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Suppose you want to say, "Bush read Chomsky's latest book." Let's focus on just the verb, "read." To say this sentence in English, we have to mark the verb for tense; in this case, we have to pronounce it like "red" and not like "reed." In Indonesian you need not (in fact, you can't) alter the verb to mark tense. In Russian you would have to alter the verb to indicate tense and gender. So if it was Laura Bush who did the reading, you'd use a different form of the verb than if it was George. In Russian you'd also have to include in the verb information about completion. If George read only part of the book, you'd use a different form of the verb than if he'd diligently plowed through the whole thing. In Turkish you'd have to include in the verb how you acquired this information: if you had witnessed this unlikely event with your own two eyes, you'd use one verb form, but if you had simply read or heard about it, or inferred it from something Bush said, you'd use a different verb form.

Clearly, languages require different things of their speakers. Does this mean that the speakers think differently about the world? Do English, Indonesian, Russian, and Turkish speakers end up attending to, partitioning, and remembering their experiences differently just because they speak different languages?

For some scholars, the answer to these questions has been an obvious yes. Just look at the way people talk, they might say. Certainly, speakers of different languages must attend to and encode strikingly different aspects of the world just so they can use their language properly. Scholars on the other side of the debate don't find the differences in how people talk convincing. All our linguistic utterances are sparse, encoding only a small part of the information we have available. Just because English speakers don't include the same information in their verbs that Russian and Turkish speakers do doesn't mean that English speakers aren't paying attention to the same things; all it means is that they're not talking about them. It's possible that everyone thinks the same way, notices the same things, but just talks differently.

Believers in cross-linguistic differences counter that everyone does not pay attention to the same things: if everyone did, one might think it would be easy to learn to speak other languages. Unfortunately, learning a new language (especially one not closely related to those you know) is never easy; it seems to require paying attention to a new set of distinctions. Whether it's distinguishing modes of being in Spanish, evidentiality in Turkish, or aspect in Russian, learning to speak these languages requires something more than just learning vocabulary: it requires paying attention to the right things in the world so that you have the correct information to include in what you say.

Follow me to Pormpuraaw, a small Aboriginal community on the western edge of Cape York, in northern Australia. I came here because of the way the locals, the Kuuk Thaayorre, talk about space. Instead of words like "right," "left," "forward," and "back," which, as commonly used in English, define space relative to an observer, the Kuuk Thaayorre, like many other Aboriginal groups, use cardinal-direction terms — north, south, east, and west — to define space.1 This is done at all scales, which means you have to say things like "There's an ant on your southeast leg" or "Move the cup to the north northwest a little bit." One obvious consequence of speaking such a language is that you have to stay oriented at all times, or else you cannot speak properly. The normal greeting in Kuuk Thaayorre is "Where are you going?" and the answer should be something like " Southsoutheast, in the middle distance." If you don't know which way you're facing, you can't even get past "Hello."

The result is a profound difference in navigational ability and spatial knowledge between speakers of languages that rely primarily on absolute reference frames (like Kuuk Thaayorre) and languages that rely on relative reference frames (like English).2 Simply put, speakers of languages like Kuuk Thaayorre are much better than English speakers at staying oriented and keeping track of where they are, even in unfamiliar landscapes or inside unfamiliar buildings. What enables them — in fact, forces them — to do this is their language. Having their attention trained in this way equips them to perform navigational feats once thought beyond human capabilities. Because space is such a fundamental domain of thought, differences in how people think about space don't end there. People rely on their spatial knowledge to build other, more complex, more abstract representations. Representations of such things as time, number, musical pitch, kinship relations, morality, and emotions have been shown to depend on how we think about space. So if the Kuuk Thaayorre think differently about space, do they also think differently about other things, like time? This is what my collaborator Alice Gaby and I came to Pormpuraaw to find out.

To test this idea, we gave people sets of pictures that showed some kind of temporal progression (e.g., pictures of a man aging, or a crocodile growing, or a banana being eaten). Their job was to arrange the shuffled photos on the ground to show the correct temporal order. We tested each person in two separate sittings, each time facing in a different cardinal direction. If you ask English speakers to do this, they'll arrange the cards so that time proceeds from left to right. Hebrew speakers will tend to lay out the cards from right to left, showing that writing direction in a language plays a role.3 So what about folks like the Kuuk Thaayorre, who don't use words like "left" and "right"? What will they do? The Kuuk Thaayorre did not arrange the cards more often from left to right than from right to left, nor more toward or away from the body. But their arrangements were not random: there was a pattern, just a different one from that of English speakers. Instead of arranging time from left to right, they arranged it from east to west. That is, when they were seated facing south, the cards went left to right. When they faced north, the cards went from right to left. When they faced east, the cards came toward the body and so on. This was true even though we never told any of our subjects which direction they faced. The Kuuk Thaayorre not only knew that already (usually much better than I did), but they also spontaneously used this spatial orientation to construct their representations of time.

I have described how languages shape the way we think about space, time, colors, and objects. Other studies have found effects of language on how people construe events, reason about causality, keep track of number, understand material substance, perceive and experience emotion, reason about other people's minds, choose to take risks, and even in the way they choose professions and spouses.8 Taken together, these results show that linguistic processes are pervasive in most fundamental domains of thought, unconsciously shaping us from the nuts and bolts of cognition and perception to our loftiest abstract notions and major life decisions. Language is central to our experience of being human, and the languages we speak profoundly shape the way we think, the way we see the world, the way we live our lives.

The fact that even quirks of grammar, such as grammatical gender, can affect our thinking is profound. Such quirks are pervasive in language; gender, for example, applies to all nouns, which means that it is affecting how people think about anything that can be designated by a noun.

How does an artist decide whether death, say, or time should be painted as a man or a woman? It turns out that in 85 percent of such personifications, whether a male or female figure is chosen is predicted by the grammatical gender of the word in the artist's native language. So, for example, German painters are more likely to paint death as a man, whereas Russian painters are more likely to paint death as a woman.

Does treating chairs as masculine and beds as feminine in the grammar make Russian speakers think of chairs as being more like men and beds as more like women in some way? It turns out that it does. In one study, we asked German and Spanish speakers to describe objects having opposite gender assignment in those two languages. The descriptions they gave differed in a way predicted by grammatical gender. For example, when asked to describe a "key" — a word that is masculine in German and feminine in Spanish — the German speakers were more likely to use words like "hard," "heavy," "jagged," "metal," "serrated," and "useful," whereas Spanish speakers were more likely to say "golden," "intricate," "little," "lovely," "shiny," and "tiny." To describe a "bridge," which is feminine in German and masculine in Spanish, the German speakers said "beautiful," "elegant," "fragile," "peaceful," "pretty," and "slender," and the Spanish speakers said "big," "dangerous," "long," "strong," "sturdy," and "towering." This was true even though all testing was done in English, a language without grammatical gender. The same pattern of results also emerged in entirely nonlinguistic tasks (e.g., rating similarity between pictures). And we can also show that it is aspects of language per se that shape how people think: teaching English speakers new grammatical gender systems influences mental representations of objects in the same way it does with German and Spanish speakers. Apparently even small flukes of grammar, like the seemingly arbitrary assignment of gender to a noun, can have an effect on people's ideas of concrete objects in the world.

