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His answer is that both utilitarianism and deontology inherited the ideas of right, wrong and duty from Christianity, but endeavored to do without Christianity’s own answers to those questions: the law is given by God and the duty is toward Him. Taylor says that Mill, Kant and the like simply absorbed the Christian concept of morality while rejecting its logical foundation (such as it was). As a result, utilitarians and deontologists alike keep talking about the right thing to do, or the good as if those concepts still make sense once we move to a secular worldview. Utilitarians substituted pain and pleasure for wrong and right respectively, and Kant thought that pure reason can arrive at moral universals. But of course neither utilitarians nor deontologist ever give us a reason why it would be irrational to simply decline to pursue actions that increase global pleasure and diminish global pain, or why it would be irrational for someone not to find the categorical imperative particularly compelling.

The situation — again according to Taylor — is dramatically different for virtue ethics. Yes, there too we find concepts like right and wrong and duty. But, for the ancient Greeks they had completely different meanings, which made perfect sense then and now, if we are not mislead by the use of those words in a different context. For the Greeks, an action was right if it was approved by one’s society, wrong if it wasn’t, and duty was to one’s polis. And they understood perfectly well that what was right (or wrong) in Athens may or may not be right (or wrong) in Sparta. And that an Athenian had a duty to Athens, but not to Sparta, and vice versa for a Spartan.

But wait a minute. Does that mean that Taylor is saying that virtue ethics was founded on moral relativism? That would be an extraordinary claim indeed, and he does not, in fact, make it. His point is a bit more subtle. He suggests that for the ancient Greeks ethics was not (principally) about right, wrong and duty. It was about happiness, understood in the broad sense of eudaimonia, the good or fulfilling life. Aristotle in particular wrote in his Ethics about both aspects: the practical ethics of one’s duty to one’s polis, and the universal (for human beings) concept of ethics as the pursuit of the good life. And make no mistake about it: for Aristotle the first aspect was relatively trivial and understood by everyone, it was the second one that represented the real challenge for the philosopher.

For instance, the Ethics is famous for Aristotle’s list of the virtues (see Table), and his idea that the right thing to do is to steer a middle course between extreme behaviors. But this part of his work, according to Taylor, refers only to the practical ways of being a good Athenian, not to the universal pursuit of eudaimonia. Vice of Deficiency Virtuous Mean Vice of Excess Cowardice Courage Rashness Insensibility Temperance Intemperance Illiberality Liberality Prodigality Pettiness Munificence Vulgarity Humble-mindedness High-mindedness Vaingloriness Want of Ambition Right Ambition Over-ambition Spiritlessness Good Temper Irascibility Surliness Friendly Civility Obsequiousness Ironical Depreciation Sincerity Boastfulness Boorishness Wittiness Buffoonery</t

How, then, is one to embark on the more difficult task of figuring out how to live a good life? For Aristotle eudaimonia meant the best kind of existence that a human being can achieve, which in turns means that we need to ask what it is that makes humans different from all other species, because it is the pursuit of excellence in that something that provides for a eudaimonic life.

Now, Plato - writing before Aristotle - ended up construing the good life somewhat narrowly and in a self-serving fashion. He reckoned that the thing that distinguishes humanity from the rest of the biological world is our ability to use reason, so that is what we should be pursuing as our highest goal in life. And of course nobody is better equipped than a philosopher for such an enterprise... Which reminds me of Bertrand Russell’s quip that “A process which led from the amoeba to man appeared to the philosophers to be obviously a progress, though whether the amoeba would agree with this opinion is not known.”

But Aristotle's conception of "reason" was significantly broader, and here is where Taylor’s own update of virtue ethics begins to shine, particularly in Chapter 16 of the book, aptly entitled “Happiness.” Taylor argues that the proper way to understand virtue ethics is as the quest for the use of intelligence in the broadest possible sense, in the sense of creativity applied to all walks of life. He says: “Creative intelligence is exhibited by a dancer, by athletes, by a chess player, and indeed in virtually any activity guided by intelligence [including — but certainly not limited to — philosophy].” He continues: “The exercise of skill in a profession, or in business, or even in such things as gardening and farming, or the rearing of a beautiful family, all such things are displays of creative intelligence.”

what we have now is a sharp distinction between utilitarianism and deontology on the one hand and virtue ethics on the other, where the first two are (mistakenly, in Taylor’s assessment) concerned with the impossible question of what is right or wrong, and what our duties are — questions inherited from religion but that in fact make no sense outside of a religious framework. Virtue ethics, instead, focuses on the two things that really matter and to which we can find answers: the practical pursuit of a life within our polis, and the lifelong quest of eudaimonia understood as the best exercise of our creative faculties

&gt; So if one's profession is that of assassin or torturer would being the best that you can be still be your duty and eudaimonic? And what about those poor blighters who end up with an ugly family? &lt;Aristotle's philosophy is ver much concerned with virtue, and being an assassin or a torturer is not a virtue, so the concept of a eudaimonic life for those characters is oxymoronic. As for ending up in a "ugly" family, Aristotle did write that eudaimonia is in part the result of luck, because it is affected by circumstances.

&gt; So to the title question of this post: "Is modern moral philosophy still in thrall to religion?" one should say: Yes, for some residual forms of philosophy and for some philosophers &lt;That misses Taylor's contention - which I find intriguing, though I have to give it more thought - that *all* modern moral philosophy, except virtue ethics, is in thrall to religion, without realizing it.

“The exercise of skill in a profession, or in business, or even in such things as gardening and farming, or the rearing of a beautiful family, all such things are displays of creative intelligence.”So if one's profession is that of assassin or torturer would being the best that you can be still be your duty and eudaimonic? And what about those poor blighters who end up with an ugly family?

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."

This is why, for example, large numbers of Americans oppose the idea of an estate tax even though the current form of the tax, slated to return in 2011, is very unlikely to affect them or their estates. In narrowly self-interested terms, that view may be irrational, but most Americans are unwilling to frame national issues in terms of rich versus poor. There’s a great deal of hostility toward various government bailouts, but the idea of “undeserving” recipients is the key factor in those feelings. Resentment against Wall Street gamesters hasn’t spilled over much into resentment against the wealthy more generally. The bailout for General Motors’ labor unions wasn’t so popular either—again, obviously not because of any bias against the wealthy but because a basic sense of fairness was violated. As of November 2010, congressional Democrats are of a mixed mind as to whether the Bush tax cuts should expire for those whose annual income exceeds $250,000; that is in large part because their constituents bear no animus toward rich people, only toward undeservedly rich people.

envy is usually local. At least in the United States, most economic resentment is not directed toward billionaires or high-roller financiers—not even corrupt ones. It’s directed at the guy down the hall who got a bigger raise. It’s directed at the husband of your wife’s sister, because the brand of beer he stocks costs $3 a case more than yours, and so on. That’s another reason why a lot of people aren’t so bothered by income or wealth inequality at the macro level. Most of us don’t compare ourselves to billionaires. Gore Vidal put it honestly: “Whenever a friend succeeds, a little something in me dies.”

Occasionally the cynic in me wonders why so many relatively well-off intellectuals lead the egalitarian charge against the privileges of the wealthy. One group has the status currency of money and the other has the status currency of intellect, so might they be competing for overall social regard? The high status of the wealthy in America, or for that matter the high status of celebrities, seems to bother our intellectual class most. That class composes a very small group, however, so the upshot is that growing income inequality won’t necessarily have major political implications at the macro level.

All that said, income inequality does matter—for both politics and the economy.

The numbers are clear: Income inequality has been rising in the United States, especially at the very top. The data show a big difference between two quite separate issues, namely income growth at the very top of the distribution and greater inequality throughout the distribution. The first trend is much more pronounced than the second, although the two are often confused.

When it comes to the first trend, the share of pre-tax income earned by the richest 1 percent of earners has increased from about 8 percent in 1974 to more than 18 percent in 2007. Furthermore, the richest 0.01 percent (the 15,000 or so richest families) had a share of less than 1 percent in 1974 but more than 6 percent of national income in 2007. As noted, those figures are from pre-tax income, so don’t look to the George W. Bush tax cuts to explain the pattern. Furthermore, these gains have been sustained and have evolved over many years, rather than coming in one or two small bursts between 1974 and today.1

At the same time, wage growth for the median earner has slowed since 1973. But that slower wage growth has afflicted large numbers of Americans, and it is conceptually distinct from the higher relative share of top income earners. For instance, if you take the 1979–2005 period, the average incomes of the bottom fifth of households increased only 6 percent while the incomes of the middle quintile rose by 21 percent. That’s a widening of the spread of incomes, but it’s not so drastic compared to the explosive gains at the very top.

