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materialism is not the greedy desire for material goods, but rather the belief that the fundamental reality of the world is material;

idealism is not the aspiration toward lofty and laudable goals, but rather the belief that the fundamental reality of the world is mental or idea-like. English-speaking philosophers today tend to speak of “physicalism” or “naturalism” rather than materialism (perhaps to avoid confusion with the Wall Street sense of the term). At the same time, Anglo-American historians of philosophy continue to find the distinction between materialism and idealism a useful one in our attempts at categorizing past schools of thought. Democritus and La Mettrie were materialists; Hobbes was pretty close. Berkeley and Kant were idealists; Leibniz may have been.

And it was these paradoxes that led the Irish philosopher to conclude that talk of matter was but a case of multiplying entities beyond necessity. For Berkeley, all we can know are ideas, and for this reason it made sense to suppose that the world itself consists in ideas.

Soviet and Western Marxists alike, by stark contrast, and before them the French “vulgar” (i.e., non-dialectical) materialists of the 18th century, saw and see the material world as the base and cause of all mental activity, as both bringing ideas into existence, and also determining the form and character of a society’s ideas in accordance with the state of its technology, its methods of resource extraction and its organization of labor. So here to focus on the material is not to become distracted from the true source of being, but rather to zero right in on it.

one great problem with the concept of materialism is that it says very little in itself. What is required in addition is an elaboration of what a given thinker takes matter, or ideas, to be. It may not be just the Marxist aftertaste, but also the fact that the old common-sense idea about matter as brute, given stuff has turned out to have so little to do with the way the physical world actually is, that has led Anglo-American philosophers to prefer to associate themselves with the “physical” or the “natural” rather than with the material.  Reality, they want to say, is just what is natural, while everything else is in turn “supernatural” (this distinction has its clarity going for it, but it also seems uncomfortably close to tautology). Not every philosopher has a solid grasp of subatomic physics, but most know enough to grasp that, even if reality is eventually exhaustively accounted for through an enumeration of the kinds of particles and a few basic forces, this reality will still look nothing like what your average person-in-the-street takes reality to be.

The 18th-century idealist philosopher George Berkeley strongly believed that matter was only a fiction contrived by philosophers in the first place, for which the real people had no need. For Berkeley, there was never anything common-sensical about matter. We did not need to arrive at the era of atom-splitting and wave-particle duality, then, in order for the paradoxes inherent in matter to make themselves known (is it infinitely divisible or isn’t it?

Central to this performance was the concept of  “materialism.” The entire history of philosophy, in fact, was portrayed in Soviet historiography as a series of matches between the materialist home-team and its “idealist” opponents, beginning roughly with Democritus (good) and Plato (bad), and culminating in the opposition between official party philosophy and logical positivism, the latter of which was portrayed as a shrouded variety of idealism. Thus from the “Short Philosophical Dictionary,” published in Moscow in 1951, we learn that the school of logical empiricism represented by Rudolf Carnap, Otto Neurath and others, “is a form of subjective idealism, characteristic of degenerating bourgeois philosophy in the epoch of the decline of capitalism.”Now the Soviet usage of this pair of terms appears to fly in the face of our ordinary, non-philosophical understanding of them (that, for example,  Wall Street values are “materialist,” while the Occupy movement is “idealist”). One might have thought that the communists should be flinging the “materialist” label at their capitalist enemies, rather than claiming it for themselves. One might also have thought that the Bolshevik Revolution and the subsequent failed project of building a workers’ utopia was nothing if not idealistic.

Consider money. Though it might sometimes be represented by bank notes or coins, money is an immaterial thing par excellence, and to seek to acquire it is to move on the plane of ideas. Of course, money can also be converted into material things, yet it seems simplistic to suppose that we want money only in order to convert it into the material things we really want, since even these material things aren’t just material either: they are symbolically dense artifacts, and they convey to others certain ideas about their owners. This, principally, is why their owners want them, which is to say that materialists (in the everyday sense) are trading in ideas just as much as anyone else.

In the end no one really cares about stuff itself. Material acquisitions — even, or perhaps especially, material acquisitions of things like Rolls Royces and Rolexes — are maneuvers within a universe of materially instantiated ideas. This is human reality, and it is within this reality that mystics, scientists, and philosophers alike are constrained to pursue their various ends, no matter what they might take the ultimate nature of the external world to be.

For Bronowski, science and art were two neighboring mighty rivers that flowed from a common source: the human imagination.

For Dr. Bronowski, there was no absolute knowledge and anyone who claims it — whether a scientist, a politician or a religious believer — opens the door to tragedy. All scientific information is imperfect and we have to treat it with humility. Such, for him, was the human condition.

This is the condition for what we can know, but it is also, crucially, a moral lesson. It is the lesson of 20th-century painting from Cubism onwards, but also that of quantum physics. All we can do is to push deeper and deeper into better approximations of an ever-evasive reality

Errors are inextricably bound up with pursuit of human knowledge, which requires not just mathematical calculation but insight, interpretation and a personal act of judgment for which we are responsible.

Dr. Bronowski insisted that the principle of uncertainty was a misnomer, because it gives the impression that in science (and outside of it) we are always uncertain. But this is wrong. Knowledge is precise, but that precision is confined within a certain toleration of uncertainty.

The emphasis on the moral responsibility of knowledge was essential for all of Dr. Bronowski’s work. The acquisition of knowledge entails a responsibility for the integrity of what we are as ethical creatures.

Pursuing knowledge means accepting uncertainty. Heisenberg’s principle has the consequence that no physical events can ultimately be described with absolute certainty or with “zero tolerance,” as it were. The more we know, the less certain we are.

Our relations with others also require a principle of tolerance. We encounter other people across a gray area of negotiation and approximation. Such is the business of listening and the back and forth of conversation and social interaction.

For Dr. Bronowski, the moral consequence of knowledge is that we must never judge others on the basis of some absolute, God-like conception of certainty. All knowledge, all information that passes between human beings, can be exchanged only within what we might call “a play of tolerance,” whether in science, literature, politics or religion.

The play of tolerance opposes the principle of monstrous certainty that is endemic to fascism and, sadly, not just fascism but all the various faces of fundamentalism. When we think we have certainty, when we aspire to the knowledge of the gods, then Auschwitz can happen and can repeat itself.

The pursuit of scientific knowledge is as personal an act as lifting a paintbrush or writing a poem, and they are both profoundly human. If the human condition is defined by limitedness, then this is a glorious fact because it is a moral limitedness rooted in a faith in the power of the imagination, our sense of responsibility and our acceptance of our fallibility. We always have to acknowledge that we might be mistaken.

Even doctors—those whose business is to treat others humanely— can remain disengaged from the minds of their patients, particularly when those patients are easily seen as different from the doctors themselves. Until the early 1990s, for instance, it was routine practice for infants to undergo surgery without anesthesia. Why? Because at the time, doctors did not believe that infants were able to experience pain, a fundamental capacity of the human mind.

Your sixth sense functions only when you engage it. When you do not, you may fail to recognize a fully human mind that is right before your eyes.

Although it is indeed true that the ability to read the minds of others exists along a spectrum with stable individual differences, I believe that the more useful knowledge comes from understanding the moment-to-moment, situational influences that can lead even the most social person—yes, even you and me—to treat others as mindless animals or objects.

None of the cases described in this chapter so far involve people with chronic and stable personality disorders. Instead, they all come from predictable contexts in which people’s sixth sense remained disengaged for one fundamental reason: distance.

This three-part chain—sharing attention, imitating action, and imitation creating experience—shows one way in which your sixth sense works through your physical senses. More important, it also shows how your sixth sense could remain disengaged, leaving you disconnected from the minds of others. Close your eyes, look away, plug your ears, stand too far away to see or hear, or simply focus your attention elsewhere, and your sixth sense may not be triggered.

