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People with heart failure-related difficulties could monitor blood flow and body temperature; those with central nervous system issues, including schizophrenia and Alzheimer’s disease, could take the pills to monitor vital signs in real time.

Future generations of these pills could even be convenience tools.

Once that pill is in your body, you could pick up your smartphone and not have to type in a password. Instead, you are the password. Sit in the car and it will start. Touch the handle to your home door and it will automatically unlock. “Essentially, your entire body becomes your authentication token,

“The wonderful is that there are a great number of things you want to know about yourself on a continual basis, especially if you’re diabetic or suffer from another disease. The terrible is that health insurance companies could know about the inner workings of your body.”

And the implications of a tiny computer inside your body being hacked? Let’s say they are troubling.

After it has done its job, flowing down around the stomach and through the intestinal tract, what happens next?“It passes naturally through the body in about 24 hours,” Ms. Carbonelli said, but since each pill costs $46, “some people choose to recover and recycle it.”

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.

Hedonic well-being comes from an experience a person seeks out that gives them pleasure.

Eudaimonic well-being is a kind of happiness that comes not from consuming something but from a sustained effort at working toward something bigger than you.

they can and do influence each other, so it has been hard for scientists to measure which kind has had a greater positive influence on someone's physical or psychological well-being.

there is an increased expression of genes involved in inflammation and a decreased antiviral response. People who are subjected to long periods of stress have white blood cells that make slightly more pro-inflammatory proteins on a constant basis.

Bottom line? Happiness that comes from working for the greater good has a much more positive genetic impact.

The people who found happiness by pursuing a greater good had a lower level of this inflammatory gene expression and strong antiviral and antibody gene expression.

Inevitably, some of those initial steps will have been influenced by seemingly trivial random events. So it is reasonable to conclude that virtually all successful careers entail at least a modicum of luck.

One’s date of birth can matter enormously, for example. According to a 2008 study, most children born in the summer tend to be among the youngest members of their class at school, which appears to explain why they are significantly less likely to hold leadership positions during high school and thus, another study indicates, less likely to land premium jobs later in life. Similarly, according to research published in the journal Economics Letters in 2012, the number of American chief executives who were born in June and July is almost one-third lower than would be expected on the basis of chance alone.

To acknowledge the importance of random events is not to suggest that success is independent of talent and effort. In highly competitive arenas, those who do well are almost always extremely talented and hard-working.

Such expertise comes not from luck but from thousands of hours of assiduous effort.

Being born in a good environment is one of the few dimensions of luck we can control — that is, at least we can decide how lucky our children will be.

The unlucky population is growing, and its luck is getting worse.

Evidence from the social sciences demonstrates that beyond a certain income threshold, people’s sense of well-being depends much more on their relative purchasing power than on how much they spend in absolute terms. If top tax rates were a little higher, all homes would be a little smaller, all cars a little less expensive, all diamonds a little more modest and all celebrations a little less costly. The standards that define “special” would adjust accordingly, leaving most successful people quite satisfied.

Merely prompting people to reflect on their good fortune tends to make them more willing to contribute to the common good, according to a 2010 study published in the journal Emotion.

Mark Zuckerberg is 3.17 degrees of separation from all Facebook users.

The typical Facebook user has 155 friends, but only describes 50 of them as friends in real life, according to a 2014 study from the Pew Research Center. Thirty-five percent of people have Facebook friends they've never met in person.

The original "six degrees of separation" experiment required people to know each other fairly well: They had to be on a first-name basis, at a time when society was slightly more formal, in order for the connection to count.

About one-third of the documents eventually reached the stockbroker, after a chain of, on average, six people — the six degrees of separation. It's a small world after all, Milgram concluded.

She found instead that Milgram's conclusions rested on a shaky foundation, and that class and race divided Americans more than his original paper admitted. The majority of Milgram's letters didn't make it to the Boston stockbroker. And further experiments that factored in class and race suggested that making connections across those barriers was even more challenging

While middle- and high-income people were able to find their targets regardless of their household income, low-income people could only connect with other low-income families, Kleinfeld wrote in a 2002 article in the journal Society.