The broader change in income distribution, the one occurring beneath the very top earners, can be deconstructed in a manner that makes nearly all of it look harmless. For instance, there is usually greater inequality of income among both older people and the more highly educated, if only because there is more time and more room for fortunes to vary. Since America is becoming both older and more highly educated, our measured income inequality will increase pretty much by demographic fiat. Economist Thomas Lemieux at the University of British Columbia estimates that these demographic effects explain three-quarters of the observed rise in income inequality for men, and even more for women.2

Attacking the problem from a different angle, other economists are challenging whether there is much growth in inequality at all below the super-rich. For instance, real incomes are measured using a common price index, yet poorer people are more likely to shop at discount outlets like Wal-Mart, which have seen big price drops over the past twenty years.3 Once we take this behavior into account, it is unclear whether the real income gaps between the poor and middle class have been widening much at all. Robert J. Gordon, an economist from Northwestern University who is hardly known as a right-wing apologist, wrote in a recent paper that “there was no increase of inequality after 1993 in the bottom 99 percent of the population”, and that whatever overall change there was “can be entirely explained by the behavior of income in the top 1 percent.”4

And so we come again to the gains of the top earners, clearly the big story told by the data. It’s worth noting that over this same period of time, inequality of work hours increased too. The top earners worked a lot more and most other Americans worked somewhat less. That’s another reason why high earners don’t occasion more resentment: Many people understand how hard they have to work to get there. It also seems that most of the income gains of the top earners were related to performance pay—bonuses, in other words—and not wildly out-of-whack yearly salaries.5

It is also the case that any society with a lot of “threshold earners” is likely to experience growing income inequality. A threshold earner is someone who seeks to earn a certain amount of money and no more. If wages go up, that person will respond by seeking less work or by working less hard or less often. That person simply wants to “get by” in terms of absolute earning power in order to experience other gains in the form of leisure—whether spending time with friends and family, walking in the woods and so on. Luck aside, that person’s income will never rise much above the threshold.

The funny thing is this: For years, many cultural critics in and of the United States have been telling us that Americans should behave more like threshold earners. We should be less harried, more interested in nurturing friendships, and more interested in the non-commercial sphere of life. That may well be good advice. Many studies suggest that above a certain level more money brings only marginal increments of happiness. What isn’t so widely advertised is that those same critics have basically been telling us, without realizing it, that we should be acting in such a manner as to increase measured income inequality. Not only is high inequality an inevitable concomitant of human diversity, but growing income inequality may be, too, if lots of us take the kind of advice that will make us happier.

Why is the top 1 percent doing so well?

Steven N. Kaplan and Joshua Rauh have recently provided a detailed estimation of particular American incomes.6 Their data do not comprise the entire U.S. population, but from partial financial records they find a very strong role for the financial sector in driving the trend toward income concentration at the top. For instance, for 2004, nonfinancial executives of publicly traded companies accounted for less than 6 percent of the top 0.01 percent income bracket. In that same year, the top 25 hedge fund managers combined appear to have earned more than all of the CEOs from the entire S&amp;P 500. The number of Wall Street investors earning more than $100 million a year was nine times higher than the public company executives earning that amount. The authors also relate that they shared their estimates with a former U.S. Secretary of the Treasury, one who also has a Wall Street background. He thought their estimates of earnings in the financial sector were, if anything, understated.

Many of the other high earners are also connected to finance. After Wall Street, Kaplan and Rauh identify the legal sector as a contributor to the growing spread in earnings at the top. Yet many high-earning lawyers are doing financial deals, so a lot of the income generated through legal activity is rooted in finance. Other lawyers are defending corporations against lawsuits, filing lawsuits or helping corporations deal with complex regulations. The returns to these activities are an artifact of the growing complexity of the law and government growth rather than a tale of markets per se. Finance aside, there isn’t much of a story of market failure here, even if we don’t find the results aesthetically appealing.

When it comes to professional athletes and celebrities, there isn’t much of a mystery as to what has happened. Tiger Woods earns much more, even adjusting for inflation, than Arnold Palmer ever did. J.K. Rowling, the first billionaire author, earns much more than did Charles Dickens. These high incomes come, on balance, from the greater reach of modern communications and marketing. Kids all over the world read about Harry Potter. There is more purchasing power to spend on children’s books and, indeed, on culture and celebrities more generally. For high-earning celebrities, hardly anyone finds these earnings so morally objectionable as to suggest that they be politically actionable. Cultural critics can complain that good schoolteachers earn too little, and they may be right, but that does not make celebrities into political targets. They’re too popular. It’s also pretty clear that most of them work hard to earn their money, by persuading fans to buy or otherwise support their product. Most of these individuals do not come from elite or extremely privileged backgrounds, either. They worked their way to the top, and even if Rowling is not an author for the ages, her books tapped into the spirit of their time in a special way. We may or may not wish to tax the wealthy, including wealthy celebrities, at higher rates, but there is no need to “cure” the structural causes of higher celebrity incomes.

to be sure, the high incomes in finance should give us all pause.

The first factor driving high returns is sometimes called by practitioners “going short on volatility.” Sometimes it is called “negative skewness.” In plain English, this means that some investors opt for a strategy of betting against big, unexpected moves in market prices. Most of the time investors will do well by this strategy, since big, unexpected moves are outliers by definition. Traders will earn above-average returns in good times. In bad times they won’t suffer fully when catastrophic returns come in, as sooner or later is bound to happen, because the downside of these bets is partly socialized onto the Treasury, the Federal Reserve and, of course, the taxpayers and the unemployed.

if you bet against unlikely events, most of the time you will look smart and have the money to validate the appearance. Periodically, however, you will look very bad. Does that kind of pattern sound familiar? It happens in finance, too. Betting against a big decline in home prices is analogous to betting against the Wizards. Every now and then such a bet will blow up in your face, though in most years that trading activity will generate above-average profits and big bonuses for the traders and CEOs.

To this mix we can add the fact that many money managers are investing other people’s money. If you plan to stay with an investment bank for ten years or less, most of the people playing this investing strategy will make out very well most of the time. Everyone’s time horizon is a bit limited and you will bring in some nice years of extra returns and reap nice bonuses. And let’s say the whole thing does blow up in your face? What’s the worst that can happen? Your bosses fire you, but you will still have millions in the bank and that MBA from Harvard or Wharton. For the people actually investing the money, there’s barely any downside risk other than having to quit the party early. Furthermore, if everyone else made more or less the same mistake (very surprising major events, such as a busted housing market, affect virtually everybody), you’re hardly disgraced. You might even get rehired at another investment bank, or maybe a hedge fund, within months or even weeks.

Moreover, smart shareholders will acquiesce to or even encourage these gambles. They gain on the upside, while the downside, past the point of bankruptcy, is borne by the firm’s creditors. And will the bondholders object? Well, they might have a difficult time monitoring the internal trading operations of financial institutions. Of course, the firm’s trading book cannot be open to competitors, and that means it cannot be open to bondholders (or even most shareholders) either. So what, exactly, will they have in hand to object to?

Perhaps more important, government bailouts minimize the damage to creditors on the downside. Neither the Treasury nor the Fed allowed creditors to take any losses from the collapse of the major banks during the financial crisis. The U.S. government guaranteed these loans, either explicitly or implicitly. Guaranteeing the debt also encourages equity holders to take more risk. While current bailouts have not in general maintained equity values, and while share prices have often fallen to near zero following the bust of a major bank, the bailouts still give the bank a lifeline. Instead of the bank being destroyed, sometimes those equity prices do climb back out of the hole. This is true of the major surviving banks in the United States, and even AIG is paying back its bailout. For better or worse, we’re handing out free options on recovery, and that encourages banks to take more risk in the first place.

there is an unholy dynamic of short-term trading and investing, backed up by bailouts and risk reduction from the government and the Federal Reserve. This is not good. “Going short on volatility” is a dangerous strategy from a social point of view. For one thing, in so-called normal times, the finance sector attracts a big chunk of the smartest, most hard-working and most talented individuals. That represents a huge human capital opportunity cost to society and the economy at large. But more immediate and more important, it means that banks take far too many risks and go way out on a limb, often in correlated fashion. When their bets turn sour, as they did in 2007–09, everyone else pays the price.