Even basic aspects of time perception can be affected by language. For example, English speakers prefer to talk about duration in terms of length (e.g., "That was a short talk," "The meeting didn't take long"), while Spanish and Greek speakers prefer to talk about time in terms of amount, relying more on words like "much" "big", and "little" rather than "short" and "long" Our research into such basic cognitive abilities as estimating duration shows that speakers of different languages differ in ways predicted by the patterns of metaphors in their language. (For example, when asked to estimate duration, English speakers are more likely to be confused by distance information, estimating that a line of greater length remains on the test screen for a longer period of time, whereas Greek speakers are more likely to be confused by amount, estimating that a container that is fuller remains longer on the screen.)

An important question at this point is: Are these differences caused by language per se or by some other aspect of culture? Of course, the lives of English, Mandarin, Greek, Spanish, and Kuuk Thaayorre speakers differ in a myriad of ways. How do we know that it is language itself that creates these differences in thought and not some other aspect of their respective cultures? One way to answer this question is to teach people new ways of talking and see if that changes the way they think. In our lab, we've taught English speakers different ways of talking about time. In one such study, English speakers were taught to use size metaphors (as in Greek) to describe duration (e.g., a movie is larger than a sneeze), or vertical metaphors (as in Mandarin) to describe event order. Once the English speakers had learned to talk about time in these new ways, their cognitive performance began to resemble that of Greek or Mandarin speakers. This suggests that patterns in a language can indeed play a causal role in constructing how we think.6 In practical terms, it means that when you're learning a new language, you're not simply learning a new way of talking, you are also inadvertently learning a new way of thinking. Beyond abstract or complex domains of thought like space and time, languages also meddle in basic aspects of visual perception — our ability to distinguish colors, for example. Different languages divide up the color continuum differently: some make many more distinctions between colors than others, and the boundaries often don't line up across languages.

To test whether differences in color language lead to differences in color perception, we compared Russian and English speakers' ability to discriminate shades of blue. In Russian there is no single word that covers all the colors that English speakers call "blue." Russian makes an obligatory distinction between light blue (goluboy) and dark blue (siniy). Does this distinction mean that siniy blues look more different from goluboy blues to Russian speakers? Indeed, the data say yes. Russian speakers are quicker to distinguish two shades of blue that are called by the different names in Russian (i.e., one being siniy and the other being goluboy) than if the two fall into the same category. For English speakers, all these shades are still designated by the same word, "blue," and there are no comparable differences in reaction time. Further, the Russian advantage disappears when subjects are asked to perform a verbal interference task (reciting a string of digits) while making color judgments but not when they're asked to perform an equally difficult spatial interference task (keeping a novel visual pattern in memory). The disappearance of the advantage when performing a verbal task shows that language is normally involved in even surprisingly basic perceptual judgments — and that it is language per se that creates this difference in perception between Russian and English speakers.

What it means for a language to have grammatical gender is that words belonging to different genders get treated differently grammatically and words belonging to the same grammatical gender get treated the same grammatically. Languages can require speakers to change pronouns, adjective and verb endings, possessives, numerals, and so on, depending on the noun's gender. For example, to say something like "my chair was old" in Russian (moy stul bil' stariy), you'd need to make every word in the sentence agree in gender with "chair" (stul), which is masculine in Russian. So you'd use the masculine form of "my," "was," and "old." These are the same forms you'd use in speaking of a biological male, as in "my grandfather was old." If, instead of speaking of a chair, you were speaking of a bed (krovat'), which is feminine in Russian, or about your grandmother, you would use the feminine form of "my," "was," and "old."

there is one crucial difference between IQ and CQ scores. With intelligence, there is a phenomenon called the Flynn effect—each generation, scores go up about 10 points. Enriched environments are making kids smarter. With creativity, a reverse trend has just been identified and is being reported for the first time here: American creativity scores are falling.

creativity scores had been steadily rising, just like IQ scores, until 1990. Since then, creativity scores have consistently inched downward.

It is the scores of younger children in America—from kindergarten through sixth grade—for whom the decline is “most serious.”

It’s too early to determine conclusively why U.S. creativity scores are declining. One likely culprit is the number of hours kids now spend in front of the TV and playing videogames rather than engaging in creative activities. Another is the lack of creativity development in our schools. In effect, it’s left to the luck of the draw who becomes creative: there’s no concerted effort to nurture the creativity of all children.

Around the world, though, other countries are making creativity development a national priority.

In China there has been widespread education reform to extinguish the drill-and-kill teaching style. Instead, Chinese schools are also adopting a problem-based learning approach.

When faculty of a major Chinese university asked Plucker to identify trends in American education, he described our focus on standardized curriculum, rote memorization, and nationalized testing.

Overwhelmed by curriculum standards, American teachers warn there’s no room in the day for a creativity class.

The age-old belief that the arts have a special claim to creativity is unfounded. When scholars gave creativity tasks to both engineering majors and music majors, their scores laid down on an identical spectrum, with the same high averages and standard deviations.

The argument that we can’t teach creativity because kids already have too much to learn is a false trade-off. Creativity isn’t about freedom from concrete facts. Rather, fact-finding and deep research are vital stages in the creative process.

The lore of pop psychology is that creativity occurs on the right side of the brain. But we now know that if you tried to be creative using only the right side of your brain, it’d be like living with ideas perpetually at the tip of your tongue, just beyond reach.

Creativity requires constant shifting, blender pulses of both divergent thinking and convergent thinking, to combine new information with old and forgotten ideas. Highly creative people are very good at marshaling their brains into bilateral mode, and the more creative they are, the more they dual-activate.

“Creativity can be taught,” says James C. Kaufman, professor at California State University, San Bernardino. What’s common about successful programs is they alternate maximum divergent thinking with bouts of intense convergent thinking, through several stages. Real improvement doesn’t happen in a weekend workshop. But when applied to the everyday process of work or school, brain function improves.

highly creative adults tended to grow up in families embodying opposites. Parents encouraged uniqueness, yet provided stability. They were highly responsive to kids’ needs, yet challenged kids to develop skills. This resulted in a sort of adaptability: in times of anxiousness, clear rules could reduce chaos—yet when kids were bored, they could seek change, too. In the space between anxiety and boredom was where creativity flourished.

highly creative adults frequently grew up with hardship. Hardship by itself doesn’t lead to creativity, but it does force kids to become more flexible—and flexibility helps with creativity.

In early childhood, distinct types of free play are associated with high creativity. Preschoolers who spend more time in role-play (acting out characters) have higher measures of creativity: voicing someone else’s point of view helps develop their ability to analyze situations from different perspectives. When playing alone, highly creative first graders may act out strong negative emotions: they’ll be angry, hostile, anguished.

In middle childhood, kids sometimes create paracosms—fantasies of entire alternative worlds. Kids revisit their paracosms repeatedly, sometimes for months, and even create languages spoken there. This type of play peaks at age 9 or 10, and it’s a very strong sign of future creativity.

From fourth grade on, creativity no longer occurs in a vacuum; researching and studying become an integral part of coming up with useful solutions. But this transition isn’t easy. As school stuffs more complex information into their heads, kids get overloaded, and creativity suffers. When creative children have a supportive teacher—someone tolerant of unconventional answers, occasional disruptions, or detours of curiosity—they tend to excel. When they don’t, they tend to underperform and drop out of high school or don’t finish college at high rates.