Distance keeps your sixth sense disengaged for at least two reasons. First, your ability to understand the minds of others can be triggered by your physical senses. When you’re too far away in physical space, those triggers do not get pulled. Second, your ability to understand the minds of others is also engaged by your cognitive inferences. Too far away in psychological space—too different, too foreign, too other—and those triggers, again, do not get pulled

For psychologists, distance is not just physical space. It is also psychological space, the degree to which you feel closely connected to someone else. You are describing psychological distance when you say that you feel “distant” from your spouse, “out of touch” with your kids’ lives, “worlds apart” from a neighbor’s politics, or “separated” from your employees. You don’t mean that you are physically distant from other people; you mean that you feel psychologically distant from them in some way

Interviews with U.S. soldiers in World War II found that only 15 to 20 percent were able to discharge their weapons at the enemy in close firefights. Even when they did shoot, soldiers found it hard to hit their human targets. In the U.S. Civil War, muskets were capable of hitting a pie plate at 70 yards and soldiers could typically reload anywhere from 4 to 5 times per minute. Theoretically, a regiment of 200 soldiers firing at a wall of enemy soldiers 100 feet wide should be able to kill 120 on the first volley. And yet the kill rate during the Civil War was closer to 1 to 2 men per minute, with the average distance of engagement being only 30 yards.

Modern armies now know that they have to overcome these empathic urges, so soldiers undergo relentless training that desensitizes them to close combat, so that they can do their jobs. Modern technology also allows armies to kill more easily because it enables killing at such a great physical distance. Much of the killing by U.S. soldiers now comes through the hands of drone pilots watching a screen from a trailer in Nevada, with their sixth sense almost completely disengaged.

Other people obviously do not need to be standing right in front of you for you to imagine what they are thinking or feeling or planning. You can simply close your eyes and imagine it.

The MPFC and a handful of other brain regions undergird the inferential component of your sixth sense. When this network of brain regions is engaged, you are thinking about others’ minds. Failing to engage this region when thinking about other people is then a solid indication that you’re overlooking their minds.

Research confirms that the MPFC is engaged more when you’re thinking about yourself, your close friends and family, and others who have beliefs similar to your own. It is activated when you care enough about others to care what they are thinking, and not when you are indifferent to others

As people become more and more different from us, or more distant from our immediate social networks, they become less and less likely to engage our MPFC. When we don’t engage this region, others appear relatively mindless, something less than fully human.

The mistake that can arise when you fail to engage with the minds of others is that you may come to think of them as relatively mindless. That is, you may come to think that these others have less going on between their ears than, say, you do.

It’s not only free will that other minds might seem to lack. This lesser minds effect has many manifestations, including what appears to be a universal tendency to assume that others’ minds are less sophisticated and more superficial than one’s own. Members of distant out-groups, ranging from terrorists to poor hurricane victims to political opponents, are also rated as less able to experience complicated emotions, such as shame, pride, embarassment, and guilt than close members of one’s own group.

There’s also a subset of this progressive story pattern that I’m particularly interested in, and that’s the “conceptual breakthrough” story, where the characters discover something about the nature of the universe which radically expands their understanding of the world.  This is a classic science fiction storyline.

one of the cool things about science fiction is that it lets you dramatize the process of scientific discovery, that moment of suddenly understanding something about the universe. That is what scientists find appealing about science, and I enjoy seeing the same thing in science fiction.

when you mention myth or mythic structure, yes, I don’t think myths can do that, because in general, myths reflect a pre-industrial view of the world. I don’t know if there is room in mythology for a strong conception of the future, other than an end-of-the-world or Armageddon scenario …

there is a risk that a radical capitalistic ideology could spread which refuses even to consider these problems, in the a priori belief that any attempt to solve them is doomed to failure and which blindly entrusts their solution to the free development of market forces.

Could anyone have offered a more potent critique of current Republican ideology than John Paul II? Could anything better illustrate John Paul II’s critique of radical capitalist ideology than the GOP’s refusal to be concerned in any way about a fundamental question like access to basic healthcare for millions of citizens in the richest country on earth?

And in the Church of Limbaugh, market capitalism is an unqualified, eternal good. It is the ever-lasting truth about human beings. It is inextricable from any concept of human freedom. The fewer restrictions on it, the better.

the Pope is not making an empirical observation. In so far as he is, he agrees with you. What he’s saying is that this passion for material things is not what makes us good or happy. That’s all

if the mania for more and more materialist thrills distracts us from, say, the plight of a working American facing bankruptcy because of cancer, or the child of an illegal immigrant with no secure home, then it is a deeply immoral distraction.

material goods are not self-evidently the purpose of life and are usually (and in Jesus’ stern teachings always) paths away from God and our own good and our own happiness.

Christianity is one of the most powerful critiques of radical market triumphalism.

Neuroscientists assume that these mental powers somehow emerge from the electrical signaling of neurons — the circuitry of the brain. But no one has come close to explaining how that occurs. Continue reading the main story Continue reading the main story That, Dr. Nagel proposes, might require another revolution: showing that mind, along with matter and energy, is “a fundamental principle of nature” — and that we live in a universe primed “to generate beings capable of comprehending it.” Rather than being a blind series of random mutations and adaptations, evolution would have a direction, maybe even a purpose.

“Above all,” he wrote, “I would like to extend the boundaries of what is not regarded as unthinkable, in light of how little we really understand about the world.”

Dr. Tegmark, in his new book, “Our Mathematical Universe: My Quest for the Ultimate Nature of Reality,” turns the idea on its head: The reason mathematics serves as such a forceful tool is that the universe is a mathematical structure. Going beyond Pythagoras and Plato, he sets out to show how matter, energy, space and time might emerge from n

the mathematician Edward Frenkel noted that only a small part of the vast ocean of mathematics appears to describe the real world. The rest seems to b

The real payoff in subscribing to the idea of a brain as a computer would come from using that idea to profitably guide research. In an article last fall in the journal Science, two of my colleagues (Adam Marblestone of M.I.T. and Thomas Dean of Google) and I endeavored to do just that, suggesting that a particular kind of computer, known as the field programmable gate array, might offer a preliminary starting point for thinking about how the brain works.

FIELD programmable gate arrays consist of a large number of “logic block” programs that can be configured, and reconfigured, individually, to do a wide range of tasks. One logic block might do arithmetic, another signal processing, and yet another look things up in a table. The computation of the whole is a function of how the individual parts are configured. Much of the logic can be executed in parallel, much like what happens in a brain.

our suggestion is that the brain might similarly consist of highly orchestrated sets of fundamental building blocks, such as “computational primitives” for constructing sequences, retrieving information from memory, and routing information between different locations in the brain. Identifying those building blocks, we believe, could be the Rosetta stone that unlocks the brain.

it is unlikely that we will ever be able to directly connect the language of neurons and synapses to the diversity of human behavior, as many neuroscientists seem to hope. The chasm between brains and behavior is just too vast.

Our best shot may come instead from dividing and conquering. Fundamentally, that may involve two steps: finding some way to connect the scientific language of neurons and the scientific language of computational primitives (which would be comparable in computer science to connecting the physics of electrons and the workings of microprocessors); and finding some way to connect the scientific language of computational primitives and that of human behavior (which would be comparable to understanding how computer programs are built out of more basic microprocessor instructions).

If neurons are akin to computer hardware, and behaviors are akin to the actions that a computer performs, computation is likely to be the glue that binds the two.

Medieval science was guided by "logical consistency."

The logical empiricist's conception of scientific progress was thus a continuous one; more comprehensive theory replaced compatible, older theory

Hempel also believed that science evolved in a continuous manner. New theory did not contradict past theory: "theory does not simply refute the earlier empirical generalizations in its field; rather, it shows that within a certain limited range defined by qualifying conditions, the generalizations hold true in fairly close approximation." [21]

movement combined induction, based on empiricism, and deduction in the form of logic

e notion of scientific realism held by Newton led to the evolutionary view of the progress of science

he entities and processes of theory were believed to exist in nature, and science should discover those entities and processes

Particularly disturbing discoveries were made in the area of atomic physics. For instance, Heisenberg's indeterminacy (25)principle, according to historian of science Cecil Schneer, yielded the conclusion that "the world of nature is indeterminate.