And it’s not just the taxpayer cost of the bailout that stings. The financial disruption ends up throwing a lot of people out of work down the economic food chain, often for long periods. Furthermore, the Federal Reserve System has recapitalized major U.S. banks by paying interest on bank reserves and by keeping an unusually high interest rate spread, which allows banks to borrow short from Treasury at near-zero rates and invest in other higher-yielding assets and earn back lots of money rather quickly. In essence, we’re allowing banks to earn their way back by arbitraging interest rate spreads against the U.S. government. This is rarely called a bailout and it doesn’t count as a normal budget item, but it is a bailout nonetheless. This type of implicit bailout brings high social costs by slowing down economic recovery (the interest rate spreads require tight monetary policy) and by redistributing income from the Treasury to the major banks.

the “going short on volatility” strategy increases income inequality. In normal years the financial sector is flush with cash and high earnings. In implosion years a lot of the losses are borne by other sectors of society. In other words, financial crisis begets income inequality. Despite being conceptually distinct phenomena, the political economy of income inequality is, in part, the political economy of finance. Simon Johnson tabulates the numbers nicely: From 1973 to 1985, the financial sector never earned more than 16 percent of domestic corporate profits. In 1986, that figure reached 19 percent. In the 1990s, it oscillated between 21 percent and 30 percent, higher than it had ever been in the postwar period. This decade, it reached 41 percent. Pay rose just as dramatically. From 1948 to 1982, average compensation in the financial sector ranged between 99 percent and 108 percent of the average for all domestic private industries. From 1983, it shot upward, reaching 181 percent in 2007.7

There’s a second reason why the financial sector abets income inequality: the “moving first” issue. Let’s say that some news hits the market and that traders interpret this news at different speeds. One trader figures out what the news means in a second, while the other traders require five seconds. Still other traders require an entire day or maybe even a month to figure things out. The early traders earn the extra money. They buy the proper assets early, at the lower prices, and reap most of the gains when the other, later traders pile on. Similarly, if you buy into a successful tech company in the early stages, you are “moving first” in a very effective manner, and you will capture most of the gains if that company hits it big.

The moving-first phenomenon sums to a “winner-take-all” market. Only some relatively small number of traders, sometimes just one trader, can be first. Those who are first will make far more than those who are fourth or fifth. This difference will persist, even if those who are fourth come pretty close to competing with those who are first. In this context, first is first and it doesn’t matter much whether those who come in fourth pile on a month, a minute or a fraction of a second later. Those who bought (or sold, as the case may be) first have captured and locked in most of the available gains. Since gains are concentrated among the early winners, and the closeness of the runner-ups doesn’t so much matter for income distribution, asset-market trading thus encourages the ongoing concentration of wealth. Many investors make lots of mistakes and lose their money, but each year brings a new bunch of projects that can turn the early investors and traders into very wealthy individuals.

These two features of the problem—“going short on volatility” and “getting there first”—are related. Let’s say that Goldman Sachs regularly secures a lot of the best and quickest trades, whether because of its quality analysis, inside connections or high-frequency trading apparatus (it has all three). It builds up a treasure chest of profits and continues to hire very sharp traders and to receive valuable information. Those profits allow it to make “short on volatility” bets faster than anyone else, because if it messes up, it still has a large enough buffer to pad losses. This increases the odds that Goldman will repeatedly pull in spectacular profits.

Still, every now and then Goldman will go bust, or would go bust if not for government bailouts. But the odds are in any given year that it won’t because of the advantages it and other big banks have. It’s as if the major banks have tapped a hole in the social till and they are drinking from it with a straw. In any given year, this practice may seem tolerable—didn’t the bank earn the money fair and square by a series of fairly normal looking trades? Yet over time this situation will corrode productivity, because what the banks do bears almost no resemblance to a process of getting capital into the hands of those who can make most efficient use of it. And it leads to periodic financial explosions. That, in short, is the real problem of income inequality we face today. It’s what causes the inequality at the very top of the earning pyramid that has dangerous implications for the economy as a whole.

What about controlling bank risk-taking directly with tight government oversight? That is not practical. There are more ways for banks to take risks than even knowledgeable regulators can possibly control; it just isn’t that easy to oversee a balance sheet with hundreds of billions of dollars on it, especially when short-term positions are wound down before quarterly inspections. It’s also not clear how well regulators can identify risky assets. Some of the worst excesses of the financial crisis were grounded in mortgage-backed assets—a very traditional function of banks—not exotic derivatives trading strategies. Virtually any asset position can be used to bet long odds, one way or another. It is naive to think that underpaid, undertrained regulators can keep up with financial traders, especially when the latter stand to earn billions by circumventing the intent of regulations while remaining within the letter of the law.

For the time being, we need to accept the possibility that the financial sector has learned how to game the American (and UK-based) system of state capitalism. It’s no longer obvious that the system is stable at a macro level, and extreme income inequality at the top has been one result of that imbalance. Income inequality is a symptom, however, rather than a cause of the real problem. The root cause of income inequality, viewed in the most general terms, is extreme human ingenuity, albeit of a perverse kind. That is why it is so hard to control.

Another root cause of growing inequality is that the modern world, by so limiting our downside risk, makes extreme risk-taking all too comfortable and easy. More risk-taking will mean more inequality, sooner or later, because winners always emerge from risk-taking. Yet bankers who take bad risks (provided those risks are legal) simply do not end up with bad outcomes in any absolute sense. They still have millions in the bank, lots of human capital and plenty of social status. We’re not going to bring back torture, trial by ordeal or debtors’ prisons, nor should we. Yet the threat of impoverishment and disgrace no longer looms the way it once did, so we no longer can constrain excess financial risk-taking. It’s too soft and cushy a world.

Why don’t we simply eliminate the safety net for clueless or unlucky risk-takers so that losses equal gains overall? That’s a good idea in principle, but it is hard to put into practice. Once a financial crisis arrives, politicians will seek to limit the damage, and that means they will bail out major financial institutions. Had we not passed TARP and related policies, the United States probably would have faced unemployment rates of 25 percent of higher, as in the Great Depression. The political consequences would not have been pretty. Bank bailouts may sound quite interventionist, and indeed they are, but in relative terms they probably were the most libertarian policy we had on tap. It meant big one-time expenses, but, for the most part, it kept government out of the real economy (the General Motors bailout aside).

We probably don’t have any solution to the hazards created by our financial sector, not because plutocrats are preventing our political system from adopting appropriate remedies, but because we don’t know what those remedies are. Yet neither is another crisis immediately upon us. The underlying dynamic favors excess risk-taking, but banks at the current moment fear the scrutiny of regulators and the public and so are playing it fairly safe. They are sitting on money rather than lending it out. The biggest risk today is how few parties will take risks, and, in part, the caution of banks is driving our current protracted economic slowdown. According to this view, the long run will bring another financial crisis once moods pick up and external scrutiny weakens, but that day of reckoning is still some ways off.

Is the overall picture a shame? Yes. Is it distorting resource distribution and productivity in the meantime? Yes. Will it again bring our economy to its knees? Probably. Maybe that’s simply the price of modern society. Income inequality will likely continue to rise and we will search in vain for the appropriate political remedies for our underlying problems.

Mark Zuckerberg does not appear to be that popular a figure. When you consider that Facebook has 600 million users, 18,353 votes for him, on Time's poll seems mighty few. Whatever Facebook users think of Facebook, they don't go out of their way to be supportive of Zuckerberg, as a public figure

Someday, all the fossil fuels that used to be in the ground will be burned. After that, in about a millennium, the earth will dissolve most of the resulting carbon dioxide into the oceans. (The oceans have dissolved in them “40 times more carbon than the atmosphere contains, a total of 30&nbsp;trillion tons, or 30 times the world’s coal reserves.”) The dissolving will leave the concentration in the atmosphere only slightly higher than today’s. Then “over tens of millennia, or perhaps hundreds” the earth will transfer the excess carbon dioxide into its rocks, “eventually returning levels in the sea and air to what they were before humans arrived on the scene.” This will take an eternity as humans reckon, but a blink in geologic time.