They’re quitting because they’re discouraged and bored, not because they’re dark, depressed, anxious, or neurotic. It’s a myth that creative people have these traits. (Those traits actually shut down creativity; they make people less open to experience and less interested in novelty.) Rather, creative people, for the most part, exhibit active moods and positive affect. They’re not particularly happy—contentment is a kind of complacency creative people rarely have. But they’re engaged, motivated, and open to the world.

A similar study of 1,500 middle schoolers found that those high in creative self-efficacy had more confidence about their future and ability to succeed. They were sure that their ability to come up with alternatives would aid them, no matter what problems would arise.

In his final book, Power and Prosperity, the late Mancur Olson argued that the state was a “stationary bandit”. A stationary bandit is better than a “roving bandit”, because the latter has no interest in developing the economy, while the former does. But it may not be much better, because those who control the state will seek to extract the surplus over subsistence generated by those under their control.

In the contemporary west, there are three protections against undue exploitation by the stationary bandit: exit, voice (on the first two of these, see this on Albert Hirschman) and restraint. By “exit”, I mean the possibility of escaping from the control of a given jurisdiction, by emigration, capital flight or some form of market exchange. By “voice”, I mean a degree of control over, the state, most obviously by voting. By “restraint”, I mean independent courts, division of powers, federalism and entrenched rights.

defining what a democratic state, viewed precisely as such a constrained protective arrangement, is entitled to do.

There exists a strand in classical liberal or, in contemporary US parlance, libertarian thought which believes the answer is to define the role of the state so narrowly and the rights of individuals so broadly that many political choices (the income tax or universal health care, for example) would be ruled out a priori. In other words, it seeks to abolish much of politics through constitutional restraints. I view this as a hopeless strategy, both intellectually and politically. It is hopeless intellectually, because the values people hold are many and divergent and some of these values do not merely allow, but demand, government protection of weak, vulnerable or unfortunate people. Moreover, such values are not “wrong”. The reality is that people hold many, often incompatible, core values. Libertarians argue that the only relevant wrong is coercion by the state. Others disagree and are entitled to do so. It is hopeless politically, because democracy necessitates debate among widely divergent opinions. Trying to rule out a vast range of values from the political sphere by constitutional means will fail. Under enough pressure, the constitution itself will be changed, via amendment or reinterpretation.

So what ought the protective role of the state to include? Again, in such a discussion, classical liberals would argue for the “night-watchman” role. The government’s responsibilities are limited to protecting individuals from coercion, fraud and theft and to defending the country from foreign aggression. Yet once one has accepted the legitimacy of using coercion (taxation) to provide the goods listed above, there is no reason in principle why one should not accept it for the provision of other goods that cannot be provided as well, or at all, by non-political means.

Those other measures would include addressing a range of externalities (e.g. pollution), providing information and supplying insurance against otherwise uninsurable risks, such as unemployment, spousal abandonment and so forth. The subsidisation or public provision of childcare and education is a way to promote equality of opportunity. The subsidisation or public provision of health insurance is a way to preserve life, unquestionably one of the purposes of the state. Safety standards are a way to protect people against the carelessness or malevolence of others or (more controversially) themselves. All these, then, are legitimate protective measures. The more complex the society and economy, the greater the range of the protections that will be sought.

What, then, are the objections to such actions? The answers might be: the proposed measures are ineffective, compared with what would happen in the absence of state intervention; the measures are unaffordable and might lead to state bankruptcy; the measures encourage irresponsible behaviour; and, at the limit, the measures restrict individual autonomy to an unacceptable degree. These are all, we should note, questions of consequences.

The vote is more evenly distributed than wealth and income. Thus, one would expect the tenor of democratic policymaking to be redistributive and so, indeed, it is. Those with wealth and income to protect will then make political power expensive to acquire and encourage potential supporters to focus on common enemies (inside and outside the country) and on cultural values. The more unequal are incomes and wealth and the more determined are the “haves” to avoid being compelled to support the “have-nots”, the more politics will take on such characteristics.

In the 1970s, the view that democracy would collapse under the weight of its excessive promises seemed to me disturbingly true. I am no longer convinced of this: as Adam Smith said, “There is a great deal of ruin in a nation”. Moreover, the capacity for learning by democracies is greater than I had realised. The conservative movements of the 1980s were part of that learning. But they went too far in their confidence in market arrangements and their indifference to the social and political consequences of inequality. I would support state pensions, state-funded health insurance and state regulation of environmental and other externalities. I am happy to debate details. The ancient Athenians called someone who had a purely private life “idiotes”. This is, of course, the origin of our word “idiot”. Individual liberty does indeed matter. But it is not the only thing that matters. The market is a remarkable social institution. But it is far from perfect. Democratic politics can be destructive. But it is much better than the alternatives. Each of us has an obligation, as a citizen, to make politics work as well as he (or she) can and to embrace the debate over a wide range of difficult choices that this entails.

Religious belief is a very different kind of thing. It is not restricted only to those with a certain education or knowledge, it does not require years of training, it is not specialized and it is not technical. (I’m talking here about the content of what people who regularly attend church, mosque or synagogue take themselves to be thinking; I’m not talking about how theologians interpret this content.)

while religious belief is widespread, scientific knowledge is not. I would guess that very few people in the world are actually interested in the details of contemporary scientific theories. Why? One obvious reason is that many lack access to this knowledge. Another reason is that even when they have access, these theories require sophisticated knowledge and abilities, which not everyone is capable of getting.

most people aren’t deeply interested in science, even when they have the opportunity and the basic intellectual capacity to learn about it. Of course, educated people who know about science know roughly what Einstein, Newton and Darwin said. Many educated people accept the modern scientific view of the world and understand its main outlines. But this is not the same as being interested in the details of science, or being immersed in scientific thinking.

This lack of interest in science contrasts sharply with the worldwide interest in religion. It’s hard to say whether religion is in decline or growing, partly because it’s hard to identify only one thing as religion — not a question I can address here. But it’s pretty obvious that whatever it is, religion commands and absorbs the passions and intellects of hundreds of millions of people, many more people than science does. Why is this? Is it because — as the new atheists might argue — they want to explain the world in a scientific kind of way, but since they have not been properly educated they haven’t quite got there yet? Or is it because so many people are incurably irrational and are incapable of scientific thinking? Or is something else going on?

Some philosophers have said that religion is so unlike science that it has its own “grammar” or “logic” and should not be held accountable to the same standards as scientific or ordinary empirical belief. When Christians express their belief that “Christ has risen,” for example, they should not be taken as making a factual claim, but as expressing their commitment to what Wittgenstein called a certain “form of life,” a way of seeing significance in the world, a moral and practical outlook which is worlds away from scientific explanation.

This view has some merits, as we shall see, but it grossly misrepresents some central phenomena of religion. It is absolutely essential to religions that they make certain factual or historical claims. When Saint Paul says “if Christ is not risen, then our preaching is in vain and our faith is in vain” he is saying that the point of his faith depends on a certain historical occurrence.

Theologians will debate exactly what it means to claim that Christ has risen, what exactly the meaning and significance of this occurrence is, and will give more or less sophisticated accounts of it. But all I am saying is that whatever its specific nature, Christians must hold that there was such an occurrence. Christianity does make factual, historical claims. But this is not the same as being a kind of proto-science. This will become clear if we reflect a bit on what science involves.