The correct interpretation of Milgram, she argued, was not the optimistic conclusion that we're all only a few degrees of separation away. Instead, it's that there are still barriers that are insurmountable.

But the real divide is between people who are on Facebook and those who aren't on the internet at all. Facebook users make up about 62 percent of American adults but 72 percent of all internet users. Americans without the internet are disproportionately older, rural, and less educated. As Facebook users get closer, they might be becoming ever more isolated.

It's quite possible that our love of music was simply an accident. We originally evolved emotions to help us navigate dangerous worlds (fear) and social situations (joy). And somehow, the tones and beats of musical composition activate similar brain areas.

Nature Neuroscience, led by Zatorre, researchers found that dopamine release is strongest when a piece of music reaches an emotional peak and the listener feels "chills"— the spine-tingling sensation of excitement and awe.

"Music engages the same [reward] system, even though it is not biologically necessary for survival," says Zatorre.

Presumably, we evolved to recognize patterns because it's an essential skill for survival. Does a rustling in the trees mean a dangerous animal is about to attack? Does the smell of smoke mean I should run, because a fire may be coming my way?

Music is a pattern. As we listen, we're constantly anticipating what melodies, harmonies, and rhythms may come next.

That's why we typically don't like styles of music we're not familiar with. When we're unfamiliar with a style of music, we don't have a basis to predict its patterns

We learn through our cultures what sounds constitute music. The rest is random noise.

When we hear a piece of music, its rhythm latches onto us in a process called entrainment. If the music is fast-paced, our heartbeats and breathing patterns will accelerate to match the beat.

Another hypothesis is that music latches onto the regions of the brain attuned to speech — which convey all of our emotions.

"It makes sense that our brains are really good at picking up emotions in speech," the French Institute of Science's Aucouturier says. It's essential to understand if those around us are happy, sad, angry, or scared. Much of that information is contained in the tone of a person's speech. Higher-pitched voices sound happier. More warbled voices are scared.

Music may then be an exaggerated version of speech.

And because we tend to mirror the emotions we hear in others, if the music is mimicking happy speech, then the listener will become happy too.

But Verrilli countered that the federal government retains authority to review on a "case-by-case basis" significant drug trafficking crimes.

Dozens of popular books by nonexperts have filled the void, many claiming that IQ—which after more than a century remains the dominant metric for intelligence—predicts nothing important or that intelligence is simply too complex and subtle to be measured.

evidence points toward a strong genetic component in IQ. Based on studies of twins, siblings, and adoption, contemporary estimates put the heritability of IQ at 50 to 80 percent

intelligence has a genetic recipe

“Do you know any Perl?” Li asked him. Perl is a programming language often used to analyze genomic data. Zhao admitted he did not; in fact, he had no programming skills at all. Li handed him a massive textbook, Programming Perl. There were only two weeks left in the camp, so this would get rid of the kid for good. A few days later, Zhao returned. “I finished it,” he said. “The problems are kind of boring. Do you have anything harder?” Perl is a famously complicated language that takes university students a full year to learn.

So Li gave him a large DNA data set and a complicated statistical problem. That should do it. But Zhao returned later that day. “Finished.” Not only was it finished—and correct—but Zhao had even built a slick interface on top of the data.

driven by a fascination with kids who are born smart; he wants to know what makes them—and by extension, himself—the way they are.

His son, in contrast, showed no such restraint in the weeks before he was fired, regularly posting on Twitter about conspiracy theories involving Mrs. Clinton and her campaign staff well after the election.He continued to push his support for the fake news about Comet Ping Pong after his messages on Twitter about Sunday’s episode began attracting widespread attention. It was not until shortly before 3:30 p.m. Monday that he went silent on Twitter.

In one of the last messages he posted, he shared a post from another Twitter user who sought to spread a conspiracy theory that sprang up on the right-wing fringes after the shooting: that the suspect arrested at Comet Ping Pong, Edgar M. Welch, 28, of Salisbury, N.C., was actually an actor, and that the episode was a hoax cooked up to discredit the claim of a sex trafficking ring at the restaurant.

The two reports together establish the feasibility of trying to grow replacement human organs in animals, though such a goal is still far off.

Creating chimeras, especially those with human cells, may prove controversial, given the possibility that test animals could be humanized in undesirable ways. One would be if human cells should be incorporated into a pig’s brain, endowing it with human qualities. Almost no one wants a talking pig.

The ban is still in place, and it’s unclear whether the Trump administration would continue to consider lifting the moratorium or whether new objections would be raised to using public funds for this line of research.

But no one knows exactly what sequence of chemicals is required for the generation of each different tissue or organ. This may be why glassware experiments with stem cells have not yet lived up to their full promise.

Concern about human cells’ incorporation into a lower animal’s brain is not without basis. Dr. Steven Goldman of the University of Rochester Medical Center found in 2013 that mice injected with a special type of human brain cell had enhanced learning abilities.

Mr. Trump, the bombastic businessman who’s never held office, and Mr. Johnson, the former journalist turned mayor of London, might not put it this way, since they continue to cling to a conservative mantle. But they are riding a revolt of the working class against a 40-year-long project of the political right and its corporate backers that has dominated policy making in the English-speaking world for a generation.

The British political scientist Andrew Gamble at the University of Cambridge has argued that Western capitalism has experienced two transformational crises since the end of the 19th century. The first, brought about by the Depression of the 1930s, ended an era in which governments bowed to the gospel of the gold standard and were expected to butt out of the battles between labor and capital, letting markets function on their own, whatever the consequences

Mr. Keynes’s views ultimately prevailed, though, providing the basis for a new post-World War II orthodoxy favoring active government intervention in the economy and a robust welfare state. But that era ended when skyrocketing oil prices and economic mismanagement in the 1970s brought about a combination of inflation and unemployment that fatally undermined people’s trust in the state.

The Keynesian era ended when Margaret Thatcher and Ronald Reagan rode onto the scene with a version of capitalism based on tax cuts, privatization and deregulation that helped revive their engines of growth but led the workers of the world to the deeply frustrating, increasingly unequal economy of today.

After the Brexit vote, Lawrence Summers, former Treasury secretary under President Clinton and one of President Obama’s top economic advisers at the nadir of the Great Recession, laid out an argument for what he called “responsible nationalism,” which focused squarely on the interests of domestic workers.

Instead of negotiating more agreements to ease business across borders, governments would focus on deals to improve labor and environmental standards internationally. They might cut deals to prevent cross-border tax evasion.

There is, however, little evidence that the world’s leaders will go down that path. Despite the case for economic stimulus, austerity still rules across much of the West. In Europe, most governments have imposed stringent budget cuts — ensuring that all but the strongest economies would stall. In the United States, political polarization has brought fiscal policy — spending and taxes — to a standstill.

the Common Core standards used by a majority of K-12 programs in the country require that students be able to “distinguish among fact, opinion, and reasoned judgment in a text.”

So what’s wrong with this distinction and how does it undermine the view that there are objective moral facts?

For example, many people once thought that the earth was flat. It’s a mistake to confuse truth (a feature of the world) with proof (a feature of our mental lives)

Furthermore, if proof is required for facts, then facts become person-relative. Something might be a fact for me if I can prove it but not a fact for you if you can’t. In that case, E=MC2 is a fact for a physicist but not for me.

worse, students are taught that claims are either facts or opinions. They are given quizzes in which they must sort claims into one camp or the other but not both. But if a fact is something that is true and an opinion is something that is believed, then many claims will obviously be both

How does the dichotomy between fact and opinion relate to morality

Kids are asked to sort facts from opinions and, without fail, every value claim is labeled as an opinion.

Here’s a little test devised from questions available on fact vs. opinion worksheets online: are the following facts or opinions? — Copying homework assignments is wrong. — Cursing in school is inappropriate behavior. — All men are created equal. — It is worth sacrificing some personal liberties to protect our country from terrorism. — It is wrong for people under the age of 21 to drink alcohol. — Vegetarians are healthier than people who eat meat. — Drug dealers belong in prison.

The answer? In each case, the worksheets categorize these claims as opinions. The explanation on offer is that each of these claims is a value claim and value claims are not facts. This is repeated ad nauseum: any claim with good, right, wrong, etc. is not a fact.

In summary, our public schools teach students that all claims are either facts or opinions and that all value and moral claims fall into the latter camp. The punchline: there are no moral facts. And if there are no moral facts, then there are no moral truths.

It should not be a surprise that there is rampant cheating on college campuses: If we’ve taught our students for 12 years that there is no fact of the matter as to whether cheating is wrong, we can’t very well blame them for doing so later on.

If it’s not true that it’s wrong to murder a cartoonist with whom one disagrees, then how can we be outraged? If there are no truths about what is good or valuable or right, how can we prosecute people for crimes against humanity? If it’s not true that all humans are created equal, then why vote for any political system that doesn’t benefit you over others?

the curriculum sets our children up for doublethink. They are told that there are no moral facts in one breath even as the next tells them how they ought to behave.

Our children deserve a consistent intellectual foundation. Facts are things that are true. Opinions are things we believe. Some of our beliefs are true. Others are not. Some of our beliefs are backed by evidence. Others are not.

Value claims are like any other claims: either true or false, evidenced or not.

The hard work lies not in recognizing that at least some moral claims are true but in carefully thinking through our evidence for which of the many competing moral claims is correct.

Moral truths are not the same as scientific truths or mathematical truths. Yet they may still be used a guiding principle for our individual lives as well as our laws.But there is equal danger of giving moral judgments the designation of truth as there is in not doing so. Many people believe that abortion is murder on the same level as shooting someone with a gun. But many others do not. So is it true that abortion is murder?Moral principles can become generally accepted and then form the basis for our laws. But many long accepted moral principles were later rejected as being faulty. "Separate but equal" is an example. Judging homosexual relationships as immoral is another example.

Whoa! That Einstein derived an equation is a fact. But the equation represents a theory that may have to be tweaked at some point in the future. It may be a fact that the equation foretold the violence of atomic explosions, but there are aspects of nature that elude the equation. Remember "the theory of everything?"

Here is a moral fact, this is a sermon masquerading as a philosophical debate on facts, opinions and truth. This professor of religion is asserting that the government via common core is teaching atheism via the opinion vs fact.He is arguing, in a dishonest form, that public schools should be teaching moral facts. Of course moral facts is code for the Ten Commandments.

As a fourth grade teacher, I try to teach students to read critically, including distinguishing between facts and opinions as they read (and have been doing this long before the Common Core arrived, by the way). It's not always easy for children to grasp the difference. I can only imagine the confusion that would ensue if I introduced a third category -- moral "facts" that can't be proven but are true nonetheless!

horrible acts occur not because of moral uncertainty, but because people are too sure that their views on morality are 100% true, and anyone who fails to recognize and submit themselves are heathens who deserve death.I can't think of any case where a society has suffered because people are too thoughtful and open-minded to different perspectives on moral truth.In any case, it's not an elementary school's job to teach "moral truths."

The characterization of moral anti-realism as some sort of fringe view in philosophy is misleading. Claims that can be true or false are, it seems, 'made true' by features of the world. It's not clear to many in philosophy (like me) just what features of the world could make our moral claims true. We are more likely to see people's value claims as making claims about, and enforcing conformity to, our own (contingent) social norms. This is not to hold, as Mr. McBrayer seems to think follows, that there are no reasons to endorse or criticize these social norms.

This is nonsense. Giving kids the tools to distinguish between fact and opinion is hard enough in an age when Republicans actively deny reality on Fox News every night. The last thing we need is to muddy their thinking with the concept of "moral facts."A fact is a belief that everyone _should_ agree upon because it is observable and testable. Morals are not agreed upon by all. Consider the hot button issue of abortion.

Truthfully, I'm not terribly concerned that third graders will end up taking these lessons in the definition of fact versus opinion to the extremes considered here, or take them as a license to cheat. That will come much later, when they figure out, as people always have, what they can get a way with. But Prof. McBrayer, with his blithe expectation that all the grownups know that there moral "facts"? He scares the heck out of me.

I've long chafed at the language of "fact" v. "opinion", which is grounded in a very particular, limited view of human cognition. In my own ethics courses, I work actively to undermine the distinction, focusing instead on considered judgment . . . or even more narrowly, on consideration itself. (See http://wp.me/p5Ag0i-6M )

The real waffle here is the very concept of "moral facts." Our statements of values, even very important ones are, obviously, not facts. Trying to dress them up as if they are facts, to me, argues for a pretty serious moral weakness on the part of those advancing the idea.

Our core values are not important because they are facts. They are important because we collectively hold them and cherish them. To lean on the false crutch of "moral facts" to admit the weakness of your own moral convictions.

I would like to believe that there is a core of moral facts/values upon which all humanity can agree, but it would be tough to identify exactly what those are.

For the the ancient philosophers, reality comprised the Good, the True, and the Beautiful (what we might now call ethics, science and art), seeing these as complementary and inseparable, though distinct, realms. With the ascendency of science in our culture as the only valid measure of reality to the detriment of ethics and art (that is, if it is not observable and provable, it is not real), we have turned the good and the beautiful into mere "social constructs" that have no validity on their own. While I am sympathetic in many ways with Dr. McBrayer's objections, I think he falls into the trap of discounting the Good and The Beautiful as valid in and of themselves, and tries, instead, to find ways to give them validity through the True. I think his argument would have been stronger had he used the language of validity rather than the language of truth. Goodness, Truth and Beauty each have their own validity, though interdependent and inseparable. When we artificially extract one of these and give it primacy, we distort reality and alienate ourselves from it.

Professor McBrayer seems to miss the major point of the Common Core concern: can students distinguish between premises based on (reasonably construed) fact and premises based on emotion when evaluating conclusions? I would prefer that students learn to reason rather than be taught moral 'truth' that follows Professor McBrayer's logic.

Moral issues cannot scientifically be treated on the level that Prof. McBrayer is attempting to use in this column: true or false, fact or opinion or both. Instead, they should be treated as important characteristics of the systematic working of a society or of a group of people in general. One can compare the working of two groups of people: one in which e.g. cheating and lying is acceptable, and one in which they are not. One can use historical or model examples to show the consequences and the working of specific systems of morals. I think that this method - suitably adjusted - can be used even in second grade.

Relativism has nothing to do with liberalism. The second point is that I'm not sure it does all that much harm, because I have yet to encounter a student who thought that he or she had to withhold judgment on those who hold opposing political views!

The creators of the D.S.M. in the 1960s and ’70s “were real heroes at the time,” said Dr. Steven E. Hyman, a psychiatrist and neuroscientist at the Broad Institute and a former director at the National Institute of Mental Health. “They chose a model in which all psychiatric illnesses were represented as categories discontinuous with ‘normal.’ But this is totally wrong in a way they couldn’t have imagined. So in fact what they produced was an absolute scientific nightmare. Many people who get one diagnosis get five diagnoses, but they don’t have five diseases — they have one underlying condition.”

Dr. Insel is one of a growing number of scientists who think that the field needs an entirely new paradigm for understanding mental disorders, though neither he nor anyone else knows exactly what it will look like.

Decades of spending on neuroscience have taught scientists mostly what they do not know, undermining some of their most elemental assumptions. Genetic glitches that appear to increase the risk of schizophrenia in one person may predispose others to autism-like symptoms, or bipolar disorder. The mechanisms of the field’s most commonly used drugs — antidepressants like Prozac, and antipsychosis medications like Zyprexa — have revealed nothing about the causes of those disorders. And major drugmakers have scaled back psychiatric drug development, having virtually no new biological “targets” to shoot for.