It seems, Laughlin says, that “something, presumably a geologic regulatory process, fixed the world’s carbon dioxide levels before humans arrived” with their SUVs and computers. Some scientists argue that “the photosynthetic machinery of plants seems optimized” to certain carbon dioxide levels. But “most models, even pessimistic ones,” envision “a thousand-year carbon dioxide pulse followed by glacially slow decay back to the pre-civilization situation.”

humans can “do damage persisting for geologic time” by “biodiversity loss”—extinctions that are, unlike carbon dioxide excesses, permanent. The earth did not reverse the extinction of the dinosaurs. Today extinctions result mostly from human population pressures—habitat destruction, pesticides, etc.—but “slowing man-made extinctions in a meaningful way would require drastically reducing the world’s human population.” Which will not happen.

To avoid mixing fact and speculation, earth scientists are, Laughlin says, “ultraconservative,” meaning they focus on the present and the immediate future: “[They] go to extraordinary lengths to prove by means of measurement that the globe is warming now, the ocean is acidifying now, fossil fuel is being exhausted now, and so forth, even though these things are self-evident in geologic time.”

Climate change over geologic time is, Laughlin says, something the earth has done “on its own without asking anyone’s permission or explaining itself.” People can cause climate change, but major glacial episodes have occurred “at regular intervals of 100,000 years,” always “a slow, steady cooling followed by abrupt warming back to conditions similar to today’s.”

Six million years ago the Mediterranean dried up. Ninety million years ago there were alligators in the Arctic. Three hundred million years ago Northern Europe was a desert and coal formed in Antarctica. “One thing we know for sure,” Laughlin says about these convulsions, “is that people weren’t involved.”

the emergence of the blogosphere requires significantly more openness from scientists. However, providing the details necessary to validate large datasets can be difficult and time-consuming, and how FoI laws apply to research is still an evolving area. Meanwhile, the public needs to understand that science cannot and does not produce absolutely precise answers. Though the uncertainties may become smaller and better constrained over time, uncertainty in science is a fact of life which policymakers have to deal with. The chapter concludes: “the Review would urge all scientists to learn to communicate their work in ways that the public can access and understand”.

email is less formal than other forms of communication: “Extreme forms of language are frequently applied to quite normal situations by people who would never use it in other communication channels.” The CRU scientists assumed their emails to be private, so they used “slang, jargon and acronyms” which would have been more fully explained had they been talking to the public. And although some emails suggest CRU went out of their way to make life difficult for their critics, there are others which suggest they were bending over backwards to be honest. Therefore the Review found “the e-mails cannot always be relied upon as evidence of what actually occurred, nor indicative of actual behaviour that is extreme, exceptional or unprofessional.” [section 4.3]

when put into the proper context, what do these emails actually reveal about the behaviour of the CRU scientists? The report concluded (its emphasis):

we find that their rigour and honesty as scientists are not in doubt.

we did not find any evidence of behaviour that might undermine the conclusions of the IPCC assessments.

The argument that Climategate reveals an international climate science conspiracy is not really a very skeptical one. Sure, it is skeptical in the weak sense of questioning authority, but it stops there. Unlike true skepticism, it doesn’t go on to objectively examine all the evidence and draw a conclusion based on that evidence. Instead, it cherry-picks suggestive emails, seeing everything as incontrovertible evidence of a conspiracy, and concludes all of mainstream climate science is guilty by association. This is not skepticism; this is conspiracy theory.

The media dropped the ball There is a famous quotation attributed to Mark Twain: “A lie can travel halfway around the world while the truth is putting on its shoes.” This is more true in the internet age than it was when Mark Twain was alive. Unfortunately, it took months for the Climategate inquiries to put on their shoes, and by the time they reported, the damage had already been done. The media acted as an uncritical loudspeaker for the initial allegations, which will now continue to circulate around the world forever, then failed to give anywhere near the same amount of coverage to the inquiries clearing the scientists involved. For instance, Rupert Murdoch’s The Australian published no less than 85 stories about Climategate, but not one about the Muir Russell inquiry.

Even the Guardian, who have a relatively good track record on environmental reporting and were quick to criticize the worst excesses of climate conspiracy theorists, could not resist the lure of stolen emails. As George Monbiot writes, journalists see FoI requests and email hacking as a way of keeping people accountable, rather than the distraction from actual science which they are to scientists. In contrast, CRU director Phil Jones says: “I wish people would spend as much time reading my scientific papers as they do reading my e-mails.”

This is part of a broader problem with climate change reporting: the media holds scientists to far higher standards than it does contrarians. Climate scientists have to be right 100% of the time, but contrarians apparently can get away with being wrong nearly 100% of the time. The tiniest errors of climate scientists are nitpicked and blown out of all proportion, but contrarians get away with monstrous distortions and cherry-picking of evidence. Around the same time The Australian was bashing climate scientists, the same newspaper had no problem publishing Viscount Monckton’s blatant misrepresentations of IPCC projections (not to mention his demonstrably false conspiracy theory that the Copenhagen summit was a plot to establish a world government).

In the current model of environmental reporting, the contrarians do not lose anything by making baseless accusations. In fact, it is in their interests to throw as much mud at scientists as possible to increase the chance that some of it will stick in the public consciousness. But there is untold damage to the reputation of the scientists against whom the accusations are being made. We can only hope that in future the media will be less quick to jump to conclusions. If only editors and producers would stop and think for a moment about what they’re doing: they are playing with the future of the planet.

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.

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.”

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.”

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.

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.

The whole point of Samuel Wee’s letter is to present Dr Ng’s statistics from a different angle, so as to show that things are not as rosy as Dr Ng made them seem. As posters above have pointed out, if 50% of poor students score in the top 2/3s, that means the other 50% score in the bottom 1/3. In other words, poor students still score disproportionately lower grades. As for the statistic that 90% of poor students do not make it to university, this was shown a graph provided in the ST. You can see it here: http://www.straitstimes.com/STI/STIMEDIA/pdf/20110308/a10.pdf

Finally, Dr Ng did say: “[Social mobility] cannot be about neglecting those with abilities, just because they come from middle-income homes or are rich. It cannot mean holding back those who are able so that others can catch up.” Samuel Wee paraphrased this as: “…good, able students from the middle-and-high income groups are not circumscribed or restricted in any way in the name of helping financially disadvantaged students.” I think it was an accurate paraphrase, because that was essentially what Dr Ng was saying. Samuel Wee’s paraphrase merely makes the callousness of Dr Ng’s remark stand out more clearly.

As to Mr Wee’s: “Therefore, it was greatly reassuring to read about Dr Ng’s great faith in our “unique, meritocratic Singapore system”, which ensures that good, able students from the middle-and-high income groups are not circumscribed or restricted in any way in the name of helping financially disadvantaged students”, there was nothing in the Minister’s speech, Straits Times and all other media reports, that quoted the Minister, in this context. In my opinion, the closest that I could find in all the reports, to link in context to the Minister’s faith in our meritocratic system, was what the Straits Times Forum Editor edited – “Therefore, it was reassuring to read about Dr Ng’s own experience of the ‘unique, meritocratic Singapore system’: he grew up in a three-room flat with five other siblings, and his medical studies at the National University of Singapore were heavily subsidised; later, he trained as a cancer surgeon in the United States using a government scholarship”.

To the credit of the Straits Times Forum Editor, inspite of the hundreds of letters that he receives in a day, he took the time and effort to:- Check the accuracy of the letter writer’s ‘quoted’ statistics Find the correct ‘quoted’ statistics to replace the writer’s wrongly ‘quoted’ statistics Check for misquotes out of context (in this case, what the Education Minister actually said), and then find the correct quote to amend the writer’s statement

Kind sir, the statistics state that 1 in 2 are in the top 66.6% (Which, incidentally, includes the top fifth of the bottom 50%!) Does it not stand to reason, then, that if 50% are in the top 66.6%, the remaining 50% are in the bottom 33.3%, as I stated in my letter?

Also, perhaps you were not aware of the existence of this resource, but here is a graph from the Straits Times illustrating the fact that only 10% of children from one-to-three room flats make it to university–which is to say, 90% of them don’t. http://www.straitstimes.com/STI/STIMEDIA/pdf/20110308/a10.pdf

The writer made it point to say that only 90% did not make it to university. It has been edited to say 50% made it to university AND POLYTECHNIC. Both are right, and that one is made to make the government look good

It’s amazing that the myth of the lone genius has persisted for so long, since simultaneous invention has always been the norm, not the exception. Anthropologists have shown that the same inventions tended to crop up in prehistory at roughly similar times, in roughly the same order, among cultures on different continents that couldn’t possibly have contacted one another.

Also, there’s a related myth—that innovation comes primarily from the profit motive, from the competitive pressures of a market society. If you look at history, innovation doesn’t come just from giving people incentives; it comes from creating environments where their ideas can connect.

The musician Brian Eno invented a wonderful word to describe this phenomenon: scenius. We normally think of innovators as independent geniuses, but Eno’s point is that innovation comes from social scenes,from passionate and connected groups of people.

It turns out that the lone genius entrepreneur has always been a rarity—there’s far more innovation coming out of open, nonmarket networks than we tend to assume.

Really, we should think of ideas as connections,in our brains and among people. Ideas aren’t self-contained things; they’re more like ecologies and networks. They travel in clusters.

ideas are networks

In part, that’s because ideas that leap too far ahead are almost never implemented—they aren’t even valuable. People can absorb only one advance, one small hop, at a time. Gregor Mendel’s ideas about genetics, for example: He formulated them in 1865, but they were ignored for 35 years because they were too advanced. Nobody could incorporate them. Then, when the collective mind was ready and his idea was only one hop away, three different scientists independently rediscovered his work within roughly a year of one another.

Charles Babbage is another great case study. His “analytical engine,” which he started designing in the 1830s, was an incredibly detailed vision of what would become the modern computer, with a CPU, RAM, and so on. But it couldn’t possibly have been built at the time, and his ideas had to be rediscovered a hundred years later.

I think there are a lot of ideas today that are ahead of their time. Human cloning, autopilot cars, patent-free law—all are close technically but too many steps ahead culturally. Innovating is about more than just having the idea yourself; you also have to bring everyone else to where your idea is. And that becomes really difficult if you’re too many steps ahead.

The scientist Stuart Kauffman calls this the “adjacent possible.” At any given moment in evolution—of life, of natural systems, or of cultural systems—there’s a space of possibility that surrounds any current configuration of things. Change happens when you take that configuration and arrange it in a new way. But there are limits to how much you can change in a single move.

Which is why the great inventions are usually those that take the smallest possible step to unleash the most change. That was the difference between Tim Berners-Lee’s successful HTML code and Ted Nelson’s abortive Xanadu project. Both tried to jump into the same general space—a networked hypertext—but Tim’s approach did it with a dumb half-step, while Ted’s earlier, more elegant design required that everyone take five steps all at once.

Also, the steps have to be taken in the right order. You can’t invent the Internet and then the digital computer. This is true of life as well. The building blocks of DNA had to be in place before evolution could build more complex things. One of the key ideas I’ve gotten from you, by the way—when I read your book Out of Control in grad school—is this continuity between biological and technological systems.

technology is something that can give meaning to our lives, particularly in a secular world.

He had this bleak, soul-sucking vision of technology as an autonomous force for evil. You also present technology as a sort of autonomous force—as wanting something, over the long course of its evolution—but it’s a more balanced and ultimately positive vision, which I find much more appealing than the alternative.

As I started thinking about the history of technology, there did seem to be a sense in which, during any given period, lots of innovations were in the air, as it were. They came simultaneously. It appeared as if they wanted to happen. I should hasten to add that it’s not a conscious agency; it’s a lower form, something like the way an organism or bacterium can be said to have certain tendencies, certain trends, certain urges. But it’s an agency nevertheless.

technology wants increasing diversity—which is what I think also happens in biological systems, as the adjacent possible becomes larger with each innovation. As tech critics, I think we have to keep this in mind, because when you expand the diversity of a system, that leads to an increase in great things and an increase in crap.

the idea that the most creative environments allow for repeated failure.

And for wastes of time and resources. If you knew nothing about the Internet and were trying to figure it out from the data, you would reasonably conclude that it was designed for the transmission of spam and porn. And yet at the same time, there’s more amazing stuff available to us than ever before, thanks to the Internet.

To create something great, you need the means to make a lot of really bad crap. Another example is spectrum. One reason we have this great explosion of innovation in wireless right now is that the US deregulated spectrum. Before that, spectrum was something too precious to be wasted on silliness. But when you deregulate—and say, OK, now waste it—then you get Wi-Fi.

If we didn’t have genetic mutations, we wouldn’t have us. You need error to open the door to the adjacent possible.

image of the coral reef as a metaphor for where innovation comes from. So what, today, are some of the most reeflike places in the technological realm?

Twitter—not to see what people are having for breakfast, of course, but to see what people are talking about, the links to articles and posts that they’re passing along.

second example of an information coral reef, and maybe the less predictable one, is the university system. As much as we sometimes roll our eyes at the ivory-tower isolation of universities, they continue to serve as remarkable engines of innovation.

Life seems to gravitate toward these complex states where there’s just enough disorder to create new things. There’s a rate of mutation just high enough to let interesting new innovations happen, but not so many mutations that every new generation dies off immediately.

, technology is an extension of life. Both life and technology are faces of the same larger system.

The WikiLeaks cables present quite a different picture. What emerges is one reality (the real one) colliding with another (the official one). We see smart, good-faith diplomats and foreign service personnel trying to make the truth on the ground match up to the one the administration has proclaimed to the public. The cables show the widening disconnect. It's like a foreign policy Ponzi scheme -- this one fueled not by the public's money, but the public's acquiescence.

The second aspect of the story -- the one that was the focus of the symposium -- is the changing relationship to government that technology has made possible.

Back in the year 2007, B.W. (Before WikiLeaks), Barack Obama waxed lyrical about government and the internet: "We have to use technology to open up our democracy. It's no coincidence that one of the most secretive administrations in our history has favored special interest and pursued policy that could not stand up to the sunlight."

Not long after the election, in announcing his "Transparency and Open Government" policy, the president proclaimed: "Transparency promotes accountability and provides information for citizens about what their Government is doing. Information maintained by the Federal Government is a national asset." Cut to a few years later. Now that he's defending a reality that doesn't match up to, well, reality, he's suddenly not so keen on the people having a chance to access this "national asset."

Even more wikironic are the statements by his Secretary of State who, less than a year ago, was lecturing other nations about the value of an unfettered and free internet. Given her description of the WikiLeaks as "an attack on America's foreign policy interests" that have put in danger "innocent people," her comments take on a whole different light. Some highlights: In authoritarian countries, information networks are helping people discover new facts and making governments more accountable... technologies with the potential to open up access to government and promote transparency can also be hijacked by governments to crush dissent and deny human rights... As in the dictatorships of the past, governments are targeting independent thinkers who use these tools. Now "making government accountable" is, as White House spokesman Robert Gibbs put it, a "reckless and dangerous action."

ay Rosen, one of the participants in the symposium, wrote a brilliant essay entitled "From Judith Miller to Julian Assange." He writes: For the portion of the American press that still looks to Watergate and the Pentagon Papers for inspiration, and that considers itself a check on state power, the hour of its greatest humiliation can, I think, be located with some precision: it happened on Sunday, September 8, 2002. That was when the New York Times published Judith Miller and Michael Gordon's breathless, spoon-fed -- and ultimately inaccurate -- account of Iraqi attempts to buy aluminum tubes to produce fuel for a nuclear bomb.

Miller's after-the-facts-proved-wrong response, as quoted in a Michael Massing piece in the New York Review of Books, was: "My job isn't to assess the government's information and be an independent intelligence analyst myself. My job is to tell readers of The New York Times what the government thought about Iraq's arsenal." In other words, her job is to tell citizens what their government is saying, not, as Obama called for in his transparency initiative, what their government is doing.

As Jay Rosen put it: Today it is recognized at the Times and in the journalism world that Judy Miller was a bad actor who did a lot of damage and had to go. But it has never been recognized that secrecy was itself a bad actor in the events that led to the collapse, that it did a lot of damage, and parts of it might have to go. Our press has never come to terms with the ways in which it got itself on the wrong side of secrecy as the national security state swelled in size after September 11th.

And in the WikiLeaks case, much of media has again found itself on the wrong side of secrecy -- and so much of the reporting about WikiLeaks has served to obscure, to conflate, to mislead. For instance, how many stories have you heard or read about all the cables being "dumped" in "indiscriminate" ways with no attempt to "vet" and "redact" the stories first. In truth, only just over 1,200 of the 250,000 cables have been released, and WikiLeaks is now publishing only those cables vetted and redacted by their media partners, which includes the New York Times here and the Guardian in England.

The establishment media may be part of the media, but they're also part of the establishment. And they're circling the wagons. One method they're using, as Andrew Rasiej put it after the symposium, is to conflate the secrecy that governments use to operate and the secrecy that is used to hide the truth and allow governments to mislead us.

Nobody, including WikiLeaks, is promoting the idea that government should exist in total transparency,

Assange himself would not disagree. "Secrecy is important for many things," he told Time's Richard Stengel. "We keep secret the identity of our sources, as an example, take great pains to do it." At the same time, however, secrecy "shouldn't be used to cover up abuses."

Decentralizing government power, limiting it, and challenging it was the Founders' intent and these have always been core conservative principles. Conservatives should prefer an explosion of whistleblower groups like WikiLeaks to a federal government powerful enough to take them down. Government officials who now attack WikiLeaks don't fear national endangerment, they fear personal embarrassment. And while scores of conservatives have long promised to undermine or challenge the current monstrosity in Washington, D.C., it is now an organization not recognizably conservative that best undermines the political establishment and challenges its very foundations.

It is not, as Simon Jenkins put it in the Guardian, the job of the media to protect the powerful from embarrassment. As I said at the symposium, its job is to play the role of the little boy in The Emperor's New Clothes -- brave enough to point out what nobody else is willing to say.

When the press trades truth for access, it is WikiLeaks that acts like the little boy. "Power," wrote Jenkins, "loathes truth revealed. When the public interest is undermined by the lies and paranoia of power, it is disclosure that takes sanity by the scruff of its neck and sets it back on its feet."

A final aspect of the story is Julian Assange himself. Is he a visionary? Is he an anarchist? Is he a jerk? This is fun speculation, but why does it have an impact on the value of the WikiLeaks revelations?

And these two books arrive at a time, unlike the early 1990s, when universities are, like many students, backed into a fiscal corner. Taylor writes of walking into a meeting one day and learning that Columbia’s endowment had dropped by “at least” 30 percent. Simply brushing off calls for reform, however strident and scattershot, may no longer be an option.

The labor system, for one thing, is clearly unjust. Tenured and tenure-track professors earn most of the money and benefits, but they’re a minority at the top of a pyramid. Nearly two-thirds of all college teachers are non-tenure-track adjuncts like Matt Williams, who told Hacker and Dreifus he had taught a dozen courses at two colleges in the Akron area the previous year, earning the equivalent of about $8.50 an hour by his reckoning. It is foolish that graduate programs are pumping new Ph.D.’s into a world without decent jobs for them. If some programs were phased out, teaching loads might be raised for some on the tenure track, to the benefit of undergraduate education.

it might well be time to think about vetoing Olympic-quality athletic ­facilities and trimming the ranks of administrators. At Williams, a small liberal arts college renowned for teaching, 70 percent of employees do something other than teach.

But Hacker and Dreifus go much further, all but calling for an end to the role of universities in the production of knowledge. Spin off the med schools and research institutes, they say. University presidents “should be musing about education, not angling for another center on antiterrorist technologies.” As for the humanities, let professors do research after-hours, on top of much heavier teaching schedules. “In other occupations, when people feel there is something they want to write, they do it on their own time and at their own expense,” the authors declare. But it seems doubtful that, say, “Battle Cry of Freedom,” the acclaimed Civil War history by Princeton’s James McPherson, could have been written on the weekends, or without the advance spadework of countless obscure monographs. If it is false that research invariably leads to better teaching, it is equally false to say that it never does.

Hacker’s home institution, the public Queens College, which has a spartan budget, commuter students and a three-or-four-course teaching load per semester. Taylor, by contrast, has spent his career on the elite end of higher education, but he is no less disillusioned. He shares Hacker and Dreifus’s concerns about overspecialized research and the unintended effects of tenure, which he believes blocks the way to fresh ideas. Taylor has backed away from some of the most incendiary proposals he made last year in a New York Times Op-Ed article, cheekily headlined “End the University as We Know It” — an article, he reports, that drew near-universal condemnation from academics and near-universal praise from everyone else. Back then, he called for the flat-out abolition of traditional departments, to be replaced by temporary, “problem-centered” programs focusing on issues like Mind, Space, Time, Life and Water. Now, he more realistically suggests the creation of cross-­disciplinary “Emerging Zones.” He thinks professors need to get over their fear of corporate partnerships and embrace efficiency-enhancing technologies.

It is not news that America is a land of haves and have-nots. It is news that colleges are themselves dividing into haves and have-nots; they are becoming engines of inequality. And that — not whether some professors can afford to wear Marc Jacobs — is the real scandal.

this push to abbreviate and banalify the more esoteric but truly intriguing mysteries of the universe has lurched close to parody yet failed to be as thoughtfully funny as Douglas Adams was with the Hitchhiker’s Guide to the Galaxy

Our most powerful telescopes are approaching what Columbia physicist and mathematician Brian Greene recently called the cliffs of time,&nbsp; beyond which an infinitely large yet progressively emptier universe lies forever invisible to us and vice versa, since to that universe, we also lie beyond the cliffs of time. This capturing of images from the start of time is being done by finding incredibly faint and old light using computing power and forensic techniques not even devised when Hubble was assembled on earth. In this instance Hubble has found the faint image of an object that emitted light a mere 480 million years after the ‘big bang’ 13.7 billion years ago. It is, thus, nearly as old as time itself.

The conspiracy of over simplification has until now kept the really gnarly principles involved in big bang theory out of the general media because nothing short of a first class degree in theoretical and practical physics is going to suffice for a reasonable overview. Plus a 100,000 word article with a few thousand diagrams.

Of course, ST reserves the right to edit my letter for clarity and length. When said statistics in question were directly taken from their original article, though, one has to wonder if there hasn’t been a breakdown in communication over there. I’m dreadfully sorry, forum editors, I should have double-checked my original source (your journalist Ms Rachel Chang) before sending my letter.

take a look at how my pride in our meritocratic system in my originally letter has been transfigured into awe at Dr Ng’s background, for example! Dear friends, when an editor takes the time and effort to not just paraphrase but completely and utterly transform your piece in both intent and meaning, then what can we say but bravo.

There are surely no lazy slackers over at the Straits Times; instead we have evidently men and women who dedicate time and effort to correct their misguided readers, and protect them from the shame of having their real opinions published.

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.

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.&nbsp;

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&nbsp; 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.

iPhone apps transmitted more data than the apps on phones using Google Inc.'s Android operating system. Because of the test's size, it's not known if the pattern holds among the hundreds of thousands of apps available.

TextPlus 4, a popular iPhone app for text messaging. It sent the phone's unique ID number to eight ad companies and the phone's zip code, along with the user's age and gender, to two of them.

Pandora, a popular music app, sent age, gender, location and phone identifiers to various ad networks. iPhone and Android versions of a game called Paper Toss—players try to throw paper wads into a trash can—each sent the phone's ID number to at least five ad companies. Grindr, an iPhone app for meeting gay men, sent gender, location and phone ID to three ad companies.

iPhone maker Apple Inc. says it reviews each app before offering it to users. Both Apple and Google say they protect users by requiring apps to obtain permission before revealing certain kinds of information, such as location.

The Journal found that these rules can be skirted. One iPhone app, Pumpkin Maker (a pumpkin-carving game), transmits location to an ad network without asking permission. Apple declines to comment on whether the app violated its rules.

With few exceptions, app users can't "opt out" of phone tracking, as is possible, in limited form, on regular computers. On computers it is also possible to block or delete "cookies," which are tiny tracking files. These techniques generally don't work on cellphone apps.

makers of TextPlus 4, Pandora and Grindr say the data they pass on to outside firms isn't linked to an individual's name. Personal details such as age and gender are volunteered by users, they say. The maker of Pumpkin Maker says he didn't know Apple required apps to seek user approval before transmitting location. The maker of Paper Toss didn't respond to requests for comment.