The essence of science involves making hypotheses about the causes and natures of things, in order to explain the phenomena we observe around us, and to predict their future behavior. Some sciences — medical science, for example — make hypotheses about the causes of diseases and test them by intervening. Others — cosmology, for example — make hypotheses that are more remote from everyday causes, and involve a high level of mathematical abstraction and idealization. Scientific reasoning involves an obligation to hold a hypothesis only to the extent that the evidence requires it. Scientists should not accept hypotheses which are “ad hoc” — that is, just tailored for one specific situation but cannot be generalized to others. Most scientific theories involve some kind of generalization: they don’t just make claims about one thing, but about things of a general kind. And their hypotheses are designed, on the whole, to make predictions; and if these predictions don’t come out true, then this is something for the scientists to worry about.

Religions do not construct hypotheses in this sense. I said above that Christianity rests upon certain historical claims, like the claim of the resurrection. But this is not enough to make scientific hypotheses central to Christianity, any more than it makes such hypotheses central to history. It is true, as I have just said, that Christianity does place certain historical events at the heart of their conception of the world, and to that extent, one cannot be a Christian unless one believes that these events happened. Speaking for myself, it is because I reject the factual basis of the central Christian doctrines that I consider myself an atheist. But I do not reject these claims because I think they are bad hypotheses in the scientific sense. Not all factual claims are scientific hypotheses. So I disagree with Richard Dawkins when he says “religions make existence claims, and this means scientific claims.”

Taken as hypotheses, religious claims do very badly: they are ad hoc, they are arbitrary, they rarely make predictions and when they do they almost never come true. Yet the striking fact is that it does not worry Christians when this happens. In the gospels Jesus predicts the end of the world and the coming of the kingdom of God. It does not worry believers that Jesus was wrong (even if it causes theologians to reinterpret what is meant by ‘the kingdom of God’). If Jesus was framing something like a scientific hypothesis, then it should worry them. Critics of religion might say that this just shows the manifest irrationality of religion. But what it suggests to me is that that something else is going on, other than hypothesis formation.

Religious belief tolerates a high degree of mystery and ignorance in its understanding of the world. When the devout pray, and their prayers are not answered, they do not take this as evidence which has to be weighed alongside all the other evidence that prayer is effective. They feel no obligation whatsoever to weigh the evidence. If God does not answer their prayers, well, there must be some explanation of this, even though we may never know it. Why do people suffer if an omnipotent God loves them? Many complex answers have been offered, but in the end they come down to this: it’s a mystery.

Science too has its share of mysteries (or rather: things that must simply be accepted without further explanation). But one aim of science is to minimize such things, to reduce the number of primitive concepts or primitive explanations. The religious attitude is very different. It does not seek to minimize mystery. Mysteries are accepted as a consequence of what, for the religious, makes the world meaningful.

Religion is an attempt to make sense of the world, but it does not try and do this in the way science does. Science makes sense of the world by showing how things conform to its hypotheses. The characteristic mode of scientific explanation is showing how events fit into a general pattern.

Religion, on the other hand, attempts to make sense of the world by seeing a kind of meaning or significance in things. This kind of significance does not need laws or generalizations, but just the sense that the everyday world we experience is not all there is, and that behind it all is the mystery of God’s presence. The believer is already convinced that God is present in everything, even if they cannot explain this or support it with evidence. But it makes sense of their life by suffusing it with meaning. This is the attitude (seeing God in everything) expressed in George Herbert’s poem, “The Elixir.” Equipped with this attitude, even the most miserable tasks can come to have value: Who sweeps a room as for Thy laws/ Makes that and th’ action fine.

None of these remarks are intended as being for or against religion. Rather, they are part of an attempt (by an atheist, from the outside) to understand what it is. Those who criticize religion should have an accurate understanding of what it is they are criticizing. But to understand a world view, or a philosophy or system of thought, it is not enough just to understand the propositions it contains. You also have to understand what is central and what is peripheral to the view. Religions do make factual and historical claims, and if these claims are false, then the religions fail. But this dependence on fact does not make religious claims anything like hypotheses in the scientific sense. Hypotheses are not central. Rather, what is central is the commitment to the meaningfulness (and therefore the mystery) of the world.

while religious thinking is widespread in the world, scientific thinking is not. I don’t think that this can be accounted for merely in terms of the ignorance or irrationality of human beings. Rather, it is because of the kind of intellectual, emotional and practical appeal that religion has for people, which is a very different appeal from the kind of appeal that science has. Stephen Jay Gould once argued that religion and science are “non-overlapping magisteria.” If he meant by this that religion makes no factual claims which can be refuted by empirical investigations, then he was wrong. But if he meant that religion and science are very different kinds of attempt to understand the world, then he was certainly right.

first question we can reasonably ask is whether all moral systems are indeed focused on benefiting human happiness and decreasing pain.

Jeremy Bentham, the founder of utilitarianism, wrote the following in his Introduction to the Principles of Morals and Legislation: “When a man attempts to combat the principle of utility, it is with reasons drawn, without his being aware of it, from that very principle itself.”

Michael Sandel discusses this line of thought in his excellent book, Justice: What’s the Right Thing to Do?, and sums up Bentham’s argument as such: “All moral quarrels, properly understood, are [for Bentham] disagreements about how to apply the utilitarian principle of maximizing pleasure and minimizing pain, not about the principle itself.”

But Bentham’s definition of utilitarianism is perhaps too broad: are fundamentalist Christians or Muslims really utilitarians, just with different ideas about how to facilitate human flourishing?

one wonders whether this makes the word so all-encompassing in meaning as to render it useless.

Yet, even if pain and happiness are the objects of moral concern, so what? As philosopher Simon Blackburn recently pointed out, “Every moral philosopher knows that moral philosophy is functionally about reducing suffering and increasing human flourishing.” But is that the central and sole focus of all moral philosophies? Don’t moral systems vary in their core focuses?

Consider the observation that religious belief makes humans happier, on average

Secularists would rightly resist the idea that religious belief is moral if it makes people happier. They would reject the very idea because deep down, they value truth – a value that is non-negotiable.Utilitarians would assert that truth is just another utility, for people can only value truth if they take it to be beneficial to human happiness and flourishing.

. We might all agree that morality is “functionally about reducing suffering and increasing human flourishing,” as Blackburn says, but how do we achieve that? Consequentialism posits that we can get there by weighing the consequences of beliefs and actions as they relate to human happiness and pain. Sam Harris recently wrote: “It is true that many people believe that ‘there are non-consequentialist ways of approaching morality,’ but I think that they are wrong. In my experience, when you scratch the surface on any deontologist, you find a consequentialist just waiting to get out. For instance, I think that Kant's Categorical Imperative only qualifies as a rational standard of morality given the assumption that it will be generally beneficial (as J.S. Mill pointed out at the beginning of Utilitarianism). Ditto for religious morality.”

we might wonder about the elasticity of words, in this case consequentialism. Do fundamentalist Christians and Muslims count as consequentialists? Is consequentialism so empty of content that to be a consequentialist one need only think he or she is benefiting humanity in some way?

