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The distinction between the beautiful and the sublime is the distinction between the intimate and the transcendent. This sort of distinction doesn’t just happen in aesthetics, but in life in general. We have big and little loves.

Big love involves thinking in sweeping historical terms. But today the sense that America is pursuing a noble mission in the world has been humbled by failures and passivity. The country feels more divided than unified around common purpose

Big love involves politics, and thus compromise, competition and messiness. Americans today are less likely to discern the noble within the grittiness of reality. The very words that the founders used to describe their Big love for their country sound archaic: glory, magnanimity, sacred honor and greatness.

There is, in sum, less animating desire in the country at the moment, and therefore less energy and daring. The share of Americans moving across state lines in search of opportunity has fallen by more than half since the 1970s. The rate of new business creation is down. Productivity is falling for the first time in three decades. Economic growth is anemic. There’s a spiritual and cultural element behind these trends

Republicans are the party of Big Energy and Big Food: they dominate contributions from extractive industries and agribusiness. And they are, in particular, the party of Big Pizza.

pizza partisanship tells you a lot about what is happening to American politics as a whole.

Why should pizza, of all things, be a divisive issue

The immediate answer is that it has been caught up in the nutrition wars

the pizza sector has chosen instead to take a stand for the right to add extra cheese.

The rhetoric of this fight is familiar. The pizza lobby portrays itself as the defender of personal choice and personal responsibility. It’s up to the consumer, so the argument goes, to decide what he or she wants to eat, and we don’t need a nanny state telling us what to do.

it doesn’t hold up too well once you look at what’s actually at stake in the pizza disputes.

Nobody is proposing a ban on pizza, or indeed any limitation on what informed adults should be allowed to eat. Instead, the fights involve things like labeling requirements — giving consumers the information to make informed choices — and the nutritional content of school lunches, that is, food decisions that aren’t made by responsible adults but are instead made on behalf of children.

Nutrition, where increased choice can be a bad thing, because it all too often leads to bad choices despite the best of intentions, is one of those areas — like smoking — where there’s a lot to be said for a nanny state.

diet isn’t purely a personal choice, either; obesity imposes large costs on the economy as a whole.

But you shouldn’t expect such arguments to gain much traction

For one thing, free-market fundamentalists don’t want to hear about qualifications to their doctrine

Also, with big corporations involved, the Upton Sinclair principle applies: It’s difficult to get a man to understand something when his salary depends on his not understanding it

nutritional partisanship taps into deeper cultural issues.

At one level, there is a clear correlation between lifestyles and partisan orientation: heavier states tend to vote Republican, and the G.O.P. lean is especially pronounced in what the Centers for Disease Control and Prevention call the “diabetes belt” of counties, mostly in the South, that suffer most from that particular health problem

At a still deeper level, health experts may say that we need to change how we eat, pointing to scientific evidence, but the Republican base doesn’t much like experts, science, or evidence. Debates about nutrition policy bring out a kind of venomous anger — much of it now directed at Michelle Obama, who has been championing school lunch reforms — that is all too familiar if you’ve been following the debate over climate change.

It is, instead, a case study in the toxic mix of big money, blind ideology, and popular prejudices that is making America ever less governable.

there’s that exquisite verse, one of the most beautiful in the Bible, the one that says if God cares deeply about sparrows, don’t you think He cares about you? One is so accustomed to dwelling on the second, human, half of the equation, the comforting part, but when you put your hand over that and consider only the first, it’s a little startling: God cares deeply about the sparrows. Not just that, He cares about them individually. “Are not five sparrows sold for two pennies?” Jesus says. “Yet not one of them is forgotten in God’s sight.”

The modern conversation on animal consciousness proceeds, with the rest of the Enlightenment, from the mind of René Descartes, whose take on animals was vividly (and approvingly) paraphrased by the French philosopher Nicolas Malebranche: they “eat without pleasure, cry without pain, grow without knowing it; they desire nothing, fear nothing, know nothing.” Descartes’ term for them was automata

In On the Origin of Species, Charles Darwin made the intriguing claim that among the naturalists he knew it was consistently the case that the better a researcher got to know a certain species, the more each individual animal’s actions appeared attributable to “reason and the less to unlearnt instinct.” The more you knew, the more you suspected that they were rational. That marks an important pivot, that thought, insofar as it took place in the mind of someone devoted to extremely close and meticulous study of living animals, a mind that had trained itself not to sentimentalize.

The sheer number and variety of experiments carried out in the twentieth century—and with, if anything, a renewed intensity in the twenty-first—exceeds summary. Reasoning, language, neurology, the science of emotions—every chamber where “consciousness” is thought to hide has been probed. Birds and chimps and dolphins have been made to look at themselves in mirrors—to observe whether, on the basis of what they see, they groom or preen (a measure, if somewhat arbitrary, of self-awareness). Dolphins have been found to grieve. Primates have learned symbolic or sign languages and then been interrogated with them. Their answers show thinking but have proved stubbornly open to interpretation on the issue of “consciousness,” with critics warning, as always, about the dangers of anthropomorphism, animal-rights bias, etc.

If we put aside the self-awareness standard—and really, how arbitrary and arrogant is that, to take the attribute of consciousness we happen to possess over all creatures and set it atop the hierarchy, proclaiming it the very definition of consciousness (Georg Christoph Lichtenberg wrote something wise in his notebooks, to the effect of: only a man can draw a self-portrait, but only a man wants to)—it becomes possible to say at least the following: the overwhelming tendency of all this scientific work, of its results, has been toward more consciousness. More species having it, and species having more of it than assumed.

The animal kingdom is symphonic with mental activity, and of its millions of wavelengths, we’re born able to understand the minutest sliver. The least we can do is have a proper respect for our ignorance.

The philosopher Thomas Nagel wrote an essay in 1974 titled, “What Is It Like To Be a Bat?”, in which he put forward perhaps the least overweening, most useful definition of “animal consciousness” ever written, one that channels Spinoza’s phrase about “that nature belonging to him wherein he has his being.” Animal consciousness occurs, Nagel wrote, when “there is something that it is to be that organism—something it is like for the organism.” The strangeness of his syntax carries the genuine texture of the problem. We’ll probably never be able to step far enough outside of our species-reality to say much about what is going on with them, beyond saying how like or unlike us they are. Many things are conscious on the earth, and we are one, and our consciousness feels like this; one of the things it causes us to do is doubt the existence of the consciousness of the other millions of species. But it also allows us to imagine a time when we might stop doing that.

as has happened before with other forms of property, the most politically influential owners of the new property are doing their utmost to increase their profits by creating monopolies

The most valuable intellectual properties are platforms so widely used that everyone else has to use them, too. Think of standard operating systems like Microsoft’s Windows or Google’s Android; Google’s search engine; Amazon’s shopping system; and Facebook’s communication network

Despite an explosion in the number of websites over the last decade, page views are becoming more concentrated. While in 2001, the top 10 websites accounted for 31 percent of all page views in America, by 2010 the top 10 accounted for 75 percent

Amazon is now the first stop for almost a third of all American consumers seeking to buy anything

Google and Facebook are now the first stops for many Americans seeking news — while Internet traffic to much of the nation’s newspapers, network television and other news gathering agencies has fallen well below 50 percent of all traffic.

almost all of the profits go to the platforms’ owners, who have all of the bargaining power

The rate at which new businesses have formed in the United States has slowed markedly since the late 1970s. Big Tech’s sweeping patents, standard platforms, fleets of lawyers to litigate against potential rivals and armies of lobbyists have created formidable barriers to new entrants

The law gives 20 years of patent protection to inventions that are “new and useful,” as decided by the Patent and Trademark Office. But the winners are big enough to game the system. They make small improvements warranting new patents, effectively making their intellectual property semipermanent.

They also lay claim to whole terrains of potential innovation including ideas barely on drawing boards and flood the system with so many applications that lone inventors have to wait years.

Big Tech has been almost immune to serious antitrust scrutiny, even though the largest tech companies have more market power than ever. Maybe that’s because they’ve accumulated so much political power.

Economic and political power can’t be separated because dominant corporations gain political influence over how markets are maintained and enforced, which enlarges their economic power further. One of the original goals of antitrust law was to prevent this.

We are now in a new gilded age similar to the first Gilded Age, when the nation’s antitrust laws were enacted. As then, those with great power and resources are making the “free market” function on their behalf. Big Tech — along with the drug, insurance, agriculture and financial giants — dominates both our economy and our politics.

The real question is how government organizes the market, and who has the most influence over its decisions

Yet as long as we remain obsessed by the debate over the relative merits of the “free market” and “government,” we have little hope of seeing what’s occurring and taking the action that’s needed to make our economy work for the many, not the few.

in 2001, the top 10 websites accounted for 31 percent of all U.S. page views, but, by 2010, they accounted for 75 percent of them.

As a result, our A.I. future is likely to be ruled by an oligarchy of two or three large, general-purpose cloud-based commercial intelligences.”

Advances in artificial intelligence will accelerate this centralizing trend. That’s because A.I. companies will be able to reap the rewards of network effects. The bigger their network and the more data they collect, the more effective and attractive they become.

The Internet has created a long tail, but almost all the revenue and power is among the small elite at the head.

engineers at a few gigantic companies will have vast-though-hidden power to shape how data are collected and framed, to harvest huge amounts of information, to build the frameworks through which the rest of us make decisions and to steer our choices. If you think this power will be used for entirely benign ends, then you have not read enough history.

The second implication is philosophical. A.I. will redefine what it means to be human. Our identity as humans is shaped by what machines and other animals can’t do

On the other hand, machines cannot beat us at the things we do without conscious thinking: developing tastes and affections, mimicking each other and building emotional attachments, experiencing imaginative breakthroughs, forming moral sentiments.

For the last few centuries, reason was seen as the ultimate human faculty. But now machines are better at many of the tasks we associate with thinking — like playing chess, winning at Jeopardy, and doing math.

In the age of smart machines, we’re not human because we have big brains. We’re human because we have social skills, emotional capacities and moral intuitions.

I could paint two divergent A.I. futures, one deeply humanistic, and one soullessly utilitarian.

In the humanistic one, machines liberate us from mental drudgery so we can focus on higher and happier things. In this future, differences in innate I.Q. are less important. Everybody has Google on their phones so having a great memory or the ability to calculate with big numbers doesn’t help as much.