Many apps don't offer even a basic form of consumer protection: written privacy policies. Forty-five of the 101 apps didn't provide privacy policies on their websites or inside the apps at the time of testing. Neither Apple nor Google requires app privacy policies.

the most widely shared detail was the unique ID number assigned to every phone.

On iPhones, this number is the "UDID," or Unique Device Identifier. Android IDs go by other names. These IDs are set by phone makers, carriers or makers of the operating system, and typically can't be blocked or deleted. "The great thing about mobile is you can't clear a UDID like you can a cookie," says Meghan O'Holleran of Traffic Marketplace, an Internet ad network that is expanding into mobile apps. "That's how we track everything."

O'Holleran says Traffic Marketplace, a unit of Epic Media Group, monitors smartphone users whenever it can. "We watch what apps you download, how frequently you use them, how much time you spend on them, how deep into the app you go," she says. She says the data is aggregated and not linked to an individual.

Apple and Google ad networks let advertisers target groups of users. Both companies say they don't track individuals based on the way they use apps.

Apple limits what can be installed on an iPhone by requiring iPhone apps to be offered exclusively through its App Store. Apple reviews those apps for function, offensiveness and other criteria.

Apple says iPhone apps "cannot transmit data about a user without obtaining the user's prior permission and providing the user with access to information about how and where the data will be used." Many apps tested by the Journal appeared to violate that rule, by sending a user's location to ad networks, without informing users. Apple declines to discuss how it interprets or enforces the policy.

Google doesn't review the apps, which can be downloaded from many vendors. Google says app makers "bear the responsibility for how they handle user information." Google requires Android apps to notify users, before they download the app, of the data sources the app intends to access. Possible sources include the phone's camera, memory, contact list, and more than 100 others. If users don't like what a particular app wants to access, they can choose not to install the app, Google says.

Neither Apple nor Google requires apps to ask permission to access some forms of the device ID, or to send it to outsiders. When smartphone users let an app see their location, apps generally don't disclose if they will pass the location to ad companies.

Lack of standard practices means different companies treat the same information differently. For example, Apple says that, internally, it treats the iPhone's UDID as "personally identifiable information." That's because, Apple says, it can be combined with other personal details about people—such as names or email addresses—that Apple has via the App Store or its iTunes music services. By contrast, Google and most app makers don't consider device IDs to be identifying information.

A growing industry is assembling this data into profiles of cellphone users. Mobclix, the ad exchange, matches more than 25 ad networks with some 15,000 apps seeking advertisers. The Palo Alto, Calif., company collects phone IDs, encodes them (to obscure the number), and assigns them to interest categories based on what apps people download and how much time they spend using an app, among other factors. By tracking a phone's location, Mobclix also makes a "best guess" of where a person lives, says Mr. Gurbuxani, the Mobclix executive. Mobclix then matches that location with spending and demographic data from Nielsen Co.

Mobclix can place a user in one of 150 "segments" it offers to advertisers, from "green enthusiasts" to "soccer moms." For example, "die hard gamers" are 15-to-25-year-old males with more than 20 apps on their phones who use an app for more than 20 minutes at a time. Mobclix says its system is powerful, but that its categories are broad enough to not identify individuals. "It's about how you track people better," Mr. Gurbuxani says.

four app makers posted privacy policies after being contacted by the Journal, including Rovio Mobile Ltd., the Finnish company behind the popular game Angry Birds (in which birds battle egg-snatching pigs). A spokesman says Rovio had been working on the policy, and the Journal inquiry made it a good time to unveil it.

Free and paid versions of Angry Birds were tested on an iPhone. The apps sent the phone's UDID and location to the Chillingo unit of Electronic Arts Inc., which markets the games. Chillingo says it doesn't use the information for advertising and doesn't share it with outsiders.

Some developers feel pressure to release more data about people. Max Binshtok, creator of the DailyHoroscope Android app, says ad-network executives encouraged him to transmit users' locations. Mr. Binshtok says he declined because of privacy concerns. But ads targeted by location bring in two to five times as much money as untargeted ads, Mr. Binshtok says. "We are losing a lot of revenue."

Apple targets ads to phone users based largely on what it knows about them through its App Store and iTunes music service. The targeting criteria can include the types of songs, videos and apps a person downloads, according to an Apple ad presentation reviewed by the Journal. The presentation named 103 targeting categories, including: karaoke, Christian/gospel music, anime, business news, health apps, games and horror movies. People familiar with iAd say Apple doesn't track what users do inside apps and offers advertisers broad categories of people, not specific individuals. Apple has signaled that it has ideas for targeting people more closely. In a patent application filed this past May, Apple outlined a system for placing and pricing ads based on a person's "web history or search history" and "the contents of a media library." For example, home-improvement advertisers might pay more to reach a person who downloaded do-it-yourself TV shows, the document says.

The patent application also lists another possible way to target people with ads: the contents of a friend's media library. How would Apple learn who a cellphone user's friends are, and what kinds of media they prefer? The patent says Apple could tap "known connections on one or more social-networking websites" or "publicly available information or private databases describing purchasing decisions, brand preferences," and other data. In September, Apple introduced a social-networking service within iTunes, called Ping, that lets users share music preferences with friends. Apple declined to comment.

Morris also makes heavy use of the “taking a quote out of context” strategy favored by creationists. His quotes are often from secondary sources and are incomplete.

A more scholarly (i.e. intellectually honest) approach would be to cite actual evidence to support a point. If you are going to cite an authority, then make sure the quote is relevant, in context, and complete.

And even better, cite a number of sources to show that the opinion is representative. Rather we get single, partial, and often outdated quotes without context.

(nature is not, it turns out, cleanly divided into “kinds”, which have no operational definition). He also repeats this canard: Such variation is often called microevolution, and these minor horizontal (or downward) changes occur fairly often, but such changes are not true “vertical” evolution. This is the microevolution/macroevolution false dichotomy. It is only “often called” this by creationists – not by actual evolutionary scientists. There is no theoretical or empirical division between macro and micro evolution. There is just evolution, which can result in the full spectrum of change from minor tweaks to major changes.

Morris wonders why there are no “dats” – dog-cat transitional species. He misses the hierarchical nature of evolution. As evolution proceeds, and creatures develop a greater and greater evolutionary history behind them, they increasingly are committed to their body plan. This results in a nestled hierarchy of groups – which is reflected in taxonomy (the naming scheme of living things).

once our distant ancestors developed the basic body plan of chordates, they were committed to that body plan. Subsequent evolution resulted in variations on that plan, each of which then developed further variations, etc. But evolution cannot go backward, undo evolutionary changes and then proceed down a different path. Once an evolutionary line has developed into a dog, evolution can produce variations on the dog, but it cannot go backwards and produce a cat.

Stephen J. Gould described this distinction as the difference between disparity and diversity. Disparity (the degree of morphological difference) actually decreases over evolutionary time, as lineages go extinct and the surviving lineages are committed to fewer and fewer basic body plans. Meanwhile, diversity (the number of variations on a body plan) within groups tends to increase over time.

the kind of evolutionary changes that were happening in the past, when species were relatively undifferentiated (compared to contemporary species) is indeed not happening today. Modern multi-cellular life has 600 million years of evolutionary history constraining their future evolution – which was not true of species at the base of the evolutionary tree. But modern species are indeed still evolving.

Here is a list of research documenting observed instances of speciation. The list is from 1995, and there are more recent examples to add to the list. Here are some more. And&nbsp;here is a good list with references of more recent cases.

Next Morris tries to convince the reader that there is no evidence for evolution in the past, focusing on the fossil record. He repeats the false claim (again, which I already dealt with) that there are no transitional fossils: Even those who believe in rapid evolution recognize that a considerable number of generations would be required for one distinct “kind” to evolve into another more complex kind. There ought, therefore, to be a considerable number of true transitional structures preserved in the fossils — after all, there are billions of non-transitional structures there! But (with the exception of a few very doubtful creatures such as the controversial feathered dinosaurs and the alleged walking whales), they are not there.

I deal with this question at length here, pointing out that there are numerous transitional fossils for the evolution of terrestrial vertebrates, mammals, whales, birds, turtles, and yes – humans from ape ancestors. There are many more examples, these are just some of my favorites.

Much of what follows (as you can see it takes far more space to correct the lies and distortions of Morris than it did to create them) is classic denialism – misinterpreting the state of the science, and confusing lack of information about the details of evolution with lack of confidence in the fact of evolution. Here are some examples – he quotes Niles Eldridge: “It is a simple ineluctable truth that virtually all members of a biota remain basically stable, with minor fluctuations, throughout their durations. . . .“ So how do evolutionists arrive at their evolutionary trees from fossils of organisms which didn’t change during their durations? Beware the “….” – that means that meaningful parts of the quote are being omitted. I happen to have the book (The Pattern of Evolution) from which Morris mined that particular quote. Here’s the rest of it: (Remember, by “biota” we mean the commonly preserved plants and animals of a particular geological interval, which occupy regions often as large as Roger Tory Peterson’s “eastern” region of North American birds.) And when these systems change – when the older species disappear, and new ones take their place – the change happens relatively abruptly and in lockstep fashion.”

Eldridge was one of the authors (with Gould) of punctuated equilibrium theory. This states that, if you look at the fossil record, what we see are species emerging, persisting with little change for a while, and then disappearing from the fossil record. They theorize that most species most of the time are at equilibrium with their environment, and so do not change much. But these periods of equilibrium are punctuated by disequilibrium – periods of change when species will have to migrate, evolve, or go extinct.

This does not mean that speciation does not take place. And if you look at the fossil record we see a pattern of descendant species emerging from ancestor species over time – in a nice evolutionary pattern. Morris gives a complete misrepresentation of Eldridge’s point – once again we see intellectual dishonesty in his methods of an astounding degree.

Regarding the atheism = religion comment, it reminds me of a great analogy that I first heard on twitter from Evil Eye. (paraphrase) “those that say atheism is a religion, is like saying ‘not collecting stamps’ is a hobby too.”

Morris next tackles the genetic evidence, writing: More often is the argument used that similar DNA structures in two different organisms proves common evolutionary ancestry. Neither argument is valid. There is no reason whatever why the Creator could not or would not use the same type of genetic code based on DNA for all His created life forms. This is evidence for intelligent design and creation, not evolution.

Here is an excellent summary of the multiple lines of molecular evidence for evolution. Basically, if we look at the sequence of DNA, the variations in trinucleotide codes for amino acids, and amino acids for proteins, and transposons within DNA we see a pattern that can only be explained by evolution (or a mischievous god who chose, for some reason, to make life look exactly as if it had evolved – a non-falsifiable notion).

The genetic code is essentially comprised of four letters (ACGT for DNA), and every triplet of three letters equates to a specific amino acid. There are 64 (4^3) possible three letter combinations, and 20 amino acids. A few combinations are used for housekeeping, like a code to indicate where a gene stops, but the rest code for amino acids. There are more combinations than amino acids, so most amino acids are coded for by multiple combinations. This means that a mutation that results in a one-letter change might alter from one code for a particular amino acid to another code for the same amino acid. This is called a silent mutation because it does not result in any change in the resulting protein.

It also means that there are very many possible codes for any individual protein. The question is – which codes out of the gazillions of possible codes do we find for each type of protein in different species. If each “kind” were created separately there would not need to be any relationship. Each kind could have it’s own variation, or they could all be identical if they were essentially copied (plus any mutations accruing since creation, which would be minimal). But if life evolved then we would expect that the exact sequence of DNA code would be similar in related species, but progressively different (through silent mutations) over evolutionary time.

This is precisely what we find – in every protein we have examined. This pattern is necessary if evolution were true. It cannot be explained by random chance (the probability is absurdly tiny – essentially zero). And it makes no sense from a creationist perspective. This same pattern (a branching hierarchy) emerges when we look at amino acid substitutions in proteins and other aspects of the genetic code.

Morris goes for the second law of thermodynamics again – in the exact way that I already addressed. He responds to scientists correctly pointing out that the Earth is an open system, by writing: This naive response to the entropy law is typical of evolutionary dissimulation. While it is true that local order can increase in an open system if certain conditions are met, the fact is that evolution does not meet those conditions. Simply saying that the earth is open to the energy from the sun says nothing about how that raw solar heat is converted into increased complexity in any system, open or closed. The fact is that the best known and most fundamental equation of thermodynamics says that the influx of heat into an open system will increase the entropy of that system, not decrease it. All known cases of decreased entropy (or increased organization) in open systems involve a guiding program of some sort and one or more energy conversion mechanisms.

Energy has to be transformed into a usable form in order to do the work necessary to decrease entropy. That’s right. That work is done by life. Plants take solar energy (again – I’m not sure what “raw solar heat” means) and convert it into food. That food fuels the processes of life, which include development and reproduction. Evolution emerges from those processes- therefore the conditions that Morris speaks of are met.

But Morris next makes a very confused argument: Evolution has neither of these. Mutations are not “organizing” mechanisms, but disorganizing (in accord with the second law). They are commonly harmful, sometimes neutral, but never beneficial (at least as far as observed mutations are concerned). Natural selection cannot generate order, but can only “sieve out” the disorganizing mutations presented to it, thereby conserving the existing order, but never generating new order.

The notion that evolution (as if it’s a thing) needs to use energy is hopelessly confused. Evolution is a process that emerges from the system of life – and life certainly can use solar energy to decrease its entropy, and by extension the entropy of the biosphere. Morris slips into what is often presented as an information argument.&nbsp; (Yet again – already dealt with. The pattern here is that we are seeing a shuffling around of the same tired creationists arguments.) It is first not true that most mutations are harmful. Many are silent, and many of those that are not silent are not harmful. They may be neutral, they may be a mixed blessing, and their relative benefit vs harm is likely to be situational. They may be fatal. And they also may be simply beneficial.

Morris finishes with a long rambling argument that evolution is religion. Evolution is promoted by its practitioners as more than mere science. Evolution is promulgated as an ideology, a secular religion — a full-fledged alternative to Christianity, with meaning and morality . . . . Evolution is a religion. This was true of evolution in the beginning, and it is true of evolution still today. Morris ties evolution to atheism, which, he argues, makes it a religion. This assumes, of course, that atheism is a religion. That depends on how you define atheism and how you define religion – but it is mostly wrong. Atheism is a lack of belief in one particular supernatural claim – that does not qualify it as a religion.

But mutations are not “disorganizing” – that does not even make sense. It seems to be based on a purely creationist notion that species are in some privileged perfect state, and any mutation can only take them farther from that perfection. For those who actually understand biology, life is a kluge of compromises and variation. Mutations are mostly lateral moves from one chaotic state to another. They are not directional. But they do provide raw material, variation, for natural selection. Natural selection cannot generate variation, but it can select among that variation to provide differential survival. This is an old game played by creationists – mutations are not selective, and natural selection is not creative (does not increase variation). These are true but irrelevant, because mutations increase variation and information, and selection is a creative force that results in the differential survival of better adapted variation.

The local papers have a long record of publicly endorsing the PAP-led government's position, according to Tan Tarn How, a research fellow at the Institute of Policy Studies (IPS) and himself a former journalist. In his research paper "Singapore's print media policy - a national success?" published last year he quoted Leslie Fong, a former editor of the Straits Times, saying that the press "should resist the temptation to arrogate itself the role of a watchdog, or permanent critic, of the government of the day".

With regularly briefed and supportive editors, there is no need for pre-publication censorship, according to Tan. When the editors are perceived to get things "wrong", the government frequently takes to task, either publicly or privately, the newspaper's editors or individual journalists, he said.

The country's main newspaper, the Straits Times, has consistently stood by its editorial decision-making. Editor Han Fook Kwang said last year: "Our circulation is 380,000 and we have a readership of 1.4 million - these are people who buy the paper every day. We're aware people say we're a government mouthpiece or that we are biased but the test is if our readers believe in the paper and continue to buy it."

Chee also questioned Yap's claims that The Straits Times' integrity had been damaged by the SDP's articles, citing how the Singapore media was already ranked lowly in international press freedom rankings.

Yap wanted Chee to retract his statements about the integrity of The Straits Times, and that the newspaper would withhold publishing his letters in the forum pages until he did so.