Harris’ argument is that one cannot adhere to a certain conception of morality without believing it is beneficial to society

This still seems somewhat obvious to me as a general statement about morality, but is it really the point of consequentialism? Not really. Consequentialism is much more focused than that. Consider the issue of corporal punishment in schools. Harris has stated that we would be forced to admit that corporal punishment is moral if studies showed that “subjecting children to ‘pain, violence, and public humiliation’ leads to ‘healthy emotional development and good behavior’ (i.e., it conduces to their general well-being and to the well-being of society). If it did, well then yes, I would admit that it was moral. In fact, it would appear moral to more or less everyone.” Harris is being rhetorical – he does not believe corporal punishment is moral – but the point stands.

An immediate pitfall of this approach is that it does not qualify corporal punishment as the best way to raise emotionally healthy children who behave well.

The virtue ethicists inside us would argue that we ought not to foster a society in which people beat and humiliate children, never mind the consequences. There is also a reasonable and powerful argument based on personal freedom. Don’t children have the right to be free from violence in the public classroom? Don’t children have the right not to suffer intentional harm without consent? Isn’t that part of their “moral well-being”?

If consequences were really at the heart of all our moral deliberations, we might live in a very different society.

what if economies based on slavery lead to an increase in general happiness and flourishing for their respective societies? Would we admit slavery was moral? I hope not, because we value certain ideas about human rights and freedom. Or, what if the death penalty truly deterred crime? And what if we knew everyone we killed was guilty as charged, meaning no need for The Innocence Project? I would still object, on the grounds that it is morally wrong for us to kill people, even if they have committed the crime of which they are accused. Certain things hold, no matter the consequences.

We all do care about increasing human happiness and flourishing, and decreasing pain and suffering, and we all do care about the consequences of our beliefs and actions. But we focus on those criteria to differing degrees, and we have differing conceptions of how to achieve the respective goals – making us perhaps utilitarians and consequentialists in part, but not in whole.

Sampling based on profiling is mathematically no more effective than uniform random sampling. The optimal equation, rather, turns out to be something called “square-root sampling,” a compromise between the other two methods.

“Crudely,” Press writes of his findings in the journal Significance, if certain people are “nine times as likely to be the terrorist, we pull out only three times as many of them for special checks. Surprisingly, and bizarrely, this turns out to be the most efficient way of catching the terrorist.”

Square-root sampling, though, still represents a kind of profiling, and, Press adds, not one that could be realistically implemented at airports today. Square-root sampling only works if the profile probabilities are accurate in the first place — if we are able to say with mathematical certainty that some types of people are “nine times as likely to be the terrorist” compared to others. TSA agents in a crowded holiday terminal making snap judgments about facial hair would be far from this standard. “The nice thing about uniform sampling is there’s nothing to be inaccurate about, you don’t need any data, it never can be worse than you expect,” Press said. “As soon as you use profile probabilities, if the profile probabilities are just wrong, then the strong profiling just does worse than the random sampling.”

However, a greater concern lies in the notion of climate change itself. Climate change is in essence one kind of nature-society relationship, in which humans influence the climate through greenhouse gas (particularly CO2) emissions, and the climate strikes back by heating up and going crazy at times. This can be further simplified into a battle between humans and CO2: reducing CO2 guards against climate change, and increasing it aggravates the consequences. This view is anchored in scientists’ recommendation that a ‘safe’ level of CO2 should be at 350 parts per million (ppm) instead of the current 390. Already, the need to reduce CO2 is understood, as is evident in the push for greener fuels, more efficient means of production, the proliferation of ‘green’ products and companies, and most recently, the Cancun talks.

So can there be anything wrong with reducing CO2? No, there isn’t, but singling out CO2 as the culprit of climate change or of the environmental problems we face prevents us from looking within. What do I mean? The enemy, CO2, is an ‘other’, an externality produced by our economic systems but never an inherent component of the systems. Thus, we can declare war on the gas or on climate change without taking a step back and questioning: is there anything wrong with the way we develop?  Take Singapore for example: the government pledged to reduce carbon emissions by 16% under ‘business as usual’ standards, which says nothing about how ‘business’ is going to be changed other than having less carbon emissions (in fact, it is questionable even that CO2 levels will decrease, as ‘business as usual’ standards project a steady increase emission of CO2 each year). With the development of green technologies, decrease in carbon emissions will mainly be brought about by increased energy efficiency and switch to alternative fuels (including the insidious nuclear energy).

Thus, the way we develop will hardly be changed. Nobody questions whether our neoliberal system of development, which relies heavily on consumption to drive economies, needs to be looked into. We assume that it is the right way to develop, and only tweak it for the amount of externalities produced. Whether or not we should be measuring development by the Gross Domestic Product (GDP) or if welfare is correlated to the amount of goods and services consumed is never considered. Even the UN-REDD (Reducing Emissions from Deforestation and Forest Degradation) scheme which aims to pay forest-rich countries for protecting their forests, ends up putting a price tag on them. The environment is being subsumed under the economy, when it should be that the economy is re-looked to take the environment into consideration.

when the world is celebrating after having held at bay the dangerous greenhouse gas, why would anyone bother rethinking about the economy? Yet we should, simply because there are alternative nature-society relationships and discourses about nature that are more or of equal importance as global warming. Annie Leonard’s informative videos on The Story of Stuff and specific products like electronics, bottled water and cosmetics shed light on the dangers of our ‘throw-away culture’ on the planet and poorer countries. What if the enemy was instead consumerism? Doing so would force countries (especially richer ones) to fundamentally question the nature of development, instead of just applying a quick technological fix. This is so much more difficult (and less economically viable), alongside other issues like environmental injustices – e.g. pollution or dumping of waste by Trans-National Corporations in poorer countries and removal of indigenous land rights. It is no wonder that we choose to disregard internal problems and focus instead on an external enemy; when CO2 is the culprit, the solution is too simple and detached from the communities that are affected by changes in their environment.

We need hence to allow for a greater politics of the environment. What I am proposing is not to diminish our action to reduce carbon emissions, for I do believe that it is part of the environmental problem that we are facing. What instead should be done is to reduce our fixation on CO2 as the main or only driver of climate change, and of climate change as the most pertinent nature-society issue we are facing. We should understand that there are many other ways of thinking about the environment; ‘developing’ countries, for example, tend to have a closer relationship with their environment – it is not something ‘out there’ but constantly interacted with for food, water, regulating services and cultural value. Their views and the impact of the socio-economic forces (often from TNCs and multi-lateral organizations like IMF) that shape the environment must also be taken into account, as do alternative meanings of sustainable development. Thus, even as we pat ourselves on the back for having achieved something significant at Cancun, our action should not and must not end there. Even if climate change hogs the headlines now, we must embrace more plurality in environmental discourse, for nature is not and never so simple as climate change alone. And hopefully sometime in the future, alongside a multi-lateral conference on climate change, the world can have one which rethinks the meaning of development.

this third group – the science deniers – started out in the naive group, and then were so scandalized by the realization that science is a messy human endeavor that the leap right to the nihilistic conclusion that science must therefore be bunk.

The article by Lehrer falls generally into this third category. He is discussing what has been called “the decline effect” – the fact that effect sizes in scientific studies tend to decrease over time, sometime to nothing.

This term was first applied to the parapsychological literature, and was in fact proposed as a real phenomena of ESP – that ESP effects literally decline over time. Skeptics have criticized this view as magical thinking and hopelessly naive – Occam’s razor favors the conclusion that it is the flawed measurement of ESP, not ESP itself, that is declining over time. 

