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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.

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.

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.

To be sure, a differently designed experiment would have presented more difficulty for Collins. If he'd chosen questions that involved math, they would have done him in

But many scientists consider themselves perfectly qualified to discuss topics for which they lack the underlying mathematical skills, as Collins noted when I talked to him. "You can be a great physicist and not know any mathematics," he said.

So, if Collins can talk gravitational waves as well as an insider, who cares if he doesn't know how to crunch the numbers? Alan Sokal does. The New York University physicist is famous for an experiment a decade ago that seemed to demonstrate the futility of laymen discussing science. In 1996, he tricked the top humanities journal Social Text into publishing as genuine scholarship a totally nonsensical paper that celebrated fashionable literary theory and then applied it to all manner of scientific questions. ("As Lacan suspected, there is an intimate connection between the external structure of the physical world and its inner psychological representation qua knot theory.") Sokal showed that, with a little flattery, laymen could be induced to swallow the most ridiculous of scientific canards—so why should we value their opinions on science as highly as scientists'?

Sokal doesn't think Collins has proved otherwise. When I reached him this week, he acknowledged that you don't need to practice science in order to understand it. But he maintains, as he put it to Nature, that in many science debates, "you need a knowledge of the field that is virtually, if not fully, at the level of researchers in the field," in order to participate. He elaborated: Say there are two scientists, X and Y. If you want to argue that X's theory was embraced over Y's, even though Y's is better, because the science community is biased against Y, then you had better be able to read and evaluate their theories yourself, mathematics included (or collaborate with someone who can). He has a point. Just because mathematics features little in the work of some gravitational-wave physicists doesn't mean it's a trivial part of the subject.

Even if Collins didn't demonstrate that he is qualified to pronounce on all of gravitational-wave physics, he did learn more of the subject than anyone may have thought possible. Sokal says he was shocked by Collins' store of knowledge: "He knows more about gravitational waves than I do!" Sokal admitted that Collins was already qualified to pronounce on a lot, and that with a bit more study, he would be the equal of a professional.

More than 65% of the monsoon-influenced glaciers that we observed are retreating, but heavily debris-covered glaciers with stagnant low-gradient terminus regions typically have stable fronts. Debris-covered glaciers are common in the rugged central Himalaya, but they are almost absent in subdued landscapes on the Tibetan Plateau, where retreat rates are higher. In contrast, more than 50% of observed glaciers in the westerlies-influenced Karakoram region in the northwestern Himalaya are advancing or stable.

Our study shows that there is no uniform response of Himalayan glaciers to climate change and highlights the importance of debris cover for understanding glacier retreat, an effect that has so far been neglected in predictions of future water availability9, 10 or global sea level11.

"There is no 'stereotypical' Himalayan glacier," said Bookhagen. "This is in clear contrast to the IPCC reports that lumps all Himalayan glaciers together."

Bookhagen noted that glaciers in the Karakoram region of Northwestern Himalaya are mostly stagnating. However, glaciers in the Western, Central, and Eastern Himalaya are retreating, with the highest retreat rates -- approximately 8 meters per year -- in the Western Himalayan Mountains. The authors found that half of the studied glaciers in the Karakoram region are stable or advancing, whereas about two-thirds are in retreat elsewhere throughout High Asia. This is in contrast to the prevailing notion that all glaciers in the tropics are retreating.

debris cover has the opposite effect of soot and dust on glaciers. Debris coverage thickness above 2 centimeters, or about a half an inch, 'shields' the glacier and prevents melting. This is the case for many Himalayan glaciers that are surrounded by towering mountains that almost continuously shed pebbles, debris, and rocks onto the glacier.

glaciers in the steep Himalaya are not only affected by temperature and precipitation, but also by debris coverage, and have no uniform and less predictable response, explained the authors. The debris coverage may be one of the missing links to creating a more coherent picture of glacial behavior throughout all mountains. The scientists contrast this Himalayan glacial study with glaciers from the gently dipping, low-relief Tibetan Plateau that have no debris coverage. Those glaciers behave in a different way, and their frontal changes can be explained by temperature and precipitation changes.

So there are clearly two lessons to be learned here. The first is that the standard advice is good advice. If all best practices had been followed then none of this would have happened. Even if the SQL injection error was still present, it wouldn't have caused the cascade of failures that followed.

The second lesson, however, is that the standard advice isn't good enough. Even recognized security experts who should know better won't follow it. What hope does that leave for the rest of us?

If ideas of democracy and freedom emerged at the end of the printing-press era, it wasn’t by some technological logic but because of parallel inventions, like the ideas of limited government and religious tolerance, very hard won from history.

As Andrew Pettegree shows in his fine new study, “The Book in the Renaissance,” the mainstay of the printing revolution in seventeenth-century Europe was not dissident pamphlets but royal edicts, printed by the thousand: almost all the new media of that day were working, in essence, for kinglouis.gov.

Even later, full-fledged totalitarian societies didn’t burn books. They burned some books, while keeping the printing presses running off such quantities that by the mid-fifties Stalin was said to have more books in print than Agatha Christie.

Many of the more knowing Never-Betters turn for cheer not to messy history and mixed-up politics but to psychology—to the actual expansion of our minds.

The argument, advanced in Andy Clark’s “Supersizing the Mind” and in Robert K. Logan’s “The Sixth Language,” begins with the claim that cognition is not a little processing program that takes place inside your head, Robby the Robot style. It is a constant flow of information, memory, plans, and physical movements, in which as much thinking goes on out there as in here. If television produced the global village, the Internet produces the global psyche: everyone keyed in like a neuron, so that to the eyes of a watching Martian we are really part of a single planetary brain. Contraptions don’t change consciousness; contraptions are part of consciousness. We may not act better than we used to, but we sure think differently than we did.

Cognitive entanglement, after all, is the rule of life. My memories and my wife’s intermingle. When I can’t recall a name or a date, I don’t look it up; I just ask her. Our machines, in this way, become our substitute spouses and plug-in companions.

But, if cognitive entanglement exists, so does cognitive exasperation. Husbands and wives deny each other’s memories as much as they depend on them. That’s fine until it really counts (say, in divorce court). In a practical, immediate way, one sees the limits of the so-called “extended mind” clearly in the mob-made Wikipedia, the perfect product of that new vast, supersized cognition: when there’s easy agreement, it’s fine, and when there’s widespread disagreement on values or facts, as with, say, the origins of capitalism, it’s fine, too; you get both sides. The trouble comes when one side is right and the other side is wrong and doesn’t know it. The Shakespeare authorship page and the Shroud of Turin page are scenes of constant conflict and are packed with unreliable information. Creationists crowd cyberspace every bit as effectively as evolutionists, and extend their minds just as fully. Our trouble is not the over-all absence of smartness but the intractable power of pure stupidity, and no machine, or mind, seems extended enough to cure that.

Nicholas Carr, in “The Shallows,” William Powers, in “Hamlet’s BlackBerry,” and Sherry Turkle, in “Alone Together,” all bear intimate witness to a sense that the newfound land, the ever-present BlackBerry-and-instant-message world, is one whose price, paid in frayed nerves and lost reading hours and broken attention, is hardly worth the gains it gives us. “The medium does matter,” Carr has written. “As a technology, a book focuses our attention, isolates us from the myriad distractions that fill our everyday lives. A networked computer does precisely the opposite. It is designed to scatter our attention. . . . Knowing that the depth of our thought is tied directly to the intensity of our attentiveness, it’s hard not to conclude that as we adapt to the intellectual environment of the Net our thinking becomes shallower.

Carr is most concerned about the way the Internet breaks down our capacity for reflective thought.

Powers’s reflections are more family-centered and practical. He recounts, very touchingly, stories of family life broken up by the eternal consultation of smartphones and computer monitors

He then surveys seven Wise Men—Plato, Thoreau, Seneca, the usual gang—who have something to tell us about solitude and the virtues of inner space, all of it sound enough, though he tends to overlook the significant point that these worthies were not entirely in favor of the kinds of liberties that we now take for granted and that made the new dispensation possible.

Similarly, Nicholas Carr cites Martin Heidegger for having seen, in the mid-fifties, that new technologies would break the meditational space on which Western wisdoms depend. Since Heidegger had not long before walked straight out of his own meditational space into the arms of the Nazis, it’s hard to have much nostalgia for this version of the past. One feels the same doubts when Sherry Turkle, in “Alone Together,” her touching plaint about the destruction of the old intimacy-reading culture by the new remote-connection-Internet culture, cites studies that show a dramatic decline in empathy among college students, who apparently are “far less likely to say that it is valuable to put oneself in the place of others or to try and understand their feelings.” What is to be done?

Among Ever-Wasers, the Harvard historian Ann Blair may be the most ambitious. In her book “Too Much to Know: Managing Scholarly Information Before the Modern Age,” she makes the case that what we’re going through is like what others went through a very long while ago. Against the cartoon history of Shirky or Tooby, Blair argues that the sense of “information overload” was not the consequence of Gutenberg but already in place before printing began. She wants us to resist “trying to reduce the complex causal nexus behind the transition from Renaissance to Enlightenment to the impact of a technology or any particular set of ideas.” Anyway, the crucial revolution was not of print but of paper: “During the later Middle Ages a staggering growth in the production of manuscripts, facilitated by the use of paper, accompanied a great expansion of readers outside the monastic and scholastic contexts.” For that matter, our minds were altered less by books than by index slips. Activities that seem quite twenty-first century, she shows, began when people cut and pasted from one manuscript to another; made aggregated news in compendiums; passed around précis. “Early modern finding devices” were forced into existence: lists of authorities, lists of headings.

Everyone complained about what the new information technologies were doing to our minds. Everyone said that the flood of books produced a restless, fractured attention. Everyone complained that pamphlets and poems were breaking kids’ ability to concentrate, that big good handmade books were ignored, swept aside by printed works that, as Erasmus said, “are foolish, ignorant, malignant, libelous, mad.” The reader consulting a card catalogue in a library was living a revolution as momentous, and as disorienting, as our own.

The book index was the search engine of its era, and needed to be explained at length to puzzled researchers

That uniquely evil and necessary thing the comprehensive review of many different books on a related subject, with the necessary oversimplification of their ideas that it demanded, was already around in 1500, and already being accused of missing all the points. In the period when many of the big, classic books that we no longer have time to read were being written, the general complaint was that there wasn’t enough time to read big, classic books.

at any given moment, our most complicated machine will be taken as a model of human intelligence, and whatever media kids favor will be identified as the cause of our stupidity. When there were automatic looms, the mind was like an automatic loom; and, since young people in the loom period liked novels, it was the cheap novel that was degrading our minds. When there were telephone exchanges, the mind was like a telephone exchange, and, in the same period, since the nickelodeon reigned, moving pictures were making us dumb. When mainframe computers arrived and television was what kids liked, the mind was like a mainframe and television was the engine of our idiocy. Some machine is always showing us Mind; some entertainment derived from the machine is always showing us Non-Mind.

The Fiolas say they have health problems from the stress of the case. They say they've talked to dozens of lawyers but can't get one to sue the state, because of a cap on the amount they can recover. "It ruined my life, my wife's life and my family's life," he says. The Massachusetts attorney general's office, which charged Fiola, declined interview requests.