"even the fundamental principle of causality fail[ed] ."

was not until the second half of the twentieth century that the preservers of the evolutionary idea of scientific progress, the logical empiricists, were seriously challenged

revolutionary model of scientific change and examined the role of the scientific community in preventing and then accepting change. Kuhn's conception of scientific change occurring through revolutions undermined the traditional scientific goal, finding "truth" in nature

Textbooks inform scientists-to-be about this common body of knowledge and understanding.

for the world is too huge and complex to be explored randomly.

a scientist knows what facts are relevant and can build on past research

Normal science, as defined by Kuhn, is cumulative. New knowledge fills a gap of ignorance

ne standard product of the scientific enterprise is missing. Normal science does not aim at novelties of fact or theory and, when successful, finds none."

ntain a mechanism that uncovers anomaly, inconsistencies within the paradigm.

eventually, details arise that are inconsistent with the current paradigm

hese inconsistencies are eventually resolved or are ignored.

y concern a topic of central importance, a crisis occurs and normal science comes to a hal

that the scientists re-examine the foundations of their science that they had been taking for granted

it resolves the crisis better than the others, it offers promise for future research, and it is more aesthetic than its competitors. The reasons for converting to a new paradigm are never completely rational.

Unlike evolutionary science, in which new knowledge fills a gap of ignorance, in Kuhn's model new knowledge replaces incompatible knowledge.

In a sense, we have circled back to the ancient and medieval practice of separating scientific theory from physical reality; both medieval scientists and Kuhn would agree that no theory corresponds to reality and therefore any number of theories might equally well explain a natural phenomenon. [36] Neither twentieth-century atomic theorists nor medieval astronomers are able to claim that their theories accurately describe physical phenomena. The inability to return to scientific realism suggests a tripartite division of the history of science, with a period of scientific realism fitting between two periods in which there is no insistence that theory correspond to reality. Although both scientific realism and the evolutionary idea of scientific progress appeal to common sense, both existed for only a few hundred years.

Perhaps more fundamental, the rules that shape how the bricoleur selects the various elements have also changed. Religion is far less formative of our public discourse and culture in the deep, constitutive way that it was even as recently as the postwar period, due in large part to the rise of neo-liberalism.

if we ask Americans a range of questions about matters that extend beyond their immediate horizons, we would be somewhat amazed by the blind spots in our thinking. Ignorance about religion might very well extend to ignorance about geopolitical concerns or about other cultures generally. What is striking, and simultaneously disturbing, is the degree to which our comfort and certainty about ourselves as Americans and about the world we inhabit enable us to settle into a kind of willful ignorance. So I am not inclined to single out religion in this regard; something more fundamental has been revealed

To take seriously the results of the Pew quiz leads us to question the substance of our national commitment to religious tolerance and pluralism. If our knowledge of other religions (even our own) is shoddy, then what constitutes the substance of our toleration of others? Is it simply a procedural concern? And, more importantly, if we fail to know basic facts about others, do we make it easier to retreat into the comfort of insular spaces, deaf to the claims of others? Do we expect, at the end of the day, no matter our public announcements to the contrary, that all others should sound and believe as the majority of Americans do?

The Pew Forum’s Religious Knowledge Survey examines one type of religious knowledge: knowledge-that. Respondents were asked whether certain propositions about world religions were true. But it is an open question whether this really is the sort of knowledge that we have in mind when we are talking about religious knowledge. At least sometimes, it seems like we mean knowledge-how.

The unwritten premise of the survey is that belief ought to be individual, considered, and fully-informed. But that premise fits neither religious experience nor human subjectivity over the long term. Thus to ask these questions in this way is to presume a particular kind of religious subject that is largely nonexistent, then to take pleasure in clucking over its nonexistence.

what if religion is not primarily about knowledge? What if the defining core of religion is more like a way of life, a nexus of action? What if, as per Charles Taylor, a religious orientation is more akin to a “social imaginary,” which functions as an “understanding” on a register that is somewhat inarticulable? Indeed, I think Taylor’s corpus offers multiple resources for criticizing what he would describe as the “intellectualism” of such approaches to religion—methodologies that treat human persons as “thinking things,” and thus reduce religious phenomena to a set of ideas, beliefs, and propositions. Taylor’s account of social imaginaries reminds us of a kind of understanding that is “carried” in practices, implicit in rituals and routines, and can never be adequately articulated or made explicit. If we begin to think about religion more like a social imaginary than a set of propositions and beliefs, then the methodologies of surveys of religious “knowledge” are going to look problematic.

I’m reminded of an observation Wittgenstein makes in the Philosophical Investigations: One could be a master of a game without being able to articulate the rules.

belief, faith and knowledge, Pew Forum on Religion and Public Life, religion and science, religion in the U.S., religious literacy, surveys, U.S. Religious Knowledge Survey

appealing to another method won’t help either — for unless that method can be shown to be reliable, using it to determine the reliability of the first method answers nothing.

Every one of our beliefs is produced by some method or source, be it humble (like memory) or complex (like technologically assisted science). But why think our methods, whatever they are, are trustworthy or reliable for getting at the truth? If I challenge one of your methods, you can’t just appeal to the same method to show that it is reliable. That would be circular

How do we rationally defend our most fundamental epistemic principles? Like many of the best philosophical mysteries, this a problem that can seem both unanswerable and yet extremely important to solve.

it seems to suggest that in the end, all “rational” explanations end up grounding out on something arbitrary. It all just comes down to what you happen to believe, what you feel in your gut, your faith.  Human beings have historically found this to be a very seductive idea,

this is precisely the situation we seem to be headed towards in the United States. We live isolated in our separate bubbles of information culled from sources that only reinforce our prejudices and never challenge our basic assumptions. No wonder that — as in the debates over evolution, or what to include in textbooks illustrate — we so often fail to reach agreement over the history and physical structure of the world itself. No wonder joint action grinds to a halt. When you can’t agree on your principles of evidence and rationality, you can’t agree on the facts. And if you can’t agree on the facts, you can hardly agree on what to do in the face of the facts.

We can’t decide on what counts as a legitimate reason to doubt my epistemic principles unless we’ve already settled on our principles—and that is the very issue in question.

The problem that skepticism about reason raises is not about whether I have good evidence by my principles for my principles. Presumably I do.[1] The problem is whether I can give a more objective defense of them. That is, whether I can give reasons for them that can be appreciated from what Hume called a “common point of view” — reasons that can “move some universal principle of the human frame, and touch a string, to which all mankind have an accord and symphony.”[2]

Any way you go, it seems you must admit you can give no reason for trusting your methods, and hence can give no reason to defend your most fundamental epistemic principles.

So one reason we should take the project of defending our epistemic principles seriously is that the ideal of civility demands it.

there is also another, even deeper, reason. We need to justify our epistemic principles from a common point of view because we need shared epistemic principles in order to even have a common point of view. Without a common background of standards against which we measure what counts as a reliable source of information, or a reliable method of inquiry, and what doesn’t, we won’t be able to agree on the facts, let alone values.

democracies aren’t simply organizing a struggle for power between competing interests; democratic politics isn’t war by other means. Democracies are, or should be, spaces of reasons.

we need an epistemic common currency because we often have to decide, jointly, what to do in the face of disagreement.

Sometimes we can accomplish this, in a democratic society, by voting. But we can’t decide every issue that way

We need some forms of common currency before we get to the voting booth.

Even if, as the skeptic says, we can’t defend the truth of our principles without circularity, we might still be able to show that some are better than others. Observation and experiment, for example, aren’t just good because they are reliable means to the truth. They are valuable because almost everyone can appeal to them. They have roots in our natural instincts, as Hume might have said.

that is one reason we need to resist skepticism about reason: we need to be able to give reasons for why some standards of reasons — some epistemic principles — should be part of that currency and some not.

Reasons for Reason By MICHAEL P. LYNCH

The rejection of science seems to be part of a politically monolithic red-state fundamentalism, textbook evidence of an unyielding ignorance on the part of the religious. As one fundamentalist slogan puts it, “The Bible says it, I believe it, that settles it.”