Lehrer, however, applies this idea to all of science, not just parapsychology. He writes: And this is why the decline effect is so troubling. Not because it reveals the human fallibility of science, in which data are tweaked and beliefs shape perceptions. (Such shortcomings aren’t surprising, at least for scientists.) And not because it reveals that many of our most exciting theories are fleeting fads and will soon be rejected. (That idea has been around since Thomas Kuhn.) The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that’s often not the case. Just because an idea is true doesn’t mean it can be proved. And just because an idea can be proved doesn’t mean it’s true. When the experiments are done, we still have to choose what to believe.

Lehrer is ultimately referring to aspects of science that skeptics have been pointing out for years (as a way of discerning science from pseudoscience), but Lehrer takes it to the nihilistic conclusion that it is difficult to prove anything, and that ultimately “we still have to choose what to believe.” Bollocks!

Lehrer is describing the cutting edge or the fringe of science, and then acting as if it applies all the way down to the core. I think the problem is that there is so much scientific knowledge that we take for granted – so much so that we forget it is knowledge that derived from the scientific method, and at one point was not known.

If the truth itself does not “wear off”, as the headline of Lehrer’s article provocatively states, then what is responsible for this decline effect?

it is no surprise that effect science in preliminary studies tend to be positive. This can be explained on the basis of experimenter bias – scientists want to find positive results, and initial experiments are often flawed or less than rigorous. It takes time to figure out how to rigorously study a question, and so early studies will tend not to control for all the necessary variables. There is further publication bias in which positive studies tend to be published more than negative studies.

Further, some preliminary research may be based upon chance observations – a false pattern based upon a quirky cluster of events. If these initial observations are used in the preliminary studies, then the statistical fluke will be carried forward. Later studies are then likely to exhibit a regression to the mean, or a return to more statistically likely results (which is exactly why you shouldn’t use initial data when replicating a result, but should use entirely fresh data – a mistake for which astrologers are infamous).

skeptics are frequently cautioning against new or preliminary scientific research. Don’t get excited by every new study touted in the lay press, or even by a university’s press release. Most new findings turn out to be wrong. In science, replication is king. Consensus and reliable conclusions are built upon multiple independent lines of evidence, replicated over time, all converging on one conclusion.

Lehrer does make some good points in his article, but they are points that skeptics are fond of making. In order to have a  mature and functional appreciation for the process and findings of science, it is necessary to understand how science works in the real world, as practiced by flawed scientists and scientific institutions. This is the skeptical message.

But at the same time reliable findings in science are possible, and happen frequently – when results can be replicated and when they fit into the expanding intricate weave of the picture of the natural world being generated by scientific investigation.

It’s not simply a matter of lifting the burden of toxic resentment or of immobilizing guilt, however beneficial that may be ethically and psychologically.  It is not a merely therapeutic matter, as though this were just about you.  Rather, when the requisite conditions are met, forgiveness is what a good person would seek because it expresses fundamental moral ideals.  These include ideals of spiritual growth and renewal; truth-telling; mutual respectful address; responsibility and respect; reconciliation and peace.

Are any wrongdoers unforgivable?  People who have committed heinous acts such as torture or child molestation are often cited as examples.  The question is not primarily about the psychological ability of the victim to forswear anger, but whether a wrongdoer can rightly be judged not-to-be-forgiven no matter what offender and victim say or do.  I do not see that a persuasive argument for that thesis can be made; there is no such thing as the unconditionally unforgivable.  For else we would be faced with the bizarre situation of declaring illegitimate the forgiveness reached by victim and perpetrator after each has taken every step one could possibly wish for.  The implication may distress you: Osama bin Laden, for example, is not unconditionally unforgivable for his role in the attacks of 9/11.  That being said, given the extent of the injury done by grave wrongs, their author may be rightly unforgiven for an appropriate period even if he or she has taken all reasonable steps.  There is no mathematically precise formula for determining when it is appropriate to forgive.

Delayed gratification illustrates the interaction between the two modes. The brain is attracted by immediate rewards, no matter what kind. However, when larger rewards are eventually going to become available, other parts of the brain come into play to override (sometimes) the immediate urge.

Greene's research shows that our automatic setting is "Kantian," meaning that our intuitive responses are deontological, rule driven. The manual setting, on the other hand, tends to be more utilitarian / consequentialist. Accordingly, the first mode involves emotional areas of the brain, the second one involves more cognitive areas.

The evidence comes from the (in)famous trolley dilemma and it's many variations.

when people refuse to intervene in the footbridge (as opposed to the lever) version of the dilemma, they do so because of a strong emotional response, which contradicts the otherwise utilitarian calculus they make when considering the lever version.

psychopaths turn out to be more utilitarian than normal subjects - presumably not because consequentialism is inherently pathological, but because their emotional responses are stunted. Mood also affects the results, with people exposed to comedy (to enhance mood), for instance, more likely to say that it is okay to push the guy off the footbridge.

In a more recent experiment, subjects were asked to say which action carried the better consequences, which made them feel worse, and which was overall morally acceptable. The idea was to separate the cognitive, emotional and integrative aspects of moral decision making. Predictably, activity in the amygdala correlated with deontological judgment, activity in more cognitive areas was associated with utilitarianism, and different brain regions became involved in integrating the two.

Another recent experiment used visual vs. verbal descriptions of moral dilemmas. Turns out that more visual people tend to behave emotionally / deontologically, while more verbal people are more utilitarian.

studies show that interfering with moral judgment by engaging subjects with a cognitive task slows down (though it does not reverse) utilitarian judgment, but has no effect on deontological judgment. Again, in agreement with the conclusion that the first type of modality is the result of cognition, the latter of emotion.

Nice to know, by the way, that when experimenters controlled for "real world expectations" that people have about trolleys, or when they used more realistic scenarios than trolleys and bridges, the results don't vary. In other words, trolley thought experiments are actually informative, contrary to popular criticisms.

What factors affect people's decision making in moral judgment? The main one is proximity, with people feeling much stronger obligations if they are present to the event posing the dilemma, or even relatively near (a disaster happens in a nearby country), as opposed to when they are far (a country on the other side of the world).

Greene's general conclusion is that neuroscience matters to ethics because it reveals the hidden mechanisms of human moral decision making. However, he says this is interesting to philosophers because it may lead to question ethical theories that are implicitly or explicitly based on such judgments. But neither philosophical deontology nor consequentialism are in fact based on common moral judgments, seems to me. They are the result of explicit analysis. (Though Greene raises the possibility that some philosophers engage in rationalizing, rather than reason, as in Kant's famously convoluted idea that masturbation is wrong because one is using oneself as a mean to an end...)

this is not to say that understanding moral decision making in humans isn't interesting or in fact even helpful in real life cases. An example of the latter is the common moral condemnation of incest, which is an emotional reaction that probably evolved to avoid genetically diseased offspring. It follows that science can tell us that three is nothing morally wrong in cases of incest when precautions have been taken to avoid pregnancy (and assuming psychological reactions are also accounted for). Greene puts this in terms of science helping us to transform difficult ought questions into easier ought questions.