In this future, there is increasing emphasis on personal and moral faculties: being likable, industrious, trustworthy and affectionate. People are evaluated more on these traits, which supplement machine thinking, and not the rote ones that duplicate it

In the cold, utilitarian future, on the other hand, people become less idiosyncratic. If the choice architecture behind many decisions is based on big data from vast crowds, everybody follows the prompts and chooses to be like each other. The machine prompts us to consume what is popular, the things that are easy and mentally undemanding.

In the current issue of Wired, the technology writer Kevin Kelly says that we had all better get used to this level of predictive prowess. Kelly argues that the age of artificial intelligence is finally at hand.

“So money equals speech?” I asked. No, he said. “But nobody speaks very effectively without money. If you limit how much you spend on speech, you are also limiting speech.”

Big contributors want something for their money. At its most benign, they want access, the ability to have their side heard whenever there is the possibility that legislation might affect their industry. Far less benignly, they want more — they want to know that their bidding will be done.

It can be subtle, this influence. “Maybe it’s the amendment that does not get introduced in committee because the congressman knows that it is not in sync with the desires of his money patrons,”

it can be not so subtle, too. “On any given Wednesday night in Washington,” says Nick Penniman, the executive director of Issue One, which is dedicated to reducing the influence of money in politics, “you’ll have a member of, say, the finance committee, standing in the board room of a lobbyist’s office, surrounded by bank lobbyists. At some point, someone will hand a staffer an envelope with the checks in it, and the congressman will have raised $100,000 in 45 minutes. And they know exactly who was responsible for putting it together, and whose phone calls therefore need to be returned.”

Penniman makes a distinction between “ideological givers” — donors like the Koch brothers, motivated by the chance to get like-minded people elected — and “transactional givers,” those who donate because they expect something concrete in return. “These are folks who give just as generously to both sides of the aisle.”

“Big money wins regardless of which party wins the election.”

There are two other reasons big money is corrosive to our politics.

One is that the need to raise money has become close to all-consuming.

“It’s a never-ending hustle. You get elected to this august body to fix problems, and for the privilege, you find yourself on the phone in a cubicle, dialing for dollars.”

the constant need to raise money means that “you don’t have the time for the kind of personal relationships that so many of us built up over time.” When people don’t know each other, it is a lot easier to think the worst of them. Polarization is the result.

Finally, there is the effect of big money on the rest of us. The public, Sarbanes believes, knows full well the insidious influence of money in politics. “The rational voter will say to himself, why should I bother voting if the person I’m voting for is a captive of special interests,

how does Ira Glasser react to these tales of corruption? He doesn’t deny them. “Of course there is corruption,” he says. “Of course there is undue influence of money.” But he doesn’t believe that those problems are as great as they are made out to be, or that they trump his First Amendment concerns. “The question is whether the remedy does more harm than good and violates the constitution,”

One common strategy for thinking about this is to suggest that what we used to call the whole universe is just a small part of everything there is, and that we live in a kind of bubble universe, a small region of something much larger

Newton realized there had to be some force holding the moon in its orbit around the earth, to keep it from wandering off, and he knew also there was a force that was pulling the apple down to the earth. And so what suddenly struck him was that those could be one and the same thing, the same force

That was a physical discovery, a physical discovery of momentous importance, as important as anything you could ever imagine because it knit together the terrestrial realm and the celestial realm into one common physical picture. It was also a philosophical discovery in the sense that philosophy is interested in the fundamental natures of things.

There are other ideas, for instance that maybe there might be special sorts of laws, or special sorts of explanatory principles, that would apply uniquely to the initial state of the universe.

The basic philosophical question, going back to Plato, is "What is x?" What is virtue? What is justice? What is matter? What is time? You can ask that about dark energy - what is it? And it's a perfectly good question.

right now there are just way too many freely adjustable parameters in physics. Everybody agrees about that. There seem to be many things we call constants of nature that you could imagine setting at different values, and most physicists think there shouldn't be that many, that many of them are related to one another. Physicists think that at the end of the day there should be one complete equation to describe all physics, because any two physical systems interact and physics has to tell them what to do. And physicists generally like to have only a few constants, or parameters of nature. This is what Einstein meant when he famously said he wanted to understand what kind of choices God had --using his metaphor-- how free his choices were in creating the universe, which is just asking how many freely adjustable parameters there are. Physicists tend to prefer theories that reduce that number

You have others saying that time is just an illusion, that there isn't really a direction of time, and so forth. I myself think that all of the reasons that lead people to say things like that have very little merit, and that people have just been misled, largely by mistaking the mathematics they use to describe reality for reality itself. If you think that mathematical objects are not in time, and mathematical objects don't change -- which is perfectly true -- and then you're always using mathematical objects to describe the world, you could easily fall into the idea that the world itself doesn't change, because your representations of it don't.

physicists for almost a hundred years have been dissuaded from trying to think about fundamental questions. I think most physicists would quite rightly say "I don't have the tools to answer a question like 'what is time?' - I have the tools to solve a differential equation." The asking of fundamental physical questions is just not part of the training of a physicist anymore.

The question remains as to how often, after life evolves, you'll have intelligent life capable of making technology. What people haven't seemed to notice is that on earth, of all the billions of species that have evolved, only one has developed intelligence to the level of producing technology. Which means that kind of intelligence is really not very useful. It's not actually, in the general case, of much evolutionary value. We tend to think, because we love to think of ourselves, human beings, as the top of the evolutionary ladder, that the intelligence we have, that makes us human beings, is the thing that all of evolution is striving toward. But what we know is that that's not true. Obviously it doesn't matter that much if you're a beetle, that you be really smart. If it were, evolution would have produced much more intelligent beetles. We have no empirical data to suggest that there's a high probability that evolution on another planet would lead to technological intelligence.

A major part of managing Big Data projects, he says, is asking the right questions: How do you define the problem? What data do you need? Where does it come from? What are the assumptions behind the model that the data is fed into? How is the model different from reality?

Society might be well served if the model makers pondered the ethical dimensions of their work as well as studying the math, according to Rachel Schutt, a senior statistician at Google Research. “Models do not just predict, but they can make things happen,” says Ms. Schutt, who taught a data science course this year at Columbia. “That’s not discussed generally in our field.”

the increasing use of software that microscopically tracks and monitors online behavior has raised privacy worries. Will Big Data usher in a digital surveillance state, mainly serving corporate interests?

my bigger concern is that the algorithms that are shaping my digital world are too simple-minded, rather than too smart. That was a theme of a book by Eli Pariser, titled “The Filter Bubble: What the Internet Is Hiding From You.”

Some experts displayed a top-down style of reasoning: politics as a deductive art. They started with a big-idea premise about human nature, society, or economics and applied it to the specifics of the case. They tended to reach more confident conclusions about the future. And the positions they reached were easier to classify ideologically: that is the Keynesian prediction and that is the free-market fundamentalist prediction and that is the worst-case environmentalist prediction and that is the best case technology-driven growth prediction etc. Other experts displayed a bottom-up style of reasoning: politics as a much messier inductive art. They reached less confident conclusions and they are more likely to draw on a seemingly contradictory mix of ideas in reaching those conclusions (sometimes from the left, sometimes from the right). We called the big-idea experts “hedgehogs” (they know one big thing) and the more eclectic experts “foxes” (they know many, not so big things).

The most consistent predictor of consistently more accurate forecasts was “style of reasoning”: experts with the more eclectic, self-critical, and modest cognitive styles tended to outperform the big-idea people (foxes tended to outperform hedgehogs).

Lehrer: Can non-experts do anything to encourage a more effective punditocracy?

Tetlock: Yes, non-experts can encourage more accountability in the punditocracy. Pundits are remarkably skillful at appearing to go out on a limb in their claims about the future, without actually going out on one. For instance, they often “predict” continued instability and turmoil in the Middle East (predicting the present) but they virtually never get around to telling you exactly what would have to happen to disconfirm their expectations. They are essentially impossible to pin down. If pundits felt that their public credibility hinged on participating in level playing field forecasting exercises in which they must pit their wits against an extremely difficult-to-predict world, I suspect they would be learn, quite quickly, to be more flexible and foxlike in their policy pronouncements.

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The hope is that the facilities, and perhaps more importantly the close interconnections between outstanding scientists in different fields, that it provides, will lead to it being more than the sum of its parts.

Some science directly addresses so-called “big questions”. How did life begin? What is everything made of? How did the universe begin? Often these big questions are posed within a specific theoretical framework; the Higgs boson is an example of how a good theory can condense a set of very big questions - essentially “What is mass?”

big projects are inevitably political to some extent, if only because of the fondness leaders have for making grand (or “grandiose”, as Amos would have it) announcements. Many big projects are international, which can bring in other elements, and requires decision-making frameworks that, while imperfect, do exist even if not all scientists are fully aware of them.

Last words such as these are only found in 14% of cases. The authors began to notice differences between note leavers and non-leavers in their research, as well as people who attempt suicide and those who complete the act.

Many notes were addressed to one person. Others were to no one in particular.

Nowadays, being a white male is the single biggest risk factor. Why is that? According to Case and Deaton, drastic changes in the labor market is the most significant factor.

“Hegemonic masculinity,” or a perception that heightened masculinity must be portrayed at all times, a goal that no male can live up to.

Another 23% of note writers ended it all due to unrequited love or love lost. 22% said they themselves created the problem which led to their decision.

Meyer and colleagues also propose a national prevention plan, to foster a sense of community and social support.

If you feel suicidal, or are concerned for a friend, don't wait: talk to someone, or learn about suicide prevention here.

in general what he argues is that if you take a look at animal cognition, human too, it's computational systems. Therefore, you want to look the units of computation. Think about a Turing machine, say, which is the simplest form of computation, you have to find units that have properties like "read", "write" and "address." That's the minimal computational unit, so you got to look in the brain for those. You're never going to find them if you look for strengthening of synaptic connections or field properties, and so on. You've got to start by looking for what's there and what's working and you see that from Marr's highest level.

it's basically in the spirit of Marr's analysis. So when you're studying vision, he argues, you first ask what kind of computational tasks is the visual system carrying out. And then you look for an algorithm that might carry out those computations and finally you search for mechanisms of the kind that would make the algorithm work. Otherwise, you may never find anything.

"Good Old Fashioned AI," as it's labeled now, made strong use of formalisms in the tradition of Gottlob Frege and Bertrand Russell, mathematical logic for example, or derivatives of it, like nonmonotonic reasoning and so on. It's interesting from a history of science perspective that even very recently, these approaches have been almost wiped out from the mainstream and have been largely replaced -- in the field that calls itself AI now -- by probabilistic and statistical models. My question is, what do you think explains that shift and is it a step in the right direction?

AI and robotics got to the point where you could actually do things that were useful, so it turned to the practical applications and somewhat, maybe not abandoned, but put to the side, the more fundamental scientific questions, just caught up in the success of the technology and achieving specific goals.

The approximating unanalyzed data kind is sort of a new approach, not totally, there's things like it in the past. It's basically a new approach that has been accelerated by the existence of massive memories, very rapid processing, which enables you to do things like this that you couldn't have done by hand. But I think, myself, that it is leading subjects like computational cognitive science into a direction of maybe some practical applicability... ..in engineering? Chomsky: ...But away from understanding.

I was very skeptical about the original work. I thought it was first of all way too optimistic, it was assuming you could achieve things that required real understanding of systems that were barely understood, and you just can't get to that understanding by throwing a complicated machine at it.

if success is defined as getting a fair approximation to a mass of chaotic unanalyzed data, then it's way better to do it this way than to do it the way the physicists do, you know, no thought experiments about frictionless planes and so on and so forth. But you won't get the kind of understanding that the sciences have always been aimed at -- what you'll get at is an approximation to what's happening.

Suppose you want to predict tomorrow's weather. One way to do it is okay I'll get my statistical priors, if you like, there's a high probability that tomorrow's weather here will be the same as it was yesterday in Cleveland, so I'll stick that in, and where the sun is will have some effect, so I'll stick that in, and you get a bunch of assumptions like that, you run the experiment, you look at it over and over again, you correct it by Bayesian methods, you get better priors. You get a pretty good approximation of what tomorrow's weather is going to be. That's not what meteorologists do -- they want to understand how it's working. And these are just two different concepts of what success means, of what achievement is.

if you get more and more data, and better and better statistics, you can get a better and better approximation to some immense corpus of text, like everything in The Wall Street Journal archives -- but you learn nothing about the language.

the right approach, is to try to see if you can understand what the fundamental principles are that deal with the core properties, and recognize that in the actual usage, there's going to be a thousand other variables intervening -- kind of like what's happening outside the window, and you'll sort of tack those on later on if you want better approximations, that's a different approach.

take a concrete example of a new field in neuroscience, called Connectomics, where the goal is to find the wiring diagram of very complex organisms, find the connectivity of all the neurons in say human cerebral cortex, or mouse cortex. This approach was criticized by Sidney Brenner, who in many ways is [historically] one of the originators of the approach. Advocates of this field don't stop to ask if the wiring diagram is the right level of abstraction -- maybe it's no

if you went to MIT in the 1960s, or now, it's completely different. No matter what engineering field you're in, you learn the same basic science and mathematics. And then maybe you learn a little bit about how to apply it. But that's a very different approach. And it resulted maybe from the fact that really for the first time in history, the basic sciences, like physics, had something really to tell engineers. And besides, technologies began to change very fast, so not very much point in learning the technologies of today if it's going to be different 10 years from now. So you have to learn the fundamental science that's going to be applicable to whatever comes along next. And the same thing pretty much happened in medicine.

that's the kind of transition from something like an art, that you learn how to practice -- an analog would be trying to match some data that you don't understand, in some fashion, maybe building something that will work -- to science, what happened in the modern period, roughly Galilean science.

it turns out that there actually are neural circuits which are reacting to particular kinds of rhythm, which happen to show up in language, like syllable length and so on. And there's some evidence that that's one of the first things that the infant brain is seeking -- rhythmic structures. And going back to Gallistel and Marr, its got some computational system inside which is saying "okay, here's what I do with these things" and say, by nine months, the typical infant has rejected -- eliminated from its repertoire -- the phonetic distinctions that aren't used in its own language.

people like Shimon Ullman discovered some pretty remarkable things like the rigidity principle. You're not going to find that by statistical analysis of data. But he did find it by carefully designed experiments. Then you look for the neurophysiology, and see if you can find something there that carries out these computations. I think it's the same in language, the same in studying our arithmetical capacity, planning, almost anything you look at. Just trying to deal with the unanalyzed chaotic data is unlikely to get you anywhere, just like as it wouldn't have gotten Galileo anywhere.

with regard to cognitive science, we're kind of pre-Galilean, just beginning to open up the subject

You can invent a world -- I don't think it's our world -- but you can invent a world in which nothing happens except random changes in objects and selection on the basis of external forces. I don't think that's the way our world works, I don't think it's the way any biologist thinks it is. There are all kind of ways in which natural law imposes channels within which selection can take place, and some things can happen and other things don't happen. Plenty of things that go on in the biology in organisms aren't like this. So take the first step, meiosis. Why do cells split into spheres and not cubes? It's not random mutation and natural selection; it's a law of physics. There's no reason to think that laws of physics stop there, they work all the way through. Well, they constrain the biology, sure. Chomsky: Okay, well then it's not just random mutation and selection. It's random mutation, selection, and everything that matters, like laws of physics.