But in fact their rejection of knowledge amounts to what the evangelical historian Mark A. Noll, in his 1994 book, “The Scandal of the Evangelical Mind,” described as an “intellectual disaster.” He called on evangelicals to repent for their neglect of the mind, decrying the abandonment of the intellectual heritage of the Protestant Reformation. “The scandal of the evangelical mind,” he wrote, “is that there is not much of an evangelical mind.”

Scholars like Dr. Collins and Mr. Noll, and publications like Books & Culture, Sojourners and The Christian Century, offer an alternative to the self-anointed leaders. They recognize that the Bible does not condemn evolution and says next to nothing about gay marriage. They understand that Christian theology can incorporate Darwin’s insights and flourish in a pluralistic society.

meaning is an uplifting state of consciousness. It’s what you feel when you’re serving things beyond self.

Meaningfulness tries to replace structures, standards and disciplines with self-regarding emotion. The ultimate authority of meaningful is the warm tingling we get when we feel significant and meaningful.

They subscribed to moral systems — whether secular or religious — that recommended specific ways of being, and had specific structures of what is right and wrong, and had specific disciplines about how you might get better over time.

If we look at the people in history who achieved great things — like Nelson Mandela or Albert Schweitzer or Abraham Lincoln — it wasn’t because they wanted to bathe luxuriously in their own sense of meaningfulness. They had objective and eternally true standards of justice and injustice. They were indignant when those eternal standards were violated.

Meaningfulness tries to replace moral systems with the emotional corona that surrounds acts of charity.

Because meaningfulness is built solely on an emotion, it is contentless and irreducible. Because it is built solely on emotion, it’s subjective and relativistic. You get meaning one way. I get meaning another way. Who is any of us to judge another’s emotion?

Because it’s based solely on sentiment, it is useless. There are no criteria to determine what kind of meaningfulness is higher. There’s no practical manual that would help guide each of us as we move from shallower forms of service to deeper ones. There is no hierarchy of values that would help us select, from among all the things we might do, that activity which is highest and best to do.

Because it’s based solely on emotion, it’s fleeting. When the sensations of meaningful go away then the cause that once aroused them gets dropped, too. Ennui floods in. Personal crisis follows. There’s no reliable ground.

The philosophy of meaningfulness emerges in a culture in which there is no common moral vocabulary or framework. It emerges amid radical pluralism, when people don’t want to judge each other. Meaningfulness emerges when the fundamental question is, do we feel good?

Real moral systems are based on a balance of intellectual rigor and aroused moral sentiments.

Empowered by their own sources of information and their own interpretations of research, doubters have declared war on the consensus of experts.

Our lives are permeated by science and technology as never before. For many of us this new world is wondrous, comfortable, and rich in rewards—but also more complicated and sometimes unnerving. We now face risks we can’t easily analyze.

The world crackles with real and imaginary hazards, and distinguishing the former from the latter isn’t easy.

In this bewildering world we have to decide what to believe and how to act on that. In principle that’s what science is for.

“Science is not a body of facts,” says geophysicist Marcia McNutt,

“Science is a method for deciding whether what we choose to believe has a basis in the laws of nature or not.”

The scientific method leads us to truths that are less than self-evident, often mind-blowing, and sometimes hard to swallow.

We don’t believe you.

Galileo was put on trial and forced to recant. Two centuries later Charles Darwin escaped that fate. But his idea that all life on Earth evolved from a primordial ancestor and that we humans are distant cousins of apes, whales, and even deep-sea mollusks is still a big ask for a lot of people. So is another 19th-century notion: that carbon dioxide, an invisible gas that we all exhale all the time and that makes up less than a tenth of one percent of the atmosphere, could be affecting Earth’s climate.

we intellectually accept these precepts of science, we subconsciously cling to our intuitions

Shtulman’s research indicates that as we become scientifically literate, we repress our naive beliefs but never eliminate them entirely. They lurk in our brains, chirping at us as we try to make sense of the world.

Most of us do that by relying on personal experience and anecdotes, on stories rather than statistics.

We have trouble digesting randomness; our brains crave pattern and meaning.

we can deceive ourselves.

Even for scientists, the scientific method is a hard discipline. Like the rest of us, they’re vulnerable to what they call confirmation bias—the tendency to look for and see only evidence that confirms what they already believe. But unlike the rest of us, they submit their ideas to formal peer review before publishing them

other scientists will try to reproduce them

Scientific results are always provisional, susceptible to being overturned by some future experiment or observation. Scientists rarely proclaim an absolute truth or absolute certainty. Uncertainty is inevitable at the frontiers of knowledge.

Many people in the United States—a far greater percentage than in other countries—retain doubts about that consensus or believe that climate activists are using the threat of global warming to attack the free market and industrial society generally.

news media give abundant attention to such mavericks, naysayers, professional controversialists, and table thumpers. The media would also have you believe that science is full of shocking discoveries made by lone geniuses

science tells us the truth rather than what we’d like the truth to be. Scientists can be as dogmatic as anyone else—but their dogma is always wilting in the hot glare of new research.

But industry PR, however misleading, isn’t enough to explain why only 40 percent of Americans, according to the most recent poll from the Pew Research Center, accept that human activity is the dominant cause of global warming.

“science communication problem,”

yielded abundant new research into how people decide what to believe—and why they so often don’t accept the scientific consensus.

higher literacy was associated with stronger views—at both ends of the spectrum. Science literacy promoted polarization on climate, not consensus. According to Kahan, that’s because people tend to use scientific knowledge to reinforce beliefs that have already been shaped by their worldview.

“egalitarian” and “communitarian” mind-set are generally suspicious of industry and apt to think it’s up to something dangerous that calls for government regulation; they’re likely to see the risks of climate change.

“hierarchical” and “individualistic” mind-set respect leaders of industry and don’t like government interfering in their affairs; they’re apt to reject warnings about climate change, because they know what accepting them could lead to—some kind of tax or regulation to limit emissions.

For a hierarchical individualist, Kahan says, it’s not irrational to reject established climate science: Accepting it wouldn’t change the world, but it might get him thrown out of his tribe.

Science appeals to our rational brain, but our beliefs are motivated largely by emotion, and the biggest motivation is remaining tight with our peers.

organizations funded in part by the fossil fuel industry have deliberately tried to undermine the public’s understanding of the scientific consensus by promoting a few skeptics.

Internet makes it easier than ever for climate skeptics and doubters of all kinds to find their own information and experts

Internet has democratized information, which is a good thing. But along with cable TV, it has made it possible to live in a “filter bubble” that lets in only the information with which you already agree.

How to convert climate skeptics? Throwing more facts at them doesn’t help.

people need to hear from believers they can trust, who share their fundamental values.

We believe in scientific ideas not because we have truly evaluated all the evidence but because we feel an affinity for the scientific community.

“Believing in evolution is just a description about you. It’s not an account of how you reason.”

evolution actually happened. Biology is incomprehensible without it. There aren’t really two sides to all these issues. Climate change is happening. Vaccines really do save lives. Being right does matter—and the science tribe has a long track record of getting things right in the end. Modern society is built on things it got right.

Doubting science also has consequences.

In the climate debate the consequences of doubt are likely global and enduring. In the U.S., climate change skeptics have achieved their fundamental goal of halting legislative action to combat global warming.

“That line between science communication and advocacy is very hard to step back from,”

It’s their very detachment, what you might call the cold-bloodedness of science, that makes science the killer app.

that need to fit in is so strong that local values and local opinions are always trumping science.

not a sin to change your mind when the evidence demands it.

for the best scientists, the truth is more important than the tribe.

Students come away thinking of science as a collection of facts, not a method.

Shtulman’s research has shown that even many college students don’t really understand what evidence is.

“Everybody should be questioning,” says McNutt. “That’s a hallmark of a scientist. But then they should use the scientific method, or trust people using the scientific method, to decide which way they fall on those questions.”

science has made us the dominant organisms,

incredibly rapid change, and it’s scary sometimes. It’s not all progress.

It is clear that these products are designed to be maximally addictive, in order to harvest as much of our attention as they can. Tech humanists say this business model is both unhealthy and inhumane – that it damages our psychological well-being and conditions us to behave in ways that diminish our humanity

The main solution that they propose is better design. By redesigning technology to be less addictive and less manipulative, they believe we can make it healthier – we can realign technology with our humanity and build products that don’t “hijack” our minds.

its most prominent spokesman is executive director Tristan Harris, a former “design ethicist” at Google who has been hailed by the Atlantic magazine as “the closest thing Silicon Valley has to a conscience”. Harris has spent years trying to persuade the industry of the dangers of tech addiction.

In February, Pierre Omidyar, the billionaire founder of eBay, launched a related initiative: the Tech and Society Solutions Lab, which aims to “maximise the tech industry’s contributions to a healthy society”.

the tech humanists are making a bid to become tech’s loyal opposition. They are using their insider credentials to promote a particular diagnosis of where tech went wrong and of how to get it back on track

The real reason tech humanism matters is because some of the most powerful people in the industry are starting to speak its idiom. Snap CEO Evan Spiegel has warned about social media’s role in encouraging “mindless scrambles for friends or unworthy distractions”,

In short, the effort to humanise computing produced the very situation that the tech humanists now consider dehumanising: a wilderness of screens where digital devices chase every last instant of our attention.

After years of ignoring their critics, industry leaders are finally acknowledging that problems exist. Tech humanists deserve credit for drawing attention to one of those problems – the manipulative design decisions made by Silicon Valley.

these decisions are only symptoms of a larger issue: the fact that the digital infrastructures that increasingly shape our personal, social and civic lives are owned and controlled by a few billionaires

Because it ignores the question of power, the tech-humanist diagnosis is incomplete – and could even help the industry evade meaningful reform

Taken up by leaders such as Zuckerberg, tech humanism is likely to result in only superficial changes

they will not address the origin of that anger. If anything, they will make Silicon Valley even more powerful.

To the litany of problems caused by “technology that extracts attention and erodes society”, the text asserts that “humane design is the solution”. Drawing on the rhetoric of the “design thinking” philosophy that has long suffused Silicon Valley, the website explains that humane design “starts by understanding our most vulnerable human instincts so we can design compassionately”

this language is not foreign to Silicon Valley. On the contrary, “humanising” technology has long been its central ambition and the source of its power. It was precisely by developing a “humanised” form of computing that entrepreneurs such as Steve Jobs brought computing into millions of users’ everyday lives

Facebook had a new priority: maximising “time well spent” on the platform, rather than total time spent. By “time well spent”, Zuckerberg means time spent interacting with “friends” rather than businesses, brands or media sources. He said the News Feed algorithm was already prioritising these “more meaningful” activities.

Tech humanists say they want to align humanity and technology. But this project is based on a deep misunderstanding of the relationship between humanity and technology: namely, the fantasy that these two entities could ever exist in separation.

They believe we can use better design to make technology serve human nature rather than exploit and corrupt it. But this idea is drawn from the same tradition that created the world that tech humanists believe is distracting and damaging us.

The story of our species began when we began to make tools

All of which is to say: humanity and technology are not only entangled, they constantly change together.

This is not just a metaphor. Recent research suggests that the human hand evolved to manipulate the stone tools that our ancestors used

The ways our bodies and brains change in conjunction with the tools we make have long inspired anxieties that “we” are losing some essential qualities

Yet as we lose certain capacities, we gain new ones.

The nature of human nature is that it changes. It can not, therefore, serve as a stable basis for evaluating the impact of technology

Yet the assumption that it doesn’t change serves a useful purpose. Treating human nature as something static, pure and essential elevates the speaker into a position of power. Claiming to tell us who we are, they tell us how we should be.

Messaging, for instance, is considered the strongest signal. It’s reasonable to assume that you’re closer to somebody you exchange messages with than somebody whose post you once liked.

Harris and his fellow tech humanists also frequently invoke the language of public health. The Center for Humane Technology’s Roger McNamee has gone so far as to call public health “the root of the whole thing”, and Harris has compared using Snapchat to smoking cigarettes

The public-health framing casts the tech humanists in a paternalistic role. Resolving a public health crisis requires public health expertise. It also precludes the possibility of democratic debate. You don’t put the question of how to treat a disease up for a vote – you call a doctor.

They also remain confined to the personal level, aiming to redesign how the individual user interacts with technology rather than tackling the industry’s structural failures. Tech humanism fails to address the root cause of the tech backlash: the fact that a small handful of corporations own our digital lives and strip-mine them for profit.

This is a fundamentally political and collective issue. But by framing the problem in terms of health and humanity, and the solution in terms of design, the tech humanists personalise and depoliticise it.

Far from challenging Silicon Valley, tech humanism offers Silicon Valley a useful way to pacify public concerns without surrendering any of its enormous wealth and power.

these principles could make Facebook even more profitable and powerful, by opening up new business opportunities. That seems to be exactly what Facebook has planned.

reported that total time spent on the platform had dropped by around 5%, or about 50m hours per day. But, Zuckerberg said, this was by design: in particular, it was in response to tweaks to the News Feed that prioritised “meaningful” interactions with “friends” rather than consuming “public content” like video and news. This would ensure that “Facebook isn’t just fun, but also good for people’s well-being”

Zuckerberg said he expected those changes would continue to decrease total time spent – but “the time you do spend on Facebook will be more valuable”. This may describe what users find valuable – but it also refers to what Facebook finds valuable

not all data is created equal. One of the most valuable sources of data to Facebook is used to inform a metric called “coefficient”. This measures the strength of a connection between two users – Zuckerberg once called it “an index for each relationship”

Facebook records every interaction you have with another user – from liking a friend’s post or viewing their profile, to sending them a message. These activities provide Facebook with a sense of how close you are to another person, and different activities are weighted differently.

Holding humanity and technology separate clears the way for a small group of humans to determine the proper alignment between them

Why is coefficient so valuable? Because Facebook uses it to create a Facebook they think you will like: it guides algorithmic decisions about what content you see and the order in which you see it. It also helps improve ad targeting, by showing you ads for things liked by friends with whom you often interact

emphasising time well spent means creating a Facebook that prioritises data-rich personal interactions that Facebook can use to make a more engaging platform.

“time well spent” means Facebook can monetise more efficiently. It can prioritise the intensity of data extraction over its extensiveness. This is a wise business move, disguised as a concession to critics

industrialists had to find ways to make the time of the worker more valuable – to extract more money from each moment rather than adding more moments. They did this by making industrial production more efficient: developing new technologies and techniques that squeezed more value out of the worker and stretched that value further than ever before.

there is another way of thinking about how to live with technology – one that is both truer to the history of our species and useful for building a more democratic future. This tradition does not address “humanity” in the abstract, but as distinct human beings, whose capacities are shaped by the tools they use.

It sees us as hybrids of animal and machine – as “cyborgs”, to quote the biologist and philosopher of science Donna Haraway.

The cyborg way of thinking, by contrast, tells us that our species is essentially technological. We change as we change our tools, and our tools change us. But even though our continuous co-evolution with our machines is inevitable, the way it unfolds is not. Rather, it is determined by who owns and runs those machines. It is a question of power

The various scandals that have stoked the tech backlash all share a single source. Surveillance, fake news and the miserable working conditions in Amazon’s warehouses are profitable. If they were not, they would not exist. They are symptoms of a profound democratic deficit inflicted by a system that prioritises the wealth of the few over the needs and desires of the many.

If being technological is a feature of being human, then the power to shape how we live with technology should be a fundamental human right

The decisions that most affect our technological lives are far too important to be left to Mark Zuckerberg, rich investors or a handful of “humane designers”. They should be made by everyone, together.

Rather than trying to humanise technology, then, we should be trying to democratise it. We should be demanding that society as a whole gets to decide how we live with technology

What does this mean in practice? First, it requires limiting and eroding Silicon Valley’s power.

Antitrust laws and tax policy offer useful ways to claw back the fortunes Big Tech has built on common resources

democratic governments should be making rules about how those firms are allowed to behave – rules that restrict how they can collect and use our personal data, for instance, like the General Data Protection Regulation

This means developing publicly and co-operatively owned alternatives that empower workers, users and citizens to determine how they are run.

we might demand that tech firms pay for the privilege of extracting our data, so that we can collectively benefit from a resource we collectively create.