But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology. In the field of medicine, the phenomenon seems extremely widespread, affecting not only antipsychotics but also therapies ranging from cardiac stents to Vitamin E and antidepressants: Davis has a forthcoming analysis demonstrating that the efficacy of antidepressants has gone down as much as threefold in recent decades.

the effect is especially troubling because of what it exposes about the scientific process. If replication is what separates the rigor of science from the squishiness of pseudoscience, where do we put all these rigorously validated findings that can no longer be proved? Which results should we believe? Francis Bacon, the early-modern philosopher and pioneer of the scientific method, once declared that experiments were essential, because they allowed us to “put nature to the question.” But it appears that nature often gives us different answers.

At first, he assumed that he’d made an error in experimental design or a statistical miscalculation. But he couldn’t find anything wrong with his research. He then concluded that his initial batch of research subjects must have been unusually susceptible to verbal overshadowing. (John Davis, similarly, has speculated that part of the drop-off in the effectiveness of antipsychotics can be attributed to using subjects who suffer from milder forms of psychosis which are less likely to show dramatic improvement.) “It wasn’t a very satisfying explanation,” Schooler says. “One of my mentors told me that my real mistake was trying to replicate my work. He told me doing that was just setting myself up for disappointment.”

In private, Schooler began referring to the problem as “cosmic habituation,” by analogy to the decrease in response that occurs when individuals habituate to particular stimuli. “Habituation is why you don’t notice the stuff that’s always there,” Schooler says. “It’s an inevitable process of adjustment, a ratcheting down of excitement. I started joking that it was like the cosmos was habituating to my ideas. I took it very personally.”

The most likely explanation for the decline is an obvious one: regression to the mean. As the experiment is repeated, that is, an early statistical fluke gets cancelled out. The extrasensory powers of Schooler’s subjects didn’t decline—they were simply an illusion that vanished over time. And yet Schooler has noticed that many of the data sets that end up declining seem statistically solid—that is, they contain enough data that any regression to the mean shouldn’t be dramatic. “These are the results that pass all the tests,” he says. “The odds of them being random are typically quite remote, like one in a million. This means that the decline effect should almost never happen. But it happens all the time!

this is why Schooler believes that the decline effect deserves more attention: its ubiquity seems to violate the laws of statistics. “Whenever I start talking about this, scientists get very nervous,” he says. “But I still want to know what happened to my results. Like most scientists, I assumed that it would get easier to document my effect over time. I’d get better at doing the experiments, at zeroing in on the conditions that produce verbal overshadowing. So why did the opposite happen? I’m convinced that we can use the tools of science to figure this out. First, though, we have to admit that we’ve got a problem.”

In 2001, Michael Jennions, a biologist at the Australian National University, set out to analyze “temporal trends” across a wide range of subjects in ecology and evolutionary biology. He looked at hundreds of papers and forty-four meta-analyses (that is, statistical syntheses of related studies), and discovered a consistent decline effect over time, as many of the theories seemed to fade into irrelevance. In fact, even when numerous variables were controlled for—Jennions knew, for instance, that the same author might publish several critical papers, which could distort his analysis—there was still a significant decrease in the validity of the hypothesis, often within a year of publication. Jennions admits that his findings are troubling, but expresses a reluctance to talk about them publicly. “This is a very sensitive issue for scientists,” he says. “You know, we’re supposed to be dealing with hard facts, the stuff that’s supposed to stand the test of time. But when you see these trends you become a little more skeptical of things.”

the worst part was that when I submitted these null results I had difficulty getting them published. The journals only wanted confirming data. It was too exciting an idea to disprove, at least back then.

the steep rise and slow fall of fluctuating asymmetry is a clear example of a scientific paradigm, one of those intellectual fads that both guide and constrain research: after a new paradigm is proposed, the peer-review process is tilted toward positive results. But then, after a few years, the academic incentives shift—the paradigm has become entrenched—so that the most notable results are now those that disprove the theory.

Jennions, similarly, argues that the decline effect is largely a product of publication bias, or the tendency of scientists and scientific journals to prefer positive data over null results, which is what happens when no effect is found. The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for. A “significant” result is defined as any data point that would be produced by chance less than five per cent of the time. This ubiquitous test was invented in 1922 by the English mathematician Ronald Fisher, who picked five per cent as the boundary line, somewhat arbitrarily, because it made pencil and slide-rule calculations easier. Sterling saw that if ninety-seven per cent of psychology studies were proving their hypotheses, either psychologists were extraordinarily lucky or they published only the outcomes of successful experiments. In recent years, publication bias has mostly been seen as a problem for clinical trials, since pharmaceutical companies are less interested in publishing results that aren’t favorable. But it’s becoming increasingly clear that publication bias also produces major distortions in fields without large corporate incentives, such as psychology and ecology.

While publication bias almost certainly plays a role in the decline effect, it remains an incomplete explanation. For one thing, it fails to account for the initial prevalence of positive results among studies that never even get submitted to journals. It also fails to explain the experience of people like Schooler, who have been unable to replicate their initial data despite their best efforts

an equally significant issue is the selective reporting of results—the data that scientists choose to document in the first place. Palmer’s most convincing evidence relies on a statistical tool known as a funnel graph. When a large number of studies have been done on a single subject, the data should follow a pattern: studies with a large sample size should all cluster around a common value—the true result—whereas those with a smaller sample size should exhibit a random scattering, since they’re subject to greater sampling error. This pattern gives the graph its name, since the distribution resembles a funnel.

The funnel graph visually captures the distortions of selective reporting. For instance, after Palmer plotted every study of fluctuating asymmetry, he noticed that the distribution of results with smaller sample sizes wasn’t random at all but instead skewed heavily toward positive results.

Palmer has since documented a similar problem in several other contested subject areas. “Once I realized that selective reporting is everywhere in science, I got quite depressed,” Palmer told me. “As a researcher, you’re always aware that there might be some nonrandom patterns, but I had no idea how widespread it is.” In a recent review article, Palmer summarized the impact of selective reporting on his field: “We cannot escape the troubling conclusion that some—perhaps many—cherished generalities are at best exaggerated in their biological significance and at worst a collective illusion nurtured by strong a-priori beliefs often repeated.”

Palmer emphasizes that selective reporting is not the same as scientific fraud. Rather, the problem seems to be one of subtle omissions and unconscious misperceptions, as researchers struggle to make sense of their results. Stephen Jay Gould referred to this as the “shoehorning” process. “A lot of scientific measurement is really hard,” Simmons told me. “If you’re talking about fluctuating asymmetry, then it’s a matter of minuscule differences between the right and left sides of an animal. It’s millimetres of a tail feather. And so maybe a researcher knows that he’s measuring a good male”—an animal that has successfully mated—“and he knows that it’s supposed to be symmetrical. Well, that act of measurement is going to be vulnerable to all sorts of perception biases. That’s not a cynical statement. That’s just the way human beings work.”

One of the classic examples of selective reporting concerns the testing of acupuncture in different countries. While acupuncture is widely accepted as a medical treatment in various Asian countries, its use is much more contested in the West. These cultural differences have profoundly influenced the results of clinical trials. Between 1966 and 1995, there were forty-seven studies of acupuncture in China, Taiwan, and Japan, and every single trial concluded that acupuncture was an effective treatment. During the same period, there were ninety-four clinical trials of acupuncture in the United States, Sweden, and the U.K., and only fifty-six per cent of these studies found any therapeutic benefits. As Palmer notes, this wide discrepancy suggests that scientists find ways to confirm their preferred hypothesis, disregarding what they don’t want to see. Our beliefs are a form of blindness.