What I think is valuable is the history of science. I think we learn a lot of things from the history of science that can be very valuable to the emerging sciences. Particularly when we realize that in say, the emerging cognitive sciences, we really are in a kind of pre-Galilean stage. We don't know wh

at we're looking for anymore than Galileo did, and there's a lot to learn from that.

The 2004 campaign was the year of the “Web log,” or blog, when mainstream reporters and campaigns officially began losing any control they may have had over political new

Marco Rubio’s campaign marched into the election season ready to fight the usual news-cycle-by-news-cycle skirmishes. It was surprised to learn that, lo and behold, “There was no news cycle — everything was one big fire hose,” Alex Conant, a senior Rubio strategist, told me. “News was constantly breaking and at the end of the day hardly anything mattered. Things would happen; 24 hours later, everyone was talking about something else.”

Snapchat represents a change to something else: the longevity of news, how durably it keeps in our brain cells and our servers.

Snapchat is recording the here and the now, playing for today. Tomorrow will bring something new that renders today obsolete. It’s a digital Tibetan sand painting made in the image of the millennial mind.

Snapchat executives say they set up the app this way because this is what their tens of millions of younger users want; it’s how they live.

They can’t possibly have enough bandwidth to process all the incoming information and still dwell on what already was, can they?

Experienced strategists and their candidates, who could always work through their election plans methodically — promoting their candidacies one foot in front of the other, adjusting here and there for the unexpected — suddenly found that they couldn’t operate the way they always did.

The question this year has been whether 2016 will be the “Snapchat election,

Then there was Jeb Bush, expecting to press ahead by presenting what he saw as leading-edge policy proposals that would set off a prolonged back-and-forth. When Mr. Bush rolled out a fairly sweeping plan to upend the college loan system, the poor guy thought this was going to become a big thing.

It drew only modest coverage and was quickly buried by the latest bit from Donald Trump.

In this “hit refresh” political culture, damaging news does not have to stick around for long, either. The next development, good or bad, replaces it almost immediately.

Mr. Miller pointed to a recent episode in which Mr. Trump said a protester at a rally had “ties to ISIS,” after that protester charged the stage. No such ties existed. “He says ‘ISIS is attacking me’; this was debunked in eight minutes by Twitter,” Mr. Miller said. “Cable talked about it for three hours and it went away.”

“Hillary Clinton said that she was under sniper fire in Bosnia” — she wasn’t — “and that has stuck with her for 20 years,”

Mr. Trump has mastered this era of short attention spans in politics by realizing that if you’re the one regularly feeding the stream, you can forever move past your latest trouble, and hasten the mass amnesia.

It was with this in mind that The Washington Post ran an editorial late last week reminding its readers of some of Mr. Trump’s more outlandish statements and policy positions

The Post urged its readers to “remember” more than two dozen items from Mr. Trump’s record, including that he promised “to round up 11 million undocumented immigrants and deport them,” and “lied about President Obama’s birth certificate.”

as the media habits of the young drive everybody else’s, I’m reminded of that old saw about those who forget history. Now, what was I saying?

How do we reconcile our enjoyment of social media even as we understand that the corporations who control them aren’t always acting in our best interests?

hat was because the underlying economic conditions hadn’t been changed or “disrupted,” to use a favorite Silicon Valley phrase. Google has to serve its shareholders, just like NBCUniversal does. As a result, many of the unappealing aspects of the legacy-media model have simply carried over into a digital age — namely, commercialism, consolidation, and centralization. In fact, the new system is even more dependent on advertising dollars than the one that preceded it, and digital advertising is far more invasive and ubiquitous

the popular narrative — new communications technologies would topple the establishment and empower regular people — didn’t accurately capture reality. Something more complex and predictable was happening. The old-media dinosaurs weren’t dying out, but were adapting to the online environment; meanwhile the new tech titans were coming increasingly to resemble their predecessors

I use lots of products that are created by companies whose business practices I object to and that don’t act in my best interests, or the best interests of workers or the environment — we all do, since that’s part of living under capitalism. That said, I refuse to invest so much in any platform that I can’t quit without remorse

these services aren’t free even if we don’t pay money for them; we pay with our personal data, with our privacy. This feeds into the larger surveillance debate, since government snooping piggybacks on corporate data collection. As I argue in the book, there are also negative cultural consequences (e.g., when advertisers are paying the tab we get more of the kind of culture marketers like to associate themselves with and less of the stuff they don’t) and worrying social costs. For example, the White House and the Federal Trade Commission have both recently warned that the era of “big data” opens new avenues of discrimination and may erode hard-won consumer protections.

I’m resistant to the tendency to place this responsibility solely on the shoulders of users. Gadgets and platforms are designed to be addictive, with every element from color schemes to headlines carefully tested to maximize clickability and engagement. The recent news that Facebook tweaked its algorithms for a week in 2012, showing hundreds of thousands of users only “happy” or “sad” posts in order to study emotional contagion — in other words, to manipulate people’s mental states — is further evidence that these platforms are not neutral. In the end, Facebook wants us to feel the emotion of wanting to visit Facebook frequently

social inequalities that exist in the real world remain meaningful online. What are the particular dangers of discrimination on the Internet?

