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Unlike the drum language, which was based on spoken language, the optical telegraph was based on written French. Chappe invented an elaborate coding system to translate written messages into optical signals. Chappe had the opposite problem from the drummers. The drummers had a fast transmission system with ambiguous messages. They needed to slow down the transmission to make the messages unambiguous. Chappe had a painfully slow transmission system with redundant messages. The French language, like most alphabetic languages, is highly redundant, using many more letters than are needed to convey the meaning of a message. Chappe’s coding system allowed messages to be transmitted faster. Many common phrases and proper names were encoded by only two optical symbols, with a substantial gain in speed of transmission. The composer and the reader of the message had code books listing the message codes for eight thousand phrases and names. For Napoleon it was an advantage to have a code that was effectively cryptographic, keeping the content of the messages secret from citizens along the route.

After these two historical examples of rapid communication in Africa and France, the rest of Gleick’s book is about the modern development of information technolog

The modern history is dominated by two Americans, Samuel Morse and Claude Shannon. Samuel Morse was the inventor of Morse Code. He was also one of the pioneers who built a telegraph system using electricity conducted through wires instead of optical pointers deployed on towers. Morse launched his electric telegraph in 1838 and perfected the code in 1844. His code used short and long pulses of electric current to represent letters of the alphabet.

Morse was ideologically at the opposite pole from Chappe. He was not interested in secrecy or in creating an instrument of government power. The Morse system was designed to be a profit-making enterprise, fast and cheap and available to everybody. At the beginning the price of a message was a quarter of a cent per letter. The most important users of the system were newspaper correspondents spreading news of local events to readers all over the world. Morse Code was simple enough that anyone could learn it. The system provided no secrecy to the users. If users wanted secrecy, they could invent their own secret codes and encipher their messages themselves. The price of a message in cipher was higher than the price of a message in plain text, because the telegraph operators could transcribe plain text faster. It was much easier to correct errors in plain text than in cipher.

Claude Shannon was the founding father of information theory. For a hundred years after the electric telegraph, other communication systems such as the telephone, radio, and television were invented and developed by engineers without any need for higher mathematics. Then Shannon supplied the theory to understand all of these systems together, defining information as an abstract quantity inherent in a telephone message or a television picture. Shannon brought higher mathematics into the game.

When Shannon was a boy growing up on a farm in Michigan, he built a homemade telegraph system using Morse Code. Messages were transmitted to friends on neighboring farms, using the barbed wire of their fences to conduct electric signals. When World War II began, Shannon became one of the pioneers of scientific cryptography, working on the high-level cryptographic telephone system that allowed Roosevelt and Churchill to talk to each other over a secure channel. Shannon’s friend Alan Turing was also working as a cryptographer at the same time, in the famous British Enigma project that successfully deciphered German military codes. The two pioneers met frequently when Turing visited New York in 1943, but they belonged to separate secret worlds and could not exchange ideas about cryptography.

In 1945 Shannon wrote a paper, “A Mathematical Theory of Cryptography,” which was stamped SECRET and never saw the light of day. He published in 1948 an expurgated version of the 1945 paper with the title “A Mathematical Theory of Communication.” The 1948 version appeared in the Bell System Technical Journal, the house journal of the Bell Telephone Laboratories, and became an instant classic. It is the founding document for the modern science of information. After Shannon, the technology of information raced ahead, with electronic computers, digital cameras, the Internet, and the World Wide Web.

According to Gleick, the impact of information on human affairs came in three installments: first the history, the thousands of years during which people created and exchanged information without the concept of measuring it; second the theory, first formulated by Shannon; third the flood, in which we now live

The event that made the flood plainly visible occurred in 1965, when Gordon Moore stated Moore’s Law. Moore was an electrical engineer, founder of the Intel Corporation, a company that manufactured components for computers and other electronic gadgets. His law said that the price of electronic components would decrease and their numbers would increase by a factor of two every eighteen months. This implied that the price would decrease and the numbers would increase by a factor of a hundred every decade. Moore’s prediction of continued growth has turned out to be astonishingly accurate during the forty-five years since he announced it. In these four and a half decades, the price has decreased and the numbers have increased by a factor of a billion, nine powers of ten. Nine powers of ten are enough to turn a trickle into a flood.

Gordon Moore was in the hardware business, making hardware components for electronic machines, and he stated his law as a law of growth for hardware. But the law applies also to the information that the hardware is designed to embody. The purpose of the hardware is to store and process information. The storage of information is called memory, and the processing of information is called computing. The consequence of Moore’s Law for information is that the price of memory and computing decreases and the available amount of memory and computing increases by a factor of a hundred every decade. The flood of hardware becomes a flood of information.

In 1949, one year after Shannon published the rules of information theory, he drew up a table of the various stores of memory that then existed. The biggest memory in his table was the US Library of Congress, which he estimated to contain one hundred trillion bits of information. That was at the time a fair guess at the sum total of recorded human knowledge. Today a memory disc drive storing that amount of information weighs a few pounds and can be bought for about a thousand dollars. Information, otherwise known as data, pours into memories of that size or larger, in government and business offices and scientific laboratories all over the world. Gleick quotes the computer scientist Jaron Lanier describing the effect of the flood: “It’s as if you kneel to plant the seed of a tree and it grows so fast that it swallows your whole town before you can even rise to your feet.”

On December 8, 2010, Gleick published on the The New York Review’s blog an illuminating essay, “The Information Palace.” It was written too late to be included in his book. It describes the historical changes of meaning of the word “information,” as recorded in the latest quarterly online revision of the Oxford English Dictionary. The word first appears in 1386 a parliamentary report with the meaning “denunciation.” The history ends with the modern usage, “information fatigue,” defined as “apathy, indifference or mental exhaustion arising from exposure to too much information.”

The consequences of the information flood are not all bad. One of the creative enterprises made possible by the flood is Wikipedia, started ten years ago by Jimmy Wales. Among my friends and acquaintances, everybody distrusts Wikipedia and everybody uses it. Distrust and productive use are not incompatible. Wikipedia is the ultimate open source repository of information. Everyone is free to read it and everyone is free to write it. It contains articles in 262 languages written by several million authors. The information that it contains is totally unreliable and surprisingly accurate. It is often unreliable because many of the authors are ignorant or careless. It is often accurate because the articles are edited and corrected by readers who are better informed than the authors

Jimmy Wales hoped when he started Wikipedia that the combination of enthusiastic volunteer writers with open source information technology would cause a revolution in human access to knowledge. The rate of growth of Wikipedia exceeded his wildest dreams. Within ten years it has become the biggest storehouse of information on the planet and the noisiest battleground of conflicting opinions. It illustrates Shannon’s law of reliable communication. Shannon’s law says that accurate transmission of information is possible in a communication system with a high level of noise. Even in the noisiest system, errors can be reliably corrected and accurate information transmitted, provided that the transmission is sufficiently redundant. That is, in a nutshell, how Wikipedia works.

The information flood has also brought enormous benefits to science. The public has a distorted view of science, because children are taught in school that science is a collection of firmly established truths. In fact, science is not a collection of truths. It is a continuing exploration of mysteries. Wherever we go exploring in the world around us, we find mysteries. Our planet is covered by continents and oceans whose origin we cannot explain. Our atmosphere is constantly stirred by poorly understood disturbances that we call weather and climate. The visible matter in the universe is outweighed by a much larger quantity of dark invisible matter that we do not understand at all. The origin of life is a total mystery, and so is the existence of human consciousness. We have no clear idea how the electrical discharges occurring in nerve cells in our brains are connected with our feelings and desires and actions.

Even physics, the most exact and most firmly established branch of science, is still full of mysteries. We do not know how much of Shannon’s theory of information will remain valid when quantum devices replace classical electric circuits as the carriers of information. Quantum devices may be made of single atoms or microscopic magnetic circuits. All that we know for sure is that they can theoretically do certain jobs that are beyond the reach of classical devices. Quantum computing is still an unexplored mystery on the frontier of information theory. Science is the sum total of a great multitude of mysteries. It is an unending argument between a great multitude of voices. It resembles Wikipedia much more than it resembles the Encyclopaedia Britannica.

The rapid growth of the flood of information in the last ten years made Wikipedia possible, and the same flood made twenty-first-century science possible. Twenty-first-century science is dominated by huge stores of information that we call databases. The information flood has made it easy and cheap to build databases. One example of a twenty-first-century database is the collection of genome sequences of living creatures belonging to various species from microbes to humans. Each genome contains the complete genetic information that shaped the creature to which it belongs. The genome data-base is rapidly growing and is available for scientists all over the world to explore. Its origin can be traced to the year 1939, when Shannon wrote his Ph.D. thesis with the title “An Algebra for Theoretical Genetics.

Shannon was then a graduate student in the mathematics department at MIT. He was only dimly aware of the possible physical embodiment of genetic information. The true physical embodiment of the genome is the double helix structure of DNA molecules, discovered by Francis Crick and James Watson fourteen years later. In 1939 Shannon understood that the basis of genetics must be information, and that the information must be coded in some abstract algebra independent of its physical embodiment. Without any knowledge of the double helix, he could not hope to guess the detailed structure of the genetic code. He could only imagine that in some distant future the genetic information would be decoded and collected in a giant database that would define the total diversity of living creatures. It took only sixty years for his dream to come true.

In the twentieth century, genomes of humans and other species were laboriously decoded and translated into sequences of letters in computer memories. The decoding and translation became cheaper and faster as time went on, the price decreasing and the speed increasing according to Moore’s Law. The first human genome took fifteen years to decode and cost about a billion dollars. Now a human genome can be decoded in a few weeks and costs a few thousand dollars. Around the year 2000, a turning point was reached, when it became cheaper to produce genetic information than to understand it. Now we can pass a piece of human DNA through a machine and rapidly read out the genetic information, but we cannot read out the meaning of the information. We shall not fully understand the information until we understand in detail the processes of embryonic development that the DNA orchestrated to make us what we are.

The explosive growth of information in our human society is a part of the slower growth of ordered structures in the evolution of life as a whole. Life has for billions of years been evolving with organisms and ecosystems embodying increasing amounts of information. The evolution of life is a part of the evolution of the universe, which also evolves with increasing amounts of information embodied in ordered structures, galaxies and stars and planetary systems. In the living and in the nonliving world, we see a growth of order, starting from the featureless and uniform gas of the early universe and producing the magnificent diversity of weird objects that we see in the sky and in the rain forest. Everywhere around us, wherever we look, we see evidence of increasing order and increasing information. The technology arising from Shannon’s discoveries is only a local acceleration of the natural growth of information.

. Lord Kelvin, one of the leading physicists of that time, promoted the heat death dogma, predicting that the flow of heat from warmer to cooler objects will result in a decrease of temperature differences everywhere, until all temperatures ultimately become equal. Life needs temperature differences, to avoid being stifled by its waste heat. So life will disappear

Thanks to the discoveries of astronomers in the twentieth century, we now know that the heat death is a myth. The heat death can never happen, and there is no paradox. The best popular account of the disappearance of the paradox is a chapter, “How Order Was Born of Chaos,” in the book Creation of the Universe, by Fang Lizhi and his wife Li Shuxian.2 Fang Lizhi is doubly famous as a leading Chinese astronomer and a leading political dissident. He is now pursuing his double career at the University of Arizona.

The belief in a heat death was based on an idea that I call the cooking rule. The cooking rule says that a piece of steak gets warmer when we put it on a hot grill. More generally, the rule says that any object gets warmer when it gains energy, and gets cooler when it loses energy. Humans have been cooking steaks for thousands of years, and nobody ever saw a steak get colder while cooking on a fire. The cooking rule is true for objects small enough for us to handle. If the cooking rule is always true, then Lord Kelvin’s argument for the heat death is correct.

the cooking rule is not true for objects of astronomical size, for which gravitation is the dominant form of energy. The sun is a familiar example. As the sun loses energy by radiation, it becomes hotter and not cooler. Since the sun is made of compressible gas squeezed by its own gravitation, loss of energy causes it to become smaller and denser, and the compression causes it to become hotter. For almost all astronomical objects, gravitation dominates, and they have the same unexpected behavior. Gravitation reverses the usual relation between energy and temperature. In the domain of astronomy, when heat flows from hotter to cooler objects, the hot objects get hotter and the cool objects get cooler. As a result, temperature differences in the astronomical universe tend to increase rather than decrease as time goes on. There is no final state of uniform temperature, and there is no heat death. Gravitation gives us a universe hospitable to life. Information and order can continue to grow for billions of years in the future, as they have evidently grown in the past.

The vision of the future as an infinite playground, with an unending sequence of mysteries to be understood by an unending sequence of players exploring an unending supply of information, is a glorious vision for scientists. Scientists find the vision attractive, since it gives them a purpose for their existence and an unending supply of jobs. The vision is less attractive to artists and writers and ordinary people. Ordinary people are more interested in friends and family than in science. Ordinary people may not welcome a future spent swimming in an unending flood of information.

A darker view of the information-dominated universe was described in a famous story, “The Library of Babel,” by Jorge Luis Borges in 1941.3 Borges imagined his library, with an infinite array of books and shelves and mirrors, as a metaphor for the universe.

Gleick’s book has an epilogue entitled “The Return of Meaning,” expressing the concerns of people who feel alienated from the prevailing scientific culture. The enormous success of information theory came from Shannon’s decision to separate information from meaning. His central dogma, “Meaning is irrelevant,” declared that information could be handled with greater freedom if it was treated as a mathematical abstraction independent of meaning. The consequence of this freedom is the flood of information in which we are drowning. The immense size of modern databases gives us a feeling of meaninglessness. Information in such quantities reminds us of Borges’s library extending infinitely in all directions. It is our task as humans to bring meaning back into this wasteland. As finite creatures who think and feel, we can create islands of meaning in the sea of information. Gleick ends his book with Borges’s image of the human condition:We walk the corridors, searching the shelves and rearranging them, looking for lines of meaning amid leagues of cacophony and incoherence, reading the history of the past and of the future, collecting our thoughts and collecting the thoughts of others, and every so often glimpsing mirrors, in which we may recognize creatures of the information.

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&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.

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.

Experts in the math of probability and statistics are well aware of these problems and have for decades expressed concern about them in major journals. Over the years, hundreds of published papers have warned that science’s love affair with statistics has spawned countless illegitimate findings. In fact, if you believe what you read in the scientific literature, you shouldn’t believe what you read in the scientific literature.

“There are more false claims made in the medical literature than anybody appreciates,” he says. “There’s no question about that.”Nobody contends that all of science is wrong, or that it hasn’t compiled an impressive array of truths about the natural world. Still, any single scientific study alone is quite likely to be incorrect, thanks largely to the fact that the standard statistical system for drawing conclusions is, in essence, illogical. “A lot of scientists don’t understand statistics,” says Goodman. “And they don’t understand statistics because the statistics don’t make sense.”

In 2007, for instance, researchers combing the medical literature found numerous studies linking a total of 85 genetic variants in 70 different genes to acute coronary syndrome, a cluster of heart problems. When the researchers compared genetic tests of 811 patients that had the syndrome with a group of 650 (matched for sex and age) that didn’t, only one of the suspect gene variants turned up substantially more often in those with the syndrome — a number to be expected by chance.“Our null results provide no support for the hypothesis that any of the 85 genetic variants tested is a susceptibility factor” for the syndrome, the researchers reported in the Journal of the American Medical Association.How could so many studies be wrong? Because their conclusions relied on “statistical significance,” a concept at the heart of the mathematical analysis of modern scientific experiments.

Statistical significance is a phrase that every science graduate student learns, but few comprehend. While its origins stretch back at least to the 19th century, the modern notion was pioneered by the mathematician Ronald A. Fisher in the 1920s. His original interest was agriculture. He sought a test of whether variation in crop yields was due to some specific intervention (say, fertilizer) or merely reflected random factors beyond experimental control.Fisher first assumed that fertilizer caused no difference — the “no effect” or “null” hypothesis. He then calculated a number called the P value, the probability that an observed yield in a fertilized field would occur if fertilizer had no real effect. If P is less than .05 — meaning the chance of a fluke is less than 5 percent — the result should be declared “statistically significant,” Fisher arbitrarily declared, and the no effect hypothesis should be rejected, supposedly confirming that fertilizer works.Fisher’s P value eventually became the ultimate arbiter of credibility for science results of all sorts

But in fact, there’s no logical basis for using a P value from a single study to draw any conclusion. If the chance of a fluke is less than 5 percent, two possible conclusions remain: There is a real effect, or the result is an improbable fluke. Fisher’s method offers no way to know which is which. On the other hand, if a study finds no statistically significant effect, that doesn’t prove anything, either. Perhaps the effect doesn’t exist, or maybe the statistical test wasn’t powerful enough to detect a small but real effect.

Soon after Fisher established his system of statistical significance, it was attacked by other mathematicians, notably Egon Pearson and Jerzy Neyman. Rather than testing a null hypothesis, they argued, it made more sense to test competing hypotheses against one another. That approach also produces a P value, which is used to gauge the likelihood of a “false positive” — concluding an effect is real when it actually isn’t. What  eventually emerged was a hybrid mix of the mutually inconsistent Fisher and Neyman-Pearson approaches, which has rendered interpretations of standard statistics muddled at best and simply erroneous at worst. As a result, most scientists are confused about the meaning of a P value or how to interpret it. “It’s almost never, ever, ever stated correctly, what it means,” says Goodman.

experimental data yielding a P value of .05 means that there is only a 5 percent chance of obtaining the observed (or more extreme) result if no real effect exists (that is, if the no-difference hypothesis is correct). But many explanations mangle the subtleties in that definition. A recent popular book on issues involving science, for example, states a commonly held misperception about the meaning of statistical significance at the .05 level: “This means that it is 95 percent certain that the observed difference between groups, or sets of samples, is real and could not have arisen by chance.”

That interpretation commits an egregious logical error (technical term: “transposed conditional”): confusing the odds of getting a result (if a hypothesis is true) with the odds favoring the hypothesis if you observe that result. A well-fed dog may seldom bark, but observing the rare bark does not imply that the dog is hungry. A dog may bark 5 percent of the time even if it is well-fed all of the time. (See Box 2)

Another common error equates statistical significance to “significance” in the ordinary use of the word. Because of the way statistical formulas work, a study with a very large sample can detect “statistical significance” for a small effect that is meaningless in practical terms. A new drug may be statistically better than an old drug, but for every thousand people you treat you might get just one or two additional cures — not clinically significant. Similarly, when studies claim that a chemical causes a “significantly increased risk of cancer,” they often mean that it is just statistically significant, possibly posing only a tiny absolute increase in risk.

Statisticians perpetually caution against mistaking statistical significance for practical importance, but scientific papers commit that error often. Ziliak studied journals from various fields — psychology, medicine and economics among others — and reported frequent disregard for the distinction.

“I found that eight or nine of every 10 articles published in the leading journals make the fatal substitution” of equating statistical significance to importance, he said in an interview. Ziliak’s data are documented in the 2008 book The Cult of Statistical Significance, coauthored with Deirdre McCloskey of the University of Illinois at Chicago.

Multiplicity of mistakesEven when “significance” is properly defined and P values are carefully calculated, statistical inference is plagued by many other problems. Chief among them is the “multiplicity” issue — the testing of many hypotheses simultaneously. When several drugs are tested at once, or a single drug is tested on several groups, chances of getting a statistically significant but false result rise rapidly.

Recognizing these problems, some researchers now calculate a “false discovery rate” to warn of flukes disguised as real effects. And genetics researchers have begun using “genome-wide association studies” that attempt to ameliorate the multiplicity issue (SN: 6/21/08, p. 20).

Many researchers now also commonly report results with confidence intervals, similar to the margins of error reported in opinion polls. Such intervals, usually given as a range that should include the actual value with 95 percent confidence, do convey a better sense of how precise a finding is. But the 95 percent confidence calculation is based on the same math as the .05 P value and so still shares some of its problems.

Statistical problems also afflict the “gold standard” for medical research, the randomized, controlled clinical trials that test drugs for their ability to cure or their power to harm. Such trials assign patients at random to receive either the substance being tested or a placebo, typically a sugar pill; random selection supposedly guarantees that patients’ personal characteristics won’t bias the choice of who gets the actual treatment. But in practice, selection biases may still occur, Vance Berger and Sherri Weinstein noted in 2004 in ControlledClinical Trials. “Some of the benefits ascribed to randomization, for example that it eliminates all selection bias, can better be described as fantasy than reality,” they wrote.

Randomization also should ensure that unknown differences among individuals are mixed in roughly the same proportions in the groups being tested. But statistics do not guarantee an equal distribution any more than they prohibit 10 heads in a row when flipping a penny. With thousands of clinical trials in progress, some will not be well randomized. And DNA differs at more than a million spots in the human genetic catalog, so even in a single trial differences may not be evenly mixed. In a sufficiently large trial, unrandomized factors may balance out, if some have positive effects and some are negative. (See Box 3) Still, trial results are reported as averages that may obscure individual differences, masking beneficial or harm­ful effects and possibly leading to approval of drugs that are deadly for some and denial of effective treatment to others.

nother concern is the common strategy of combining results from many trials into a single “meta-analysis,” a study of studies. In a single trial with relatively few participants, statistical tests may not detect small but real and possibly important effects. In principle, combining smaller studies to create a larger sample would allow the tests to detect such small effects. But statistical techniques for doing so are valid only if certain criteria are met. For one thing, all the studies conducted on the drug must be included — published and unpublished. And all the studies should have been performed in a similar way, using the same protocols, definitions, types of patients and doses. When combining studies with differences, it is necessary first to show that those differences would not affect the analysis, Goodman notes, but that seldom happens. “That’s not a formal part of most meta-analyses,” he says.

Meta-analyses have produced many controversial conclusions. Common claims that antidepressants work no better than placebos, for example, are based on meta-analyses that do not conform to the criteria that would confer validity. Similar problems afflicted a 2007 meta-analysis, published in the New England Journal of Medicine, that attributed increased heart attack risk to the diabetes drug Avandia. Raw data from the combined trials showed that only 55 people in 10,000 had heart attacks when using Avandia, compared with 59 people per 10,000 in comparison groups. But after a series of statistical manipulations, Avandia appeared to confer an increased risk.

combining small studies in a meta-analysis is not a good substitute for a single trial sufficiently large to test a given question. “Meta-analyses can reduce the role of chance in the interpretation but may introduce bias and confounding,” Hennekens and DeMets write in the Dec. 2 Journal of the American Medical Association. “Such results should be considered more as hypothesis formulating than as hypothesis testing.”

Some studies show dramatic effects that don’t require sophisticated statistics to interpret. If the P value is 0.0001 — a hundredth of a percent chance of a fluke — that is strong evidence, Goodman points out. Besides, most well-accepted science is based not on any single study, but on studies that have been confirmed by repetition. Any one result may be likely to be wrong, but confidence rises quickly if that result is independently replicated.“Replication is vital,” says statistician Juliet Shaffer, a lecturer emeritus at the University of California, Berkeley. And in medicine, she says, the need for replication is widely recognized. “But in the social sciences and behavioral sciences, replication is not common,” she noted in San Diego in February at the annual meeting of the American Association for the Advancement of Science. “This is a sad situation.”

Most critics of standard statistics advocate the Bayesian approach to statistical reasoning, a methodology that derives from a theorem credited to Bayes, an 18th century English clergyman. His approach uses similar math, but requires the added twist of a “prior probability” — in essence, an informed guess about the expected probability of something in advance of the study. Often this prior probability is more than a mere guess — it could be based, for instance, on previous studies.

it basically just reflects the need to include previous knowledge when drawing conclusions from new observations. To infer the odds that a barking dog is hungry, for instance, it is not enough to know how often the dog barks when well-fed. You also need to know how often it eats — in order to calculate the prior probability of being hungry. Bayesian math combines a prior probability with observed data to produce an estimate of the likelihood of the hunger hypothesis. “A scientific hypothesis cannot be properly assessed solely by reference to the observational data,” but only by viewing the data in light of prior belief in the hypothesis, wrote George Diamond and Sanjay Kaul of UCLA’s School of Medicine in 2004 in the Journal of the American College of Cardiology. “Bayes’ theorem is ... a logically consistent, mathematically valid, and intuitive way to draw inferences about the hypothesis.” (See Box 4)

In many real-life contexts, Bayesian methods do produce the best answers to important questions. In medical diagnoses, for instance, the likelihood that a test for a disease is correct depends on the prevalence of the disease in the population, a factor that Bayesian math would take into account.

But Bayesian methods introduce a confusion into the actual meaning of the mathematical concept of “probability” in the real world. Standard or “frequentist” statistics treat probabilities as objective realities; Bayesians treat probabilities as “degrees of belief” based in part on a personal assessment or subjective decision about what to include in the calculation. That’s a tough placebo to swallow for scientists wedded to the “objective” ideal of standard statistics. “Subjective prior beliefs are anathema to the frequentist, who relies instead on a series of ad hoc algorithms that maintain the facade of scientific objectivity,” Diamond and Kaul wrote.Conflict between frequentists and Bayesians has been ongoing for two centuries. So science’s marriage to mathematics seems to entail some irreconcilable differences. Whether the future holds a fruitful reconciliation or an ugly separation may depend on forging a shared understanding of probability.“What does probability mean in real life?” the statistician David Salsburg asked in his 2001 book The Lady Tasting Tea. “This problem is still unsolved, and ... if it remains un­solved, the whole of the statistical approach to science may come crashing down from the weight of its own inconsistencies.”

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."

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

I check out the first link, the first "here" where the article says "Read here and here". I can see that there's been some sort of dispute between two New Zealand groups associated with climate change. One is New Zealand’s Climate Science Coalition (NZCSC) and the other is New Zealand’s National Institute of Water and Atmospheric Research (NIWA), but it doesn't tell me a whole lot more than I already got from the other article.

I check the second source behind that article. The second article, I now realize, is published on the website of a person called Andrew Montford with whom I've been speaking recently and who is the author of a book titled The Hockey Stick Illusion. I would not label Andrew a denialist. He makes some good points and seems to be a decent guy and geniune sceptic (This is not to suggest all denialists are outwardly dishonest; however, they do tend to be hard to reason with). Again, this article doesn't give me anything that I haven't already seen, except a link to another background source. I go there.

From this piece written up on Scoop NZNEWSUK I discover that a coalition group consisting of the NZCSC and the Climate Conversation Group (CCG) has pressured the NIWA into abandoning a set of temperature record adjustments of which the coalition dispute the validity. This was the culmination of a court proceeding in December 2010, last month. In dispute were 34 adjustments that had been made by Dr Jim Salinger to the 7SS temperature series, though I don't know what that is exactly. I also discover that there is a guy called Richard Treadgold, Convenor of the CCG, who is quoted several times. Some of the statements he makes are quoted in the articles I've already seen. They are of a somewhat snide tenor. The CSC object to the methodology used by the NIWA to adjust temperature measurements (one developed as part of a PhD thesis), which they critique in a paper in November 2009 with the title "Are we feeling warmer yet?", and are concerned about how this public agency is spending its money. I'm going to have to dig a bit deeper if I want to find out more. There is a section with links under the heading "Related Stories on Scoop". I click on a few of those.

One of these leads me to more. Of particular interest is a fairly neutral article outlining the progress of the court action. I get some more background: For the last ten years, visitors to NIWA’s official website have been greeted by a graph of the “seven-station series” (7SS), under the bold heading “New Zealand Temperature Record”. The graph covers the period from 1853 to the present, and is adorned by a prominent trend-line sloping sharply upwards. Accompanying text informs the world that “New Zealand has experienced a warming trend of approximately 0.9°C over the past 100 years.” The 7SS has been updated and used in every monthly issue of NIWA’s “Climate Digest” since January 1993. Its 0.9°C (sometimes 1.0°C) of warming has appeared in the Australia/NZ Chapter of the IPCC’s 2001 and 2007 Assessment Reports. It has been offered as sworn evidence in countless tribunals and judicial enquiries, and provides the historical base for all of NIWA’s reports to both Central and Local Governments on climate science issues and future projections.

now I can see why this is so important. The temperature record informs the conclusions of the IPCC assessment reports and provides crucial evidence for global warming.

Further down we get: NIWA announces that it has now completed a full internal examination of the Salinger adjustments in the 7SS, and has forwarded its “review papers” to its Australian counterpart, the Bureau of Meteorology (BOM) for peer review.and: So the old 7SS has already been repudiated. A replacement NZTR [New Zealand Temperature Record] is being prepared by NIWA – presumably the best effort they are capable of producing. NZCSC is about to receive what it asked for. On the face of it, there’s nothing much left for the Court to adjudicate.

NIWA has been forced to withdraw its earlier temperature record and replace it with a new one. Treadgold quite clearly states that "NIWA makes the huge admission that New Zealand has experienced hardly any warming during the last half-century" and that "the new temperature record shows no evidence of a connection with global warming." Earlier in the article he also stresses the role of the CSC in achieving these revisions, saying "after 12 months of futile attempts to persuade the public, misleading answers to questions in the Parliament from ACT and reluctant but gradual capitulation from NIWA, their relentless defence of the old temperature series has simply evaporated. They’ve finally given in, but without our efforts the faulty graph would still be there."

All this leads me to believe that if I look at the website of NIWA I will see a retraction of the earlier position and a new position that New Zealand has experienced no unusual warming. This is easy enough to check. I go there. Actually, I search for it to find the exact page. Here is the 7SS page on the NIWA site. Am I surprised that NIWA have retracted nothing and that in fact their revised graph shows similar results? Not really. However, I am somewhat surprised by this page on the Climate Conversation Group website which claims that the 7SS temperature record is as dead as the parrot in the Monty Python sketch. It says "On the eve of Christmas, when nobody was looking, NIWA declared that New Zealand had a new official temperature record (the NZT7) and whipped the 7SS off its website." However, I've already seen that this is not true. Perhaps there was once a 7SS graph and information about the temperature record on the site's homepage that can no longer be seen. I don't know. I can only speculate. I know that there is a section on the NIWA site about the 7SS temperature record that contains a number of graphs and figures and discusses recent revisions. It has been updated as recently as December 2010, last month. The NIWA page talks all about the 7SS series and has a heading that reads "Our new analysis confirms the warming trend".

The CCG page claims that the new NZT7 is not in fact a revision but rather a replacement. Although it results in a similar curve, the adjustments that were made are very different. Frankly I can't see how that matters at the end of the day. Now, I don't really know whether I can believe that the NIWA analysis is true, but what I am in no doubt of whatsoever is that the statements made by Richard Treadgold that were quoted in so many places are at best misleading. The NIWA has not changed its position in the slightest. The assertion that the NIWA have admitted that New Zealand has not warmed much since 1960 is a politician's careful argument. Both analyses showed the same result. This is a fact that NIWA have not disputed; however, they still maintain a connection to global warming. A document explaining the revisions talks about why the warming has slowed after 1960: The unusually steep warming in the 1940-1960 period is paralleled by an unusually large increase in northerly flow* during this same period. On a longer timeframe, there has been a trend towards less northerly flow (more southerly) since about 1960. However, New Zealand temperatures have continued to increase over this time, albeit at a reduced rate compared with earlier in the 20th century. This is consistent with a warming of the whole region of the southwest Pacific within which New Zealand is situated.

Denialists have taken Treadgold's misleading mantra and spread it far and wide including on Twitter and fringe websites, but it is faulty as I've just demonstrated. Why do people do this? Perhaps they are hoping that others won't check the sources. Most people don't. I hope this serves as a lesson for why you always should.

There are already three heavyweight groups that could be considered the official keepers of the world's climate data. Each publishes its own figures that feed into the UN's Intergovernmental Panel on Climate Change. Nasa's Goddard Institute for Space Studies in New York City produces a rolling estimate of the world's warming. A separate assessment comes from another US agency, the National Oceanic and Atmospheric Administration (Noaa). The third group is based in the UK and led by the Met Office. They all take readings from instruments around the world to come up with a rolling record of the Earth's mean surface temperature. The numbers differ because each group uses its own dataset and does its own analysis, but they show a similar trend. Since pre-industrial times, all point to a warming of around 0.75C.

You might think three groups was enough, but Muller rolls out a list of shortcomings, some real, some perceived, that he suspects might undermine public confidence in global warming records. For a start, he says, warming trends are not based on all the available temperature records. The data that is used is filtered and might not be as representative as it could be. He also cites a poor history of transparency in climate science, though others argue many climate records and the tools to analyse them have been public for years.

Then there is the fiasco of 2009 that saw roughly 1,000 emails from a server at the University of East Anglia's Climatic Research Unit (CRU) find their way on to the internet. The fuss over the messages, inevitably dubbed Climategate, gave Muller's nascent project added impetus. Climate sceptics had already attacked James Hansen, head of the Nasa group, for making political statements on climate change while maintaining his role as an objective scientist. The Climategate emails fuelled their protests. "With CRU's credibility undergoing a severe test, it was all the more important to have a new team jump in, do the analysis fresh and address all of the legitimate issues raised by sceptics," says Muller.

This latest point is where Muller faces his most delicate challenge. To concede that climate sceptics raise fair criticisms means acknowledging that scientists and government agencies have got things wrong, or at least could do better. But the debate around global warming is so highly charged that open discussion, which science requires, can be difficult to hold in public. At worst, criticising poor climate science can be taken as an attack on science itself, a knee-jerk reaction that has unhealthy consequences. "Scientists will jump to the defence of alarmists because they don't recognise that the alarmists are exaggerating," Muller says.

The Berkeley Earth project came together more than a year ago, when Muller rang David Brillinger, a statistics professor at Berkeley and the man Nasa called when it wanted someone to check its risk estimates of space debris smashing into the International Space Station. He wanted Brillinger to oversee every stage of the project. Brillinger accepted straight away. Since the first meeting he has advised the scientists on how best to analyse their data and what pitfalls to avoid. "You can think of statisticians as the keepers of the scientific method, " Brillinger told me. "Can scientists and doctors reasonably draw the conclusions they are setting down? That's what we're here for."

For the rest of the team, Muller says he picked scientists known for original thinking. One is Saul Perlmutter, the Berkeley physicist who found evidence that the universe is expanding at an ever faster rate, courtesy of mysterious "dark energy" that pushes against gravity. Another is Art Rosenfeld, the last student of the legendary Manhattan Project physicist Enrico Fermi, and something of a legend himself in energy research. Then there is Robert Jacobsen, a Berkeley physicist who is an expert on giant datasets; and Judith Curry, a climatologist at Georgia Institute of Technology, who has raised concerns over tribalism and hubris in climate science.

Robert Rohde, a young physicist who left Berkeley with a PhD last year, does most of the hard work. He has written software that trawls public databases, themselves the product of years of painstaking work, for global temperature records. These are compiled, de-duplicated and merged into one huge historical temperature record. The data, by all accounts, are a mess. There are 16 separate datasets in 14 different formats and they overlap, but not completely. Muller likens Rohde's achievement to Hercules's enormous task of cleaning the Augean stables.

The wealth of data Rohde has collected so far – and some dates back to the 1700s – makes for what Muller believes is the most complete historical record of land temperatures ever compiled. It will, of itself, Muller claims, be a priceless resource for anyone who wishes to study climate change. So far, Rohde has gathered records from 39,340 individual stations worldwide.

Publishing an extensive set of temperature records is the first goal of Muller's project. The second is to turn this vast haul of data into an assessment on global warming.

The big three groups – Nasa, Noaa and the Met Office – work out global warming trends by placing an imaginary grid over the planet and averaging temperatures records in each square. So for a given month, all the records in England and Wales might be averaged out to give one number. Muller's team will take temperature records from individual stations and weight them according to how reliable they are.

This is where the Berkeley group faces its toughest task by far and it will be judged on how well it deals with it. There are errors running through global warming data that arise from the simple fact that the global network of temperature stations was never designed or maintained to monitor climate change. The network grew in a piecemeal fashion, starting with temperature stations installed here and there, usually to record local weather.

Among the trickiest errors to deal with are so-called systematic biases, which skew temperature measurements in fiendishly complex ways. Stations get moved around, replaced with newer models, or swapped for instruments that record in celsius instead of fahrenheit. The times measurements are taken varies, from say 6am to 9pm. The accuracy of individual stations drift over time and even changes in the surroundings, such as growing trees, can shield a station more from wind and sun one year to the next. Each of these interferes with a station's temperature measurements, perhaps making it read too cold, or too hot. And these errors combine and build up.

This is the real mess that will take a Herculean effort to clean up. The Berkeley Earth team is using algorithms that automatically correct for some of the errors, a strategy Muller favours because it doesn't rely on human interference. When the team publishes its results, this is where the scrutiny will be most intense.

Despite the scale of the task, and the fact that world-class scientific organisations have been wrestling with it for decades, Muller is convinced his approach will lead to a better assessment of how much the world is warming. "I've told the team I don't know if global warming is more or less than we hear, but I do believe we can get a more precise number, and we can do it in a way that will cool the arguments over climate change, if nothing else," says Muller. "Science has its weaknesses and it doesn't have a stranglehold on the truth, but it has a way of approaching technical issues that is a closer approximation of truth than any other method we have."

It might not be a good sign that one prominent climate sceptic contacted by the Guardian, Canadian economist Ross McKitrick, had never heard of the project. Another, Stephen McIntyre, whom Muller has defended on some issues, hasn't followed the project either, but said "anything that [Muller] does will be well done". Phil Jones at the University of East Anglia was unclear on the details of the Berkeley project and didn't comment.

Elsewhere, Muller has qualified support from some of the biggest names in the business. At Nasa, Hansen welcomed the project, but warned against over-emphasising what he expects to be the minor differences between Berkeley's global warming assessment and those from the other groups. "We have enough trouble communicating with the public already," Hansen says. At the Met Office, Peter Stott, head of climate monitoring and attribution, was in favour of the project if it was open and peer-reviewed.

Peter Thorne, who left the Met Office's Hadley Centre last year to join the Co-operative Institute for Climate and Satellites in North Carolina, is enthusiastic about the Berkeley project but raises an eyebrow at some of Muller's claims. The Berkeley group will not be the first to put its data and tools online, he says. Teams at Nasa and Noaa have been doing this for many years. And while Muller may have more data, they add little real value, Thorne says. Most are records from stations installed from the 1950s onwards, and then only in a few regions, such as North America. "Do you really need 20 stations in one region to get a monthly temperature figure? The answer is no. Supersaturating your coverage doesn't give you much more bang for your buck," he says. They will, however, help researchers spot short-term regional variations in climate change, something that is likely to be valuable as climate change takes hold.

Despite his reservations, Thorne says climate science stands to benefit from Muller's project. "We need groups like Berkeley stepping up to the plate and taking this challenge on, because it's the only way we're going to move forwards. I wish there were 10 other groups doing this," he says.

Muller's project is organised under the auspices of Novim, a Santa Barbara-based non-profit organisation that uses science to find answers to the most pressing issues facing society and to publish them "without advocacy or agenda". Funding has come from a variety of places, including the Fund for Innovative Climate and Energy Research (funded by Bill Gates), and the Department of Energy's Lawrence Berkeley Lab. One donor has had some climate bloggers up in arms: the man behind the Charles G Koch Charitable Foundation owns, with his brother David, Koch Industries, a company Greenpeace called a "kingpin of climate science denial". On this point, Muller says the project has taken money from right and left alike.

No one who spoke to the Guardian about the Berkeley Earth project believed it would shake the faith of the minority who have set their minds against global warming. "As new kids on the block, I think they will be given a favourable view by people, but I don't think it will fundamentally change people's minds," says Thorne. Brillinger has reservations too. "There are people you are never going to change. They have their beliefs and they're not going to back away from them."

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Pseudo-modernism also encompasses contemporary news programmes, whose content increasingly consists of emails or text messages sent in commenting on the news items. The terminology of ‘interactivity’ is equally inappropriate here, since there is no exchange: instead, the viewer or listener enters – writes a segment of the programme – then departs, returning to a passive role. Pseudo-modernism also includes computer games, which similarly place the individual in a context where they invent the cultural content, within pre-delineated limits. The content of each individual act of playing the game varies according to the particular player.

The pseudo-modern cultural phenomenon par excellence is the internet. Its central act is that of the individual clicking on his/her mouse to move through pages in a way which cannot be duplicated, inventing a pathway through cultural products which has never existed before and never will again. This is a far more intense engagement with the cultural process than anything literature can offer, and gives the undeniable sense (or illusion) of the individual controlling, managing, running, making up his/her involvement with the cultural product. Internet pages are not ‘authored’ in the sense that anyone knows who wrote them, or cares. The majority either require the individual to make them work, like Streetmap or Route Planner, or permit him/her to add to them, like Wikipedia, or through feedback on, for instance, media websites. In all cases, it is intrinsic to the internet that you can easily make up pages yourself (eg blogs).

Where once special effects were supposed to make the impossible appear credible, CGI frequently [inadvertently] works to make the possible look artificial, as in much of Lord of the Rings or Gladiator. Battles involving thousands of individuals have really happened; pseudo-modern cinema makes them look as if they have only ever happened in cyberspace.

Similarly, television in the pseudo-modern age favours not only reality TV (yet another unapt term), but also shopping channels, and quizzes in which the viewer calls to guess the answer to riddles in the hope of winning money.

The purely ‘spectacular’ function of television, as with all the arts, has become a marginal one: what is central now is the busy, active, forging work of the individual who would once have been called its recipient. In all of this, the ‘viewer’ feels powerful and is indeed necessary; the ‘author’ as traditionally understood is either relegated to the status of the one who sets the parameters within which others operate, or becomes simply irrelevant, unknown, sidelined; and the ‘text’ is characterised both by its hyper-ephemerality and by its instability. It is made up by the ‘viewer’, if not in its content then in its sequence – you wouldn’t read Middlemarch by going from page 118 to 316 to 401 to 501, but you might well, and justifiably, read Ceefax that way.

A pseudo-modern text lasts an exceptionally brief time. Unlike, say, Fawlty Towers, reality TV programmes cannot be repeated in their original form, since the phone-ins cannot be reproduced, and without the possibility of phoning-in they become a different and far less attractive entity.

If scholars give the date they referenced an internet page, it is because the pages disappear or get radically re-cast so quickly. Text messages and emails are extremely difficult to keep in their original form; printing out emails does convert them into something more stable, like a letter, but only by destroying their essential, electronic state.

The cultural products of pseudo-modernism are also exceptionally banal

Much text messaging and emailing is vapid in comparison with what people of all educational levels used to put into letters.

A triteness, a shallowness dominates all.

In music, the pseudo-modern supersedingof the artist-dominated album as monolithic text by the downloading and mix-and-matching of individual tracks on to an iPod, selected by the listener, was certainly prefigured by the music fan’s creation of compilation tapes a generation ago. But a shift has occurred, in that what was a marginal pastime of the fan has become the dominant and definitive way of consuming music, rendering the idea of the album as a coherent work of art, a body of integrated meaning, obsolete.

To a degree, pseudo-modernism is no more than a technologically motivated shift to the cultural centre of something which has always existed (similarly, metafiction has always existed, but was never so fetishised as it was by postmodernism). Television has always used audience participation, just as theatre and other performing arts did before it; but as an option, not as a necessity: pseudo-modern TV programmes have participation built into them.

Whereas postmodernism called ‘reality’ into question, pseudo-modernism defines the real implicitly as myself, now, ‘interacting’ with its texts. Thus, pseudo-modernism suggests that whatever it does or makes is what is reality, and a pseudo-modern text may flourish the apparently real in an uncomplicated form: the docu-soap with its hand-held cameras (which, by displaying individuals aware of being regarded, give the viewer the illusion of participation); The Office and The Blair Witch Project, interactive pornography and reality TV; the essayistic cinema of Michael Moore or Morgan Spurlock.

whereas postmodernism favoured the ironic, the knowing and the playful, with their allusions to knowledge, history and ