are likely to buy in the future. These methods can use both explicit information, like a customer’s ratings of the options, and implicit information, like whether or not they finished a specific program on Netflix. Most famously, perhaps, collaborative filtering is used by Amazon in generating “People who bought this also bought . . .” listings. Collaborative filtering requires a large set of past user behavior to make predictions. This is the heart of suggestions made by Apple Music, “who to follow” suggestions on Twitter, and matches on Tinder. Yes, Tinder apparently changes the people it will show you based on your swipes. Swiping right will change who you see in the future. It’s important to realize that, in its pure form, collaborative filtering doesn’t use in-depth information about the options themselves. When Apple Music recommends a tune, it knows nothing about the song’s tempo, beat, lyrics, or instrumentation. It simply knows that people who are like you like that song too.

The information in a message equals the negative of the probabilities that you can predict what will come next every step of the way. The easier you can predict a message, the less information the message contains.

Norbert Weiner once simplified the meaning of this equation by saying that great poetry contains more information than political speeches. You never know what will come next in a truly creative poem, but in a George Bush speech you not only know what will come next, you probably could predict the whole speech, in general, before he even opens his mouth.

30 percent—Domestic equities: US stock funds, including small-, mid-, and large-cap stocks 15 percent—Developed-world international equities: funds from developed foreign countries, including the United Kingdom, Germany, and France 5 percent—Emerging-market equities: funds from developing foreign countries, such as China, India, and Brazil. These are riskier than developed-world equities, so don’t go off buying these to fill 95 percent of your portfolio. 20 percent—Real estate investment trusts: also known as REITs. REITs invest in mortgages and residential and commercial real estate, both domestically and internationally. 15 percent—Government bonds: fixed-interest US securities, which provide predictable income and balance risk in your portfolio. As an asset class, bonds generally return less than stocks. 15 percent—Treasury inflation-protected securities: also known as TIPS, these treasury notes protect against inflation. Eventually you’ll want to own these, but they’d be the last ones I’d get after investing in all the better-returning options first.

This simple idea provides a chemical explanation for an age-old question: Why does love fade? Our brains are programmed to crave the unexpected and thus to look to the future, where every exciting possibility begins. But when anything, including love, becomes familiar, that excitement slips away, and new things draw our attention. The scientists who studied this phenomenon named the buzz we get from novelty reward prediction error, and it means just what the name says.

he couldn’t change the past, couldn’t predict the future. He only had now. And that sometimes . . . the only real thing was now.

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.

A habit is a redundant set of automatic unconscious thoughts, behaviors, and emotions that develop through repetition. It’s when you’ve done something so many times that your body is programmed to become the mind. Over time, your body is dragging you to a predictable future based on what you’ve been doing in the past. Therefore, if you’re not in the present moment, you’re probably in a program. The fact is, there’s no room for the unknown in a predictable life. But being predictable is not how the unknown works. The unknown is unfamiliar, uncertain—but it’s also exciting because it occurs in ways you cannot expect or anticipate.

A habit is a redundant set of automatic unconscious thoughts, behaviors, and emotions that develop through repetition. It’s when you’ve done something so many times that your body is programmed to become the mind. Over time, your body is dragging you to a predictable future based on what you’ve been doing in the past. Therefore, if you’re not in the present moment, you’re probably in a program.

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 product 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 materialize.

habit is a redundant set of automatic unconscious thoughts, behaviors, and emotions that develop through repetition. It’s when you’ve done something so many times that your body is programmed to become the mind. Over time, your body is dragging you to a predictable future based on what you’ve been doing in the past. Therefore, if you’re not in the present moment, you’re probably in a program.

Although our body gets older, our spirit only experiences present time. So, the question is: Why can we remember the past but not predict the future? And the answer is related to our purpose as a spiritual being. If we knew the future, we could easily avoid responsibility and delay our spiritual development.

Because threads share the same memory address space and run concurrently, they can access or modify variables that other threads might be using. This is a tremendous convenience, because it makes data sharing much easier than would other inter-thread communications mechanisms. But it is also a significant risk: threads can be confused by having data change unexpectedly. Allowing multiple threads to access and modify the same variables introduces an element of nonsequentiality into an otherwise sequential programming model, which can be confusing and difficult to reason about. For a multithreaded program's behavior to be predictable, access to shared variables must be properly coordinated so that threads do not interfere with one another. Fortunately, Java provides synchronization mechanisms to coordinate such access. UnsafeSequence

Providing structure and predictability Toddlers are reassured by familiar routines, regardless of their nature. When the environment prior to placement is a healthy one, the use of transition objects that link the former caregiver’s style and schedule to the present provides the sense of structure that is important to the toddler’s developing sense of security in her new home. A consistent schedule is also important to the child who is experiencing separation anxiety. Parents should be absolutely reliable about returning when expected. It is important to help children anticipate their schedules by talking through the day’s routine. Because toddlers cannot tell time, use concrete, regularly scheduled events to help them mark time such as mealtimes or the timing of a favorite television program such as Sesame Street. Parents should make every effort to delay making additional major life changes following a toddler adoption such as moving to a new home, adding another family member, divorce, or marriage until new routines are firm and secure.

Measles has killed hundreds of millions of people throughout history, and even today accounts for hundreds of thousands of deaths annually. The disease was almost entirely eliminated in America by modern vaccination programs in the late twentieth century, but a rising anti-vaccination movement has led to a predictable uptick in the number of cases.

interest, sleeps a lot, low energy, self-medicates to improve mood BRAIN FINDINGS/NEURO-TRANSMITTER ISSUE High limbic activity, low PFC/check vitamin D and DHEA levels SUPPLEMENTS SAMe, vitamin D, or DHEA if needed MEDICATIONS Wellbutrin TYPE 5. Anxious Addicts SYMPTOMS Anxious, tense, nervous, predicts the worst, self-medicates to calm BRAIN FINDINGS/NEURO-TRANSMITTER ISSUE High basal ganglia/low GABA

As the 1970s drew to a close, and Commodore, Tandy, Altair, and Apple began to emerge from the sidelines, PARC director Bert Sutherland asked Larry Tesler to assess what some analysts were already predicting to be the coming era of “hobby and personal computers.” “I think that the era of the personal computer is here,” Tesler countered; “PARC has kept involved in the world of academic computing, but we have largely neglected the world of personal computing which we helped to found.”41 His warning went largely unheeded. Xerox Corporation’s parochial belief that computers need only talk to printers and filing cabinets and not to each other meant that the “office of the future” remained an unfulfilled promise, and in the years between 1978 and 1982 PARC experienced a dispersal of core talent that rivals the flight of Greek scholars during the declining years of Byzantium: Charles Simonyi brought the Alto’s Bravo text editing program to Redmond, Washington, where it was rebooted as Microsoft Word; Robert Metcalf used the Ethernet protocol he had invented at PARC to found the networking giant, 3Com; John Warnock and Charles Geschke, tiring of an unresponsive bureaucracy, took their InterPress page description language and founded Adobe Systems; Tesler himself brought the icon-based, object-oriented Smalltalk programming language with him when he joined the Lisa engineering team at Apple, and Tim Mott, his codeveloper of the Gypsy desktop interface, became one of the founders of Electronic Arts—five startups that would ultimately pay off the mortgages and student loans of many hundreds of industrial, graphic, and interaction designers, and provide the tools of the trade for untold thousands of others.