Dr. Hyman, Dr. Insel and other experts said they hoped that the science of psychiatry would follow the direction of cancer research, which is moving from classifying tumors by where they occur in the body to characterizing them by their genetic and molecular signatures.

Dr. Insel said in the interview that his motivation was not to disparage the D.S.M. as a clinical tool, but to encourage researchers and especially outside reviewers who screen proposals for financing from his agency to disregard its categories and investigate the biological underpinnings of disorders instead.

Numerous environmental statutes mandate that government agencies consider “the best available science” when making decisions. And agencies routinely consult with scientific experts to fullfill such mandates.

Such provisions work reasonably well when science offers clear and simple, black-and-white answers. But when there is uncertainty, is the expectation of scientific objectivity realistic?

To gain insight into what role bias may play in listing decisions, we surveyed a group of grizzly bear researchers. We found that experts’ judgments were associated with a number of factors outside the “best commercial and scientific data,” including their professional affiliations and social norms. Furthermore, we found that while there is no consensus in the scientific community regarding the threats to grizzly bears, the majority of scientists support continued listing.

Serious empiricists frequently use regression analysis.

Regression analysis is inferior to RFT because of the difficulty of ruling out confounding factors (for example, that a gene jointly causes baldness and a preference for tight hats) and of establishing causation

RFT has its limitations as well. It is enormously expensive because you must (usually) pay a large number of people to participate in an experiment, though one can obtain a discount if one uses prisoners, especially those in a developing country. In addition, one cannot always generalize from RFTs.

academic research proceeds in fits and starts, using RFT when it can, but otherwise relying on regression analysis and similar tools, including qualitative case studies,

businesses also use RFT whenever they can. A business such as Wal-Mart, with thousands of stores, might try out some innovation like a new display in a random selection of stores, using the remaining stores as a control group

Manzi argues that the RFT—or more precisely, the overall approach to empirical investigation that the RFT exemplifies—provides a way of thinking about public policy. Thi

the universe is shaky even where, as in the case of physics, “hard science” plays the dominant role. The scientific method cannot establish truths; it can only falsify hypotheses. The hypotheses come from our daily experience, so even when science prunes away intuitions that fail the experimental method, we can never be sure that the theories that remain standing reflect the truth or just haven’t been subject to the right experiment. And even within its domain, the experimental method is not foolproof. When an experiment contradicts received wisdom, it is an open question whether the wisdom is wrong or the experiment was improperly performed.

The book is less interested in the RFT than in the limits of empirical knowledge. Given these limits, what attitude should we take toward government?

Much of scientific knowledge turns out to depend on norms of scientific behavior, good faith, convention, and other phenomena that in other contexts tend to provide an unreliable basis for knowledge.

Under this view of the world, one might be attracted to the cautious conservatism associated with Edmund Burke, the view that we should seek knowledge in traditional norms and customs, which have stood the test of time and presumably some sort of Darwinian competition—a human being is foolish, the species is wise. There are hints of this worldview in Manzi’s book, though he does not explicitly endorse it. He argues, for example, that we should approach social problems with a bias for the status quo; those who seek to change it carry the burden of persuasion. Once a problem is identified, we should try out our ideas on a small scale before implementing them across society

Pursuing the theme of federalism, Manzi argues that the federal government should institutionalize policy waivers, so states can opt out from national programs and pursue their own initiatives. A state should be allowed to opt out of federal penalties for drug crimes, for example.

It is one thing to say, as he does, that federalism is useful because we can learn as states experiment with different policies. But Manzi takes away much of the force of this observation when he observes, as he must, that the scale of many of our most urgent problems—security, the economy—is at the national level, so policymaking in response to these problems cannot be left to the states. He also worries about social cohesion, which must be maintained at a national level even while states busily experiment. Presumably, this implies national policy of some sort

Manzi’s commitment to federalism and his technocratic approach to policy, which relies so heavily on RFT, sit uneasily together. The RFT is a form of planning: the experimenter must design the RFT and then execute it by recruiting subjects, paying them, and measuring and controlling their behavior. By contrast, experimentation by states is not controlled: the critical element of the RFT—randomization—is absent.

The right way to go would be for the national government to conduct experiments by implementing policies in different states (or counties or other local units) by randomizing—that is, by ordering some states to be “treatment” states and other states to be “control” states,

Manzi’s reasoning reflects the top-down approach to social policy that he is otherwise skeptical of—although, to be sure, he is willing to subject his proposals to RFTs.

any privacy regulation that's going to make it through Congress has to provide clear ways for companies to continue profiting from data tracking. The key is coming up with an ethical framework in which they can do so, and Nissenbaum may have done just that. 

The traditional model of how this works says that your information is something like a currency and when you visit a website that collects data on you for one reason or another, you enter into a contract with that site. As long as the site gives you "notice" that data collection occurs -- usually via a privacy policy located through a link at the bottom of the page -- and you give "consent" by continuing to use the site, then no harm has been done. No matter how much data a site collects, if all they do is use it to show you advertising they hope is more relevant to you, then they've done nothing wrong.

let companies do standard data collection but require them to tell people when they are doing things with data that are inconsistent with the "context of the interaction" between a company and a person.

How can anyone make a reasonable determination of how their information might be used when there are more than 50 or 100 or 200 tools in play on a single website in a single month?

Nissenbaum doesn't think it's possible to explain the current online advertising ecosystem in a useful way without resorting to a lot of detail. She calls this the "transparency paradox," and considers it insoluble.

she wants to import the norms from the offline world into the online world. When you go to a bank, she says, you have expectations of what might happen to your communications with that bank. That should be true whether you're online, on the phone, or at the teller.  Companies can use your data to do bank stuff, but they can't sell your data to car dealers looking for people with a lot of cash on hand.

Nevermind that if you actually read all the privacy policies you encounter in a year, it would take 76 work days. And that calculation doesn't even account for all the 3rd parties that drain data from your visits to other websites. Even more to the point: there is no obvious way to discriminate between two separate webpages on the basis of their data collection policies. While tools have emerged to tell you how many data trackers are being deployed at any site at a given moment, the dynamic nature of Internet advertising means that it is nearly impossible to know the story through time

here's the big downside: it rests on the "norms" that people expect. While that may be socially optimal, it's actually quite difficult to figure out what the norms for a given situation might be. After all, there is someone else who depends on norms for his thinking about privacy.

One study found that men who consumed eight to 14 drinks a week had a 59% lower risk of heart failure compared with those who didn't drink.

But experts warn that regularly drinking more than that can cause cardiovascular damage instead, raising blood pressure, increasing the risk of hemorrhagic stroke and leading to cardiomyopathy, a dangerous enlargement of the heart.

Benefits of moderate drinking, defined as one drink a day for women, two for men. •Reduces the risk of coronary heart disease by 30% to 35%. Increases HDL 'good' cholesterol. •Prevents platelets from sticking together, reducing blood clots, and lowers the risk of congestive heart failure. •Cuts the risk of heart attack by 40% to 50% in healthy men. •Reduces the risk of stroke and dementia.

Cancer risks linked to drinking. (Risks vary with the amount of alcohol consumed.)•Raises the risk of oral and pharyngeal cancer by 20% and risk of breast cancer by 8% among people who have one or fewer drinks a day. •Raises risk of oral cancers 73%, risk of liver cancer 20% and risk of breast cancer 31% among people who have two to three drinks per day. •Associated with a fivefold increase in risk of oral, pharyngeal and esophageal cancers in people who have four or more drinks per day. •Raises the risk of colorectal cancer by 52%, pancreatic cancer by 22%, breast cancer by 46%.