Language is an essential — perhaps the essential — marker of our species. We learn in and through natural languages; we develop our most fundamental cognitive skills by speaking and hearing languages; and we ultimately assume our identities as human beings and members of communities by exercising those languages

Our profound and impressive ability to create complex tools with which to manipulate our environments is secondary to our ability to conceptualize and communicate about those environments in natural languages.

Natural languages aren’t just more complex versions of the algorithms with which we teach machines to do tasks; they are also the living embodiments of our essence as social animals.

We express our love and our losses, explore beauty, justice and the meaning of our existence, and even come to know ourselves all though natural languages.

we are fundamentally limited in how much we can know about another’s thoughts and feelings, and that this limitation and the desire to transcend it is essential to our humanity

or us humans, communication is about much more than getting information or following instructions; it’s about learning who we are by interacting with others.

Code is too hard to think about. Before trying to understand the attempts themselves, then, it’s worth understanding why this might be: what it is about code that makes it so foreign to the mind, and so unlike anything that came before it.

Technological progress used to change the way the world looked—you could watch the roads getting paved; you could see the skylines rise. Today you can hardly tell when something is remade, because so often it is remade by code.

Software has enabled us to make the most intricate machines that have ever existed. And yet we have hardly noticed, because all of that complexity is packed into tiny silicon chips as millions and millions of lines of cod

The programmer, the renowned Dutch computer scientist Edsger Dijkstra wrote in 1988, “has to be able to think in terms of conceptual hierarchies that are much deeper than a single mind ever needed to face before.” Dijkstra meant this as a warning.

As programmers eagerly poured software into critical systems, they became, more and more, the linchpins of the built world—and Dijkstra thought they had perhaps overestimated themselves.

What made programming so difficult was that it required you to think like a computer.

“The problem is that software engineers don’t understand the problem they’re trying to solve, and don’t care to,” says Leveson, the MIT software-safety expert. The reason is that they’re too wrapped up in getting their code to work.

Though he runs a lab that studies the future of computing, he seems less interested in technology per se than in the minds of the people who use it. Like any good toolmaker, he has a way of looking at the world that is equal parts technical and humane. He graduated top of his class at the California Institute of Technology for electrical engineering,

“The serious problems that have happened with software have to do with requirements, not coding errors.” When you’re writing code that controls a car’s throttle, for instance, what’s important is the rules about when and how and by how much to open it. But these systems have become so complicated that hardly anyone can keep them straight in their head. “There’s 100 million lines of code in cars now,” Leveson says. “You just cannot anticipate all these things.”

a nearly decade-long investigation into claims of so-called unintended acceleration in Toyota cars. Toyota blamed the incidents on poorly designed floor mats, “sticky” pedals, and driver error, but outsiders suspected that faulty software might be responsible

software experts spend 18 months with the Toyota code, picking up where NASA left off. Barr described what they found as “spaghetti code,” programmer lingo for software that has become a tangled mess. Code turns to spaghetti when it accretes over many years, with feature after feature piling on top of, and being woven around

Using the same model as the Camry involved in the accident, Barr’s team demonstrated that there were actually more than 10 million ways for the onboard computer to cause unintended acceleration. They showed that as little as a single bit flip—a one in the computer’s memory becoming a zero or vice versa—could make a car run out of control. The fail-safe code that Toyota had put in place wasn’t enough to stop it

. In all, Toyota recalled more than 9 million cars, and paid nearly $3 billion in settlements and fines related to unintended acceleration.

The problem is that programmers are having a hard time keeping up with their own creations. Since the 1980s, the way programmers work and the tools they use have changed remarkably little.

“Visual Studio is one of the single largest pieces of software in the world,” he said. “It’s over 55 million lines of code. And one of the things that I found out in this study is more than 98 percent of it is completely irrelevant. All this work had been put into this thing, but it missed the fundamental problems that people faced. And the biggest one that I took away from it was that basically people are playing computer inside their head.” Programmers were like chess players trying to play with a blindfold on—so much of their mental energy is spent just trying to picture where the pieces are that there’s hardly any left over to think about the game itself.

The fact that the two of them were thinking about the same problem in the same terms, at the same time, was not a coincidence. They had both just seen the same remarkable talk, given to a group of software-engineering students in a Montreal hotel by a computer researcher named Bret Victor. The talk, which went viral when it was posted online in February 2012, seemed to be making two bold claims. The first was that the way we make software is fundamentally broken. The second was that Victor knew how to fix it.

This is the trouble with making things out of code, as opposed to something physical. “The complexity,” as Leveson puts it, “is invisible to the eye.”

in early 2012, Victor had finally landed upon the principle that seemed to thread through all of his work. (He actually called the talk “Inventing on Principle.”) The principle was this: “Creators need an immediate connection to what they’re creating.” The problem with programming was that it violated the principle. That’s why software systems were so hard to think about, and so rife with bugs: The programmer, staring at a page of text, was abstracted from whatever it was they were actually making.

“Our current conception of what a computer program is,” he said, is “derived straight from Fortran and ALGOL in the late ’50s. Those languages were designed for punch cards.”

WYSIWYG (pronounced “wizzywig”) came along. It stood for “What You See Is What You Get.”

Victor’s point was that programming itself should be like that. For him, the idea that people were doing important work, like designing adaptive cruise-control systems or trying to understand cancer, by staring at a text editor, was appalling.

With the right interface, it was almost as if you weren’t working with code at all; you were manipulating the game’s behavior directly.

When the audience first saw this in action, they literally gasped. They knew they weren’t looking at a kid’s game, but rather the future of their industry. Most software involved behavior that unfolded, in complex ways, over time, and Victor had shown that if you were imaginative enough, you could develop ways to see that behavior and change it, as if playing with it in your hands. One programmer who saw the talk wrote later: “Suddenly all of my tools feel obsolete.”

hen John Resig saw the “Inventing on Principle” talk, he scrapped his plans for the Khan Academy programming curriculum. He wanted the site’s programming exercises to work just like Victor’s demos. On the left-hand side you’d have the code, and on the right, the running program: a picture or game or simulation. If you changed the code, it’d instantly change the picture. “In an environment that is truly responsive,” Resig wrote about the approach, “you can completely change the model of how a student learns ... [They] can now immediately see the result and intuit how underlying systems inherently work without ever following an explicit explanation.” Khan Academy has become perhaps the largest computer-programming class in the world, with a million students, on average, actively using the program each month.

The ideas spread. The notion of liveness, of being able to see data flowing through your program instantly, made its way into flagship programming tools offered by Google and Apple. The default language for making new iPhone and Mac apps, called Swift, was developed by Apple from the ground up to support an environment, called Playgrounds, that was directly inspired by Light Table.

“Typically the main problem with software coding—and I’m a coder myself,” Bantegnie says, “is not the skills of the coders. The people know how to code. The problem is what to code. Because most of the requirements are kind of natural language, ambiguous, and a requirement is never extremely precise, it’s often understood differently by the guy who’s supposed to code.”

In a pair of later talks, “Stop Drawing Dead Fish” and “Drawing Dynamic Visualizations,” Victor went one further. He demoed two programs he’d built—the first for animators, the second for scientists trying to visualize their data—each of which took a process that used to involve writing lots of custom code and reduced it to playing around in a WYSIWYG interface.

Victor suggested that the same trick could be pulled for nearly every problem where code was being written today. “I’m not sure that programming has to exist at all,” he told me. “Or at least software developers.” In his mind, a software developer’s proper role was to create tools that removed the need for software developers. Only then would people with the most urgent computational problems be able to grasp those problems directly, without the intermediate muck of code.

Victor implored professional software developers to stop pouring their talent into tools for building apps like Snapchat and Uber. “The inconveniences of daily life are not the significant problems,” he wrote. Instead, they should focus on scientists and engineers—as he put it to me, “these people that are doing work that actually matters, and critically matters, and using really, really bad tools.”