Survival vs. Creation illustrates the distinction between living in survival and living in creation. Living in survival entails living in stress and functioning as a materialist, believing that the outer world is more real than the inner world. When you are under the gun of the fight-or-flight nervous system, being run by its cocktail of intoxicating chemicals, you are programmed to be concerned only about your body, the things or people in your environment, and your obsession with time. Your brain and body are out of balance. You are living a predictable life. However, when you are truly in the elegant state of creation, you are no body, no thing, no time—you forget about yourself. You become pure consciousness, free from the chains of the identity that needs the outer reality to remember who it thinks it is.

and the amount of protection afforded a child by a resource (like an alcohol and drug prevention program) cannot be predicted without also accounting for the nature of the child’s strengths and challenges

There is no logical reason to think that a tire company should be a food critic, but a hundred years ago, Michelin tires started reviewing rural restaurants to encourage people living in the cities to drive farther and wear their tires out more quickly. Guinness created the Guinness Book of World Records to reinforce its brand and give people something to talk about in the pubs. Similarly, I predict that one day a brand like Nike could put out its own sports programming and compete successfully against ESPN, or Amtrak could launch a publication that could stand up to Travel + Leisure.

He explained that unlike our other classes in the program, research was all about prediction and control. I was smitten. You mean that rather than leaning and holding, I could spend my career predicting and controlling? I had found my calling.

It’s safe to predict this result, and not just because I have seen it many times in the companies I work with. It is a straightforward prediction of the Lean Startup theory itself. When people are used to evaluating their productivity locally, they feel that a good day is one in which they did their job well all day. When I worked as a programmer, that meant eight straight hours of programming without interruption. That was a good day. In contrast, if I was interrupted with questions, process, or—heaven forbid—meetings, I felt bad. What did I really accomplish that day? Code and product features were tangible to me; I could see them, understand them, and show them off. Learning, by contrast, is frustratingly intangible.

something differently, I wouldn’t be in the predicament I’m in. It’s your fault, and I’m not responsible.” Whenever you blame someone else for the problems in your life, you become powerless to change anything. The “blame game” hurts your personal sense of power. Stay away from blaming thoughts. You have to take personal responsibility for your problems before you can hope to change them. Summary of ANT Species 1. “Always/never” thinking: thinking in words like always, never, no one, everyone, every time, everything 2. Focusing on the negative: seeing only the bad in a situation 3. Fortune-telling: predicting the worst

I don’t predict the demise of object-oriented programming, by the way. Though I don’t think it has much to offer good programmers, except in certain specialized domains, it is irresistible to large organizations. Object-oriented programming offers a sustainable way to write spaghetti code. It lets you accrete programs as a series of patches. Large organizations always tend to develop software this way, and I expect this to be as true in a hundred years as it is today.

In an unpredictable environment, this approach quickly falters. The longer and more rigorously we persist with it, the more quickly and completely things will break down. The environment we are in creates gaps between plans, actions, and outcomes: The gap between plans and outcomes concerns knowledge: It is the difference between what we would like to know and what we actually know. It means that we cannot create perfect plans. The gap between plans and actions concerns alignment: It is the difference between what we would like people to do and what they actually do. It means that even if we encourage them to switch off their brains, we cannot know enough about them to program them perfectly. The gap between actions and outcomes concerns effects: It is the difference between what we hope our actions will achieve and what they actually achieve. We can never fully predict how the environment will react to what we do. It means that we cannot know in advance exactly what outcomes the actions of our organization are going to create.

The emergence of life and intelligence from less-alive and less-intelligent components has happened at least once. Emergent behavior is that which cannot be predicted through analysis at any level simpler than that of the system as a whole. Explanations of emergence, like simplifications of complexity, are inherently illusory and can only be achieved by sleight of hand. This does not mean that emergence is not real. Emergent behavior, by definition, is what’s left after everything else has been explained. “Emergence offers a way to believe in physical causality while simultaneously maintaining the impossibility of a reductionist explanation of thought,” wrote W. Daniel Hillis, a computer architect who believes that architecture and programming can only go so far, after which intelligence has to be allowed to evolve on its own. “For those who fear mechanistic explanations of the human mind, our ignorance of how local interactions produce emergent behavior offers a reassuring fog in which to hide the soul.”33 Although individual computers and individual computer programs are developing the elements of artificial intelligence, it is in the larger networks (or the network at large) that we are developing a more likely medium for the emergence of the Leviathan of artificial mind.