That it’s invisible or at least harder to track and prove. We haven’t figured out how to deal with the unique ways prejudice plays out over digital channels, and that’s partly because some folks can’t accept the fact that discrimination persists online. (After all, there is no sign on the door that reads Minorities Not Allowed.)

just because the Internet is open doesn’t mean it’s equal; offline hierarchies carry over to the online world and are even amplified there. For the past year or so, there has been a lively discussion taking place about the disproportionate and often outrageous sexual harassment women face simply for entering virtual space and asserting themselves there — research verifies that female Internet users are dramatically more likely to be threatened or stalked than their male counterparts — and yet there is very little agreement about what, if anything, can be done to address the problem.

What steps can we take to encourage better representation of independent and non-commercial media? We need to fund it, first and foremost. As individuals this means paying for the stuff we believe in and want to see thrive. But I don’t think enlightened consumption can get us where we need to go on its own. I’m skeptical of the idea that we can shop our way to a better world. The dominance of commercial media is a social and political problem that demands a collective solution, so I make an argument for state funding and propose a reconceptualization of public media. More generally, I’m struck by the fact that we use these civic-minded metaphors, calling Google Books a “library” or Twitter a “town square” — or even calling social media “social” — but real public options are off the table, at least in the United States. We hand the digital commons over to private corporations at our peril.

6. You advocate for greater government regulation of the Internet. Why is this important?

I’m for regulating specific things, like Internet access, which is what the fight for net neutrality is ultimately about. We also need stronger privacy protections and restrictions on data gathering, retention, and use, which won’t happen without a fight.

I challenge the techno-libertarian insistence that the government has no productive role to play and that it needs to keep its hands off the Internet for fear that it will be “broken.” The Internet and personal computing as we know them wouldn’t exist without state investment and innovation, so let’s be real.

there’s a pervasive and ill-advised faith that technology will promote competition if left to its own devices (“competition is a click away,” tech executives like to say), but that’s not true for a variety of reasons. The paradox of our current media landscape is this: our devices and consumption patterns are ever more personalized, yet we’re simultaneously connected to this immense, opaque, centralized infrastructure. We’re all dependent on a handful of firms that are effectively monopolies — from Time Warner and Comcast on up to Google and Facebook — and we’re seeing increased vertical integration, with companies acting as both distributors and creators of content. Amazon aspires to be the bookstore, the bookshelf, and the book. Google isn’t just a search engine, a popular browser, and an operating system; it also invests in original content

So it’s not that the Internet needs to be regulated but that these big tech corporations need to be subject to governmental oversight. After all, they are reaching farther and farther into our intimate lives. They’re watching us. Someone should be watching them.

And in many cases, though not all, people living in areas threatened by severe natural hazards do so by choice. If a risk has not been imposed on us, we take it much less seriously. Though Schulz’s piece certainly made a splash online, it is hard to imagine a mass exodus of Portlanders and Seattleites in response. Hey, they like it there.

They don’t have much to compare the future earthquake to. After all, there hasn’t been an earthquake or tsunami like it there since roughly 1700. Schulz poeticizes this problem, calling out humans for their “ignorance of or an indifference to those planetary gears which turn more slowly than our own.” Once again, this confounds our emotional connection to the risk.

But our “temporal parochialism,” as Schulz calls it, also undoes our grasp on probability. “We think probability happens with some sort of regularity or pattern,” says Ropeik. “If an earthquake is projected to hit within 50 years, when there hasn’t been one for centuries, we don’t think it’s going to happen.” Illogical thinking works in reverse, too: “If a minor earthquake just happened in Seattle, we think we’re safe.”

The belief that an unlikely event won’t happen again for a while is called a gambler’s fallacy. Probability doesn’t work like that. The odds are the same with every roll of the dice.

For individuals and government alike, addressing every point of concern requires a cost-benefit analysis. When kids barely have pencils and paper in schools that already exist, how much is appropriate to invest in earthquake preparedness? Even when that earthquake will kill thousands, displace millions, and cripple a region’s economy for decades to come—as Cascadia is projected to—the answer is complicated. “You immediately run into competing issues,” says Slovic. “When you’re putting resources into earthquake protection that has to be taken away from current social needs—that is a very difficult sell.”​

There are things people can do to combat our innate irrationality. The first is obvious: education. California has a seismic safety commission whose job is to publicize the risks of earthquakes and advocate for preparedness at household and state policy levels.

Another idea is similar to food safety ratings in the windows of some cities’ restaurants. Schulz reports that some 75 percent of Oregon’s structures aren’t designed to hold up to a really big Cascadia quake. “These buildings could have their risk and safety score publicly posted,” says Slovic. “That would motivate people to retrofit or mitigate those risks, particularly if they are schools.”

science points to a hard truth. Humans are simply inclined to be more concerned about what’s immediately in front of us: Snakes, fast-moving cars, unfamiliar chemical compounds in our breakfast cereal and the like will always elicit a quicker response than an abstract, far-off hazard.

Nevertheless, she seemed to choose her words carefully as she spoke about the campaign.

she wanted to get away from the idea that this project was politically motivated, or anti-Trump.

But the issue of ambition, and the way it is used to defame women, is nevertheless personal to her.

This was confusing to Ms. Burch, who never saw herself as being a particularly threatening person.

“I do it, too,” she said. “I’m guilty of all of it.”

And the word “feminist” began to shed its Bella Abzug and Betty Friedan connotations, as women like Madonna went from saying they are “not feminists” but “humanists” to wearing T-shirts at anti-Trump events that had the word “feminist” emblazoned across the center.

Eventually Brad Katsuyama came to realize that the most sophisticated investors didn’t know what was going on in their own market. Not the big mutual funds, Fidelity and Vanguard. Not the big money-management firms like T. Rowe Price and Capital Group. Not even the most sophisticated hedge funds.

The deep problem with the system was a kind of moral inertia. So long as it served the narrow self-interests of everyone inside it, no one on the inside would ever seek to change it, no matter how corrupt or sinister it became

Technology had collided with Wall Street in a peculiar way. It had been used to increase efficiency. But it had also been used to introduce a peculiar sort of market inefficiency. Taking advantage of loopholes in some well-meaning regulation introduced in the mid-2000s, some large amount of what Wall Street had been doing with technology was simply so someone inside the financial markets would know something that the outside world did not. The same system that once gave us subprime-mortgage collateralized debt obligations no investor could possibly truly understand now gave us stock-market trades involving fractions of a penny that occurred at unsafe speeds using order types that no investor could possibly truly understand.

The trouble with the stock market — with all of the public and private exchanges — was that they were fantastically gameable, and had been gamed: first by clever guys in small shops, and then by prop traders who moved inside the big Wall Street banks. That was the problem, Puz thought. From the point of view of the most sophisticated traders, the stock market wasn’t a mechanism for channeling capital to productive enterprise but a puzzle to be solved.

As they worked through the order types, the Puzzle Masters created a taxonomy of predatory behavior in the stock market. Broadly speaking, it appeared as if there were three activities that led to a vast amount of grotesquely unfair trading. The first they called electronic front-running — seeing an investor trying to do something in one place and racing ahead of him to the next (what had happened to Katsuyama when he traded at RBC). The second they called rebate arbitrage — using the new complexity to game the seizing of whatever legal kickbacks, called rebates within the industry, the exchange offered without actually providing the liquidity that the rebate was presumably meant to entice. The third, and probably by far the most widespread, they called slow-market arbitrage. This occurred when a high-frequency trader was able to see the price of a stock change on one exchange and pick off orders sitting on other exchanges before those exchanges were able to react. This happened all day, every day, and very likely generated more billions of dollars a year than the other strategies combined.

IEX had made its point: That to function properly, a financial market didn’t need to be rigged in someone’s favor. It didn’t need payment for order flow and co-location and all sorts of unfair advantages possessed by a small handful of traders. All it needed was for investors to take responsibility for understanding it, and then to seize its controls. “The backbone of the market,” Katsuyama says, “is investors coming together to trade.”

If an investor as large as T. Rowe Price, which acted on behalf of millions of investors, had trouble obtaining the information it needed to determine if its brokers had acted in their interest, what chance did the little guy have?

The stock market really was rigged. Katsuyama often wondered how enterprising politicians and plaintiffs’ lawyers and state attorneys general would respond to that realization. (This March, the New York attorney general, Eric Schneiderman, announced a new investigation of the stock exchanges and the dark pools, and their relationships with high-frequency traders.

tech­nology is allow­ing these practices to go mainstream, and that represents a big new step for consumers. For decades, inventory manage­ment was largely the province of companies, not individuals,

he Great Recession is responsible for some of the decline. But it’s highly possible that a perfect storm of economic and demographic factors—from high gas prices, to re-­urbanization, to stagnating wages, to new technologies enabling a different kind of consumption—has fundamentally changed the game for Millennials

The emergence of the “sharing economy”—services that use the Web to let companies and families share otherwise idle goods—is headlined by Zipcar, but it also involves companies such as Airbnb, a shared market­place for bedrooms and other accommodations for travelers; and thred­UP, a site where parents can buy and sell kids’ used clothing.

Millennials have turned against both cars and houses in dramatic and historic fashion. Just as car sales have plummeted among their age cohort, the share of young people getting their first mortgage between 2009 and 2011 is half what it was just 10 years ago

today, peer-to-peer software and mobile technology allow us all to have access, just when we need it, to the things we used to have to buy and hold. And the most powerful application is for cars.

Car ownership, meanwhile, has slipped down the hierarchy of status goods for many young adults. “Zipcar conducted a survey of Millennials,

“And this generation said, ‘We don’t care about owning a car.’ Cars used to be what people aspired to own. Now it’s the smartphone.”

Smartphones compete against cars for young people’s big-ticket dollars, since the cost of a good phone and data plan can exceed $1,000 a year. But they also provide some of the same psychic benefits—opening new vistas and carrying us far from the physical space in which we reside. “You no longer need to feel connected to your friends with a car

mobile technology has empowered more than just car-sharing. It has empowered friendships that can be maintained from a distance. The upshot could be a continuing shift from automobiles to mobile technology, and a big reduction in spending.