Bantegnie’s company is one of the pioneers in the industrial use of model-based design, in which you no longer write code directly. Instead, you create a kind of flowchart that describes the rules your program should follow (the “model”), and the computer generates code for you based on those rules

In a model-based design tool, you’d represent this rule with a small diagram, as though drawing the logic out on a whiteboard, made of boxes that represent different states—like “door open,” “moving,” and “door closed”—and lines that define how you can get from one state to the other. The diagrams make the system’s rules obvious: Just by looking, you can see that the only way to get the elevator moving is to close the door, or that the only way to get the door open is to stop.

. In traditional programming, your task is to take complex rules and translate them into code; most of your energy is spent doing the translating, rather than thinking about the rules themselves. In the model-based approach, all you have is the rules. So that’s what you spend your time thinking about. It’s a way of focusing less on the machine and more on the problem you’re trying to get it to solve.

“Everyone thought I was interested in programming environments,” he said. Really he was interested in how people see and understand systems—as he puts it, in the “visual representation of dynamic behavior.” Although code had increasingly become the tool of choice for creating dynamic behavior, it remained one of the worst tools for understanding it. The point of “Inventing on Principle” was to show that you could mitigate that problem by making the connection between a system’s behavior and its code immediate.

On this view, software becomes unruly because the media for describing what software should do—conversations, prose descriptions, drawings on a sheet of paper—are too different from the media describing what software does do, namely, code itself.

for this approach to succeed, much of the work has to be done well before the project even begins. Someone first has to build a tool for developing models that are natural for people—that feel just like the notes and drawings they’d make on their own—while still being unambiguous enough for a computer to understand. They have to make a program that turns these models into real code. And finally they have to prove that the generated code will always do what it’s supposed to.

tice brings order and accountability to large codebases. But, Shivappa says, “it’s a very labor-intensive process.” He estimates that before they used model-based design, on a two-year-long project only two to three months was spent writing code—the rest was spent working on the documentation.

uch of the benefit of the model-based approach comes from being able to add requirements on the fly while still ensuring that existing ones are met; with every change, the computer can verify that your program still works. You’re free to tweak your blueprint without fear of introducing new bugs. Your code is, in FAA parlance, “correct by construction.”

“people are not so easily transitioning to model-based software development: They perceive it as another opportunity to lose control, even more than they have already.”

The bias against model-based design, sometimes known as model-driven engineering, or MDE, is in fact so ingrained that according to a recent paper, “Some even argue that there is a stronger need to investigate people’s perception of MDE than to research new MDE technologies.”

“Human intuition is poor at estimating the true probability of supposedly ‘extremely rare’ combinations of events in systems operating at a scale of millions of requests per second,” he wrote in a paper. “That human fallibility means that some of the more subtle, dangerous bugs turn out to be errors in design; the code faithfully implements the intended design, but the design fails to correctly handle a particular ‘rare’ scenario.”

Newcombe was convinced that the algorithms behind truly critical systems—systems storing a significant portion of the web’s data, for instance—ought to be not just good, but perfect. A single subtle bug could be catastrophic. But he knew how hard bugs were to find, especially as an algorithm grew more complex. You could do all the testing you wanted and you’d never find them all.

An algorithm written in TLA+ could in principle be proven correct. In practice, it allowed you to create a realistic model of your problem and test it not just thoroughly, but exhaustively. This was exactly what he’d been looking for: a language for writing perfect algorithms.

TLA+, which stands for “Temporal Logic of Actions,” is similar in spirit to model-based design: It’s a language for writing down the requirements—TLA+ calls them “specifications”—of computer programs. These specifications can then be completely verified by a computer. That is, before you write any code, you write a concise outline of your program’s logic, along with the constraints you need it to satisfy

Programmers are drawn to the nitty-gritty of coding because code is what makes programs go; spending time on anything else can seem like a distraction. And there is a patient joy, a meditative kind of satisfaction, to be had from puzzling out the micro-mechanics of code. But code, Lamport argues, was never meant to be a medium for thought. “It really does constrain your ability to think when you’re thinking in terms of a programming language,”

Code makes you miss the forest for the trees: It draws your attention to the working of individual pieces, rather than to the bigger picture of how your program fits together, or what it’s supposed to do—and whether it actually does what you think. This is why Lamport created TLA+. As with model-based design, TLA+ draws your focus to the high-level structure of a system, its essential logic, rather than to the code that implements it.

But TLA+ occupies just a small, far corner of the mainstream, if it can be said to take up any space there at all. Even to a seasoned engineer like Newcombe, the language read at first as bizarre and esoteric—a zoo of symbols.

this is a failure of education. Though programming was born in mathematics, it has since largely been divorced from it. Most programmers aren’t very fluent in the kind of math—logic and set theory, mostly—that you need to work with TLA+. “Very few programmers—and including very few teachers of programming—understand the very basic concepts and how they’re applied in practice. And they seem to think that all they need is code,” Lamport says. “The idea that there’s some higher level than the code in which you need to be able to think precisely, and that mathematics actually allows you to think precisely about it, is just completely foreign. Because they never learned it.”

“In the 15th century,” he said, “people used to build cathedrals without knowing calculus, and nowadays I don’t think you’d allow anyone to build a cathedral without knowing calculus. And I would hope that after some suitably long period of time, people won’t be allowed to write programs if they don’t understand these simple things.”

Programmers, as a species, are relentlessly pragmatic. Tools like TLA+ reek of the ivory tower. When programmers encounter “formal methods” (so called because they involve mathematical, “formally” precise descriptions of programs), their deep-seated instinct is to recoil.

Formal methods had an image problem. And the way to fix it wasn’t to implore programmers to change—it was to change yourself. Newcombe realized that to bring tools like TLA+ to the programming mainstream, you had to start speaking their language.

he presented TLA+ as a new kind of “pseudocode,” a stepping-stone to real code that allowed you to exhaustively test your algorithms—and that got you thinking precisely early on in the design process. “Engineers think in terms of debugging rather than ‘verification,’” he wrote, so he titled his internal talk on the subject to fellow Amazon engineers “Debugging Designs.” Rather than bemoan the fact that programmers see the world in code, Newcombe embraced it. He knew he’d lose them otherwise. “I’ve had a bunch of people say, ‘Now I get it,’” Newcombe says.

In the world of the self-driving car, software can’t be an afterthought. It can’t be built like today’s airline-reservation systems or 911 systems or stock-trading systems. Code will be put in charge of hundreds of millions of lives on the road and it has to work. That is no small task.

By removing the tangible product from the center of commerce, surveillance capitalism upsets the equilibrium. Whenever we use free apps and online services, it’s often said, we become the products, our attention harvested and sold to advertisers

this truism gets it wrong. Surveillance capitalism’s real products, vaporous but immensely valuable, are predictions about our future behavior — what we’ll look at, where we’ll go, what we’ll buy, what opinions we’ll hold — that internet companies derive from our personal data and sell to businesses, political operatives, and other bidders.

Unlike financial derivatives, which they in some ways resemble, these new data derivatives draw their value, parasite-like, from human experience.To the Googles and Facebooks of the world, we are neither the customer nor the product. We are the source of what Silicon Valley technologists call “data exhaust” — the informational byproducts of online activity that become the inputs to prediction algorithms

Another 2015 study, appearing in the Journal of Computer-Mediated Communication, showed that when people hear their phone ring but are unable to answer it, their blood pressure spikes, their pulse quickens, and their problem-solving skills decline.

The smartphone has become a repository of the self, recording and dispensing the words, sounds and images that define what we think, what we experience and who we are. In a 2015 Gallup survey, more than half of iPhone owners said that they couldn’t imagine life without the device.

So what happens to our minds when we allow a single tool such dominion over our perception and cognition?

Not only do our phones shape our thoughts in deep and complicated ways, but the effects persist even when we aren’t using the devices. As the brain grows dependent on the technology, the research suggests, the intellect weakens.

he has seen mounting evidence that using a smartphone, or even hearing one ring or vibrate, produces a welter of distractions that makes it harder to concentrate on a difficult problem or job. The division of attention impedes reasoning and performance.

internet companies operate in what Zuboff terms “extreme structural independence from people.” When databases displace goods as the engine of the economy, our own interests, as consumers but also as citizens, cease to be part of the negotiation. We are no longer one of the forces guiding the market’s invisible hand. We are the objects of surveillance and control.