John Ioannidis, an epidemiologist at Stanford University, argues that such distortions are a serious issue in biomedical research. “These exaggerations are why the decline has become so common,” he says. “It’d be really great if the initial studies gave us an accurate summary of things. But they don’t. And so what happens is we waste a lot of money treating millions of patients and doing lots of follow-up studies on other themes based on results that are misleading.”

In 2005, Ioannidis published an article in the Journal of the American Medical Association that looked at the forty-nine most cited clinical-research studies in three major medical journals. Forty-five of these studies reported positive results, suggesting that the intervention being tested was effective. Because most of these studies were randomized controlled trials—the “gold standard” of medical evidence—they tended to have a significant impact on clinical practice, and led to the spread of treatments such as hormone replacement therapy for menopausal women and daily low-dose aspirin to prevent heart attacks and strokes. Nevertheless, the data Ioannidis found were disturbing: of the thirty-four claims that had been subject to replication, forty-one per cent had either been directly contradicted or had their effect sizes significantly downgraded.

The situation is even worse when a subject is fashionable. In recent years, for instance, there have been hundreds of studies on the various genes that control the differences in disease risk between men and women. These findings have included everything from the mutations responsible for the increased risk of schizophrenia to the genes underlying hypertension. Ioannidis and his colleagues looked at four hundred and thirty-two of these claims. They quickly discovered that the vast majority had serious flaws. But the most troubling fact emerged when he looked at the test of replication: out of four hundred and thirty-two claims, only a single one was consistently replicable. “This doesn’t mean that none of these claims will turn out to be true,” he says. “But, given that most of them were done badly, I wouldn’t hold my breath.”

the main problem is that too many researchers engage in what he calls “significance chasing,” or finding ways to interpret the data so that it passes the statistical test of significance—the ninety-five-per-cent boundary invented by Ronald Fisher. “The scientists are so eager to pass this magical test that they start playing around with the numbers, trying to find anything that seems worthy,” Ioannidis says. In recent years, Ioannidis has become increasingly blunt about the pervasiveness of the problem. One of his most cited papers has a deliberately provocative title: “Why Most Published Research Findings Are False.”

The problem of selective reporting is rooted in a fundamental cognitive flaw, which is that we like proving ourselves right and hate being wrong. “It feels good to validate a hypothesis,” Ioannidis said. “It feels even better when you’ve got a financial interest in the idea or your career depends upon it. And that’s why, even after a claim has been systematically disproven”—he cites, for instance, the early work on hormone replacement therapy, or claims involving various vitamins—“you still see some stubborn researchers citing the first few studies that show a strong effect. They really want to believe that it’s true.”

scientists need to become more rigorous about data collection before they publish. “We’re wasting too much time chasing after bad studies and underpowered experiments,” he says. The current “obsession” with replicability distracts from the real problem, which is faulty design. He notes that nobody even tries to replicate most science papers—there are simply too many. (According to Nature, a third of all studies never even get cited, let alone repeated.)

Schooler recommends the establishment of an open-source database, in which researchers are required to outline their planned investigations and document all their results. “I think this would provide a huge increase in access to scientific work and give us a much better way to judge the quality of an experiment,” Schooler says. “It would help us finally deal with all these issues that the decline effect is exposing.”

Although such reforms would mitigate the dangers of publication bias and selective reporting, they still wouldn’t erase the decline effect. This is largely because scientific research will always be shadowed by a force that can’t be curbed, only contained: sheer randomness. Although little research has been done on the experimental dangers of chance and happenstance, the research that exists isn’t encouraging

John Crabbe, a neuroscientist at the Oregon Health and Science University, conducted an experiment that showed how unknowable chance events can skew tests of replicability. He performed a series of experiments on mouse behavior in three different science labs: in Albany, New York; Edmonton, Alberta; and Portland, Oregon. Before he conducted the experiments, he tried to standardize every variable he could think of. The same strains of mice were used in each lab, shipped on the same day from the same supplier. The animals were raised in the same kind of enclosure, with the same brand of sawdust bedding. They had been exposed to the same amount of incandescent light, were living with the same number of littermates, and were fed the exact same type of chow pellets. When the mice were handled, it was with the same kind of surgical glove, and when they were tested it was on the same equipment, at the same time in the morning.

The premise of this test of replicability, of course, is that each of the labs should have generated the same pattern of results. “If any set of experiments should have passed the test, it should have been ours,” Crabbe says. “But that’s not the way it turned out.” In one experiment, Crabbe injected a particular strain of mouse with cocaine. In Portland the mice given the drug moved, on average, six hundred centimetres more than they normally did; in Albany they moved seven hundred and one additional centimetres. But in the Edmonton lab they moved more than five thousand additional centimetres. Similar deviations were observed in a test of anxiety. Furthermore, these inconsistencies didn’t follow any detectable pattern. In Portland one strain of mouse proved most anxious, while in Albany another strain won that distinction.

The disturbing implication of the Crabbe study is that a lot of extraordinary scientific data are nothing but noise. The hyperactivity of those coked-up Edmonton mice wasn’t an interesting new fact—it was a meaningless outlier, a by-product of invisible variables we don’t understand. The problem, of course, is that such dramatic findings are also the most likely to get published in prestigious journals, since the data are both statistically significant and entirely unexpected. Grants get written, follow-up studies are conducted. The end result is a scientific accident that can take years to unravel.

This suggests that the decline effect is actually a decline of illusion.

While Karl Popper imagined falsification occurring with a single, definitive experiment—Galileo refuted Aristotelian mechanics in an afternoon—the process turns out to be much messier than that. Many scientific theories continue to be considered true even after failing numerous experimental tests. Verbal overshadowing might exhibit the decline effect, but it remains extensively relied upon within the field. The same holds for any number of phenomena, from the disappearing benefits of second-generation antipsychotics to the weak coupling ratio exhibited by decaying neutrons, which appears to have fallen by more than ten standard deviations between 1969 and 2001. Even the law of gravity hasn’t always been perfect at predicting real-world phenomena. (In one test, physicists measuring gravity by means of deep boreholes in the Nevada desert found a two-and-a-half-per-cent discrepancy between the theoretical predictions and the actual data.) Despite these findings, second-generation antipsychotics are still widely prescribed, and our model of the neutron hasn’t changed. The law of gravity remains the same.

Such anomalies demonstrate the slipperiness of empiricism. Although many scientific ideas generate conflicting results and suffer from falling effect sizes, they continue to get cited in the textbooks and drive standard medical practice. Why? Because these ideas seem true. Because they make sense. Because we can’t bear to let them go. And this is why the decline effect is so troubling. Not because it reveals the human fallibility of science, in which data are tweaked and beliefs shape perceptions. (Such shortcomings aren’t surprising, at least for scientists.) And not because it reveals that many of our most exciting theories are fleeting fads and will soon be rejected. (That idea has been around since Thomas Kuhn.) The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that’s often not the case. Just because an idea is true doesn’t mean it can be proved. And just because an idea can be proved doesn’t mean it’s true. When the experiments are done, we still have to choose what to believe.