Social skills and relationships seem to suffer as well.

In both tests, the subjects whose phones were in view posted the worst scores, while those who left their phones in a different room did the best. The students who kept their phones in their pockets or bags came out in the middle. As the phone’s proximity increased, brainpower decreased.

In subsequent interviews, nearly all the participants said that their phones hadn’t been a distraction—that they hadn’t even thought about the devices during the experiment. They remained oblivious even as the phones disrupted their focus and thinking.

The researchers recruited 520 undergraduates at UCSD and gave them two standard tests of intellectual acuity. One test gauged “available working-memory capacity,” a measure of how fully a person’s mind can focus on a particular task. The second assessed “fluid intelligence,” a person’s ability to interpret and solve an unfamiliar problem. The only variable in the experiment was the location of the subjects’ smartphones. Some of the students were asked to place their phones in front of them on their desks; others were told to stow their phones in their pockets or handbags; still others were required to leave their phones in a different room.

the “integration of smartphones into daily life” appears to cause a “brain drain” that can diminish such vital mental skills as “learning, logical reasoning, abstract thought, problem solving, and creativity.”

 Smartphones have become so entangled with our existence that, even when we’re not peering or pawing at them, they tug at our attention, diverting precious cognitive resources. Just suppressing the desire to check our phone, which we do routinely and subconsciously throughout the day, can debilitate our thinking.

They found that students who didn’t bring their phones to the classroom scored a full letter-grade higher on a test of the material presented than those who brought their phones. It didn’t matter whether the students who had their phones used them or not: All of them scored equally poorly.

A study of nearly a hundred secondary schools in the U.K., published last year in the journal Labour Economics, found that when schools ban smartphones, students’ examination scores go up substantially, with the weakest students benefiting the most.

Data, the novelist and critic Cynthia Ozick once wrote, is “memory without history.” Her observation points to the problem with allowing smartphones to commandeer our brains

Because smartphones serve as constant reminders of all the friends we could be chatting with electronically, they pull at our minds when we’re talking with people in person, leaving our conversations shallower and less satisfying.

In a 2013 study conducted at the University of Essex in England, 142 participants were divided into pairs and asked to converse in private for ten minutes. Half talked with a phone in the room, half without a phone present. The subjects were then given tests of affinity, trust and empathy. “The mere presence of mobile phones,” the researchers reported in the Journal of Social and Personal Relationships, “inhibited the development of interpersonal closeness and trust” and diminished “the extent to which individuals felt empathy and understanding from their partners.”

The evidence that our phones can get inside our heads so forcefully is unsettling. It suggests that our thoughts and feelings, far from being sequestered in our skulls, can be skewed by external forces we’re not even aware o

 Scientists have long known that the brain is a monitoring system as well as a thinking system. Its attention is drawn toward any object that is new, intriguing or otherwise striking — that has, in the psychological jargon, “salience.”

even in the history of captivating media, the smartphone stands out. It is an attention magnet unlike any our minds have had to grapple with before. Because the phone is packed with so many forms of information and so many useful and entertaining functions, it acts as what Dr. Ward calls a “supernormal stimulus,” one that can “hijack” attention whenever it is part of our surroundings — and it is always part of our surroundings.

Imagine combining a mailbox, a newspaper, a TV, a radio, a photo album, a public library and a boisterous party attended by everyone you know, and then compressing them all into a single, small, radiant object. That is what a smartphone represents to us. No wonder we can’t take our minds off it.

The irony of the smartphone is that the qualities that make it so appealing to us — its constant connection to the net, its multiplicity of apps, its responsiveness, its portability — are the very ones that give it such sway over our minds.

Phone makers like Apple and Samsung and app writers like Facebook, Google and Snap design their products to consume as much of our attention as possible during every one of our waking hours

Social media apps were designed to exploit “a vulnerability in human psychology,” former Facebook president Sean Parker said in a recent interview. “[We] understood this consciously. And we did it anyway.”

A quarter-century ago, when we first started going online, we took it on faith that the web would make us smarter: More information would breed sharper thinking. We now know it’s not that simple.

As strange as it might seem, people’s knowledge and understanding may actually dwindle as gadgets grant them easier access to online data stores

In a seminal 2011 study published in Science, a team of researchers — led by the Columbia University psychologist Betsy Sparrow and including the late Harvard memory expert Daniel Wegner — had a group of volunteers read forty brief, factual statements (such as “The space shuttle Columbia disintegrated during re-entry over Texas in Feb. 2003”) and then type the statements into a computer. Half the people were told that the machine would save what they typed; half were told that the statements would be erased.

Afterward, the researchers asked the subjects to write down as many of the statements as they could remember. Those who believed that the facts had been recorded in the computer demonstrated much weaker recall than those who assumed the facts wouldn’t be stored. Anticipating that information would be readily available in digital form seemed to reduce the mental effort that people made to remember it

The researchers dubbed this phenomenon the “Google effect” and noted its broad implications: “Because search engines are continually available to us, we may often be in a state of not feeling we need to encode the information internally. When we need it, we will look it up.”

as the pioneering psychologist and philosopher William James said in an 1892 lecture, “the art of remembering is the art of thinking.”

Only by encoding information in our biological memory can we weave the rich intellectual associations that form the essence of personal knowledge and give rise to critical and conceptual thinking. No matter how much information swirls around us, the less well-stocked our memory, the less we have to think with.

As Dr. Wegner and Dr. Ward explained in a 2013 Scientific American article, when people call up information through their devices, they often end up suffering from delusions of intelligence. They feel as though “their own mental capacities” had generated the information, not their devices. “The advent of the ‘information age’ seems to have created a generation of people who feel they know more than ever before,” the scholars concluded, even though “they may know ever less about the world around them.”

That insight sheds light on society’s current gullibility crisis, in which people are all too quick to credit lies and half-truths spread through social media. If your phone has sapped your powers of discernment, you’ll believe anything it tells you.

A second experiment conducted by the researchers produced similar results, while also revealing that the more heavily students relied on their phones in their everyday lives, the greater the cognitive penalty they suffered.

When we constrict our capacity for reasoning and recall or transfer those skills to a gadget, we sacrifice our ability to turn information into knowledge. We get the data but lose the meaning

We need to give our minds more room to think. And that means putting some distance between ourselves and our phones.

Google’s once-patient investors grew restive, demanding that the founders figure out a way to make money, preferably lots of it.

nder pressure, Page and Brin authorized the launch of an auction system for selling advertisements tied to search queries. The system was designed so that the company would get paid by an advertiser only when a user clicked on an ad. This feature gave Google a huge financial incentive to make accurate predictions about how users would respond to ads and other online content. Even tiny increases in click rates would bring big gains in income. And so the company began deploying its stores of behavioral data not for the benefit of users but to aid advertisers — and to juice its own profits. Surveillance capitalism had arrived.

Google’s business now hinged on what Zuboff calls “the extraction imperative.” To improve its predictions, it had to mine as much information as possible from web users. It aggressively expanded its online services to widen the scope of its surveillance.

Through Gmail, it secured access to the contents of people’s emails and address books. Through Google Maps, it gained a bead on people’s whereabouts and movements. Through Google Calendar, it learned what people were doing at different moments during the day and whom they were doing it with. Through Google News, it got a readout of people’s interests and political leanings. Through Google Shopping, it opened a window onto people’s wish lists,

The company gave all these services away for free to ensure they’d be used by as many people as possible. It knew the money lay in the data.

the organization grew insular and secretive. Seeking to keep the true nature of its work from the public, it adopted what its CEO at the time, Eric Schmidt, called a “hiding strategy” — a kind of corporate omerta backed up by stringent nondisclosure agreements.

Page and Brin further shielded themselves from outside oversight by establishing a stock structure that guaranteed their power could never be challenged, neither by investors nor by directors.

What’s most remarkable about the birth of surveillance capitalism is the speed and audacity with which Google overturned social conventions and norms about data and privacy. Without permission, without compensation, and with little in the way of resistance, the company seized and declared ownership over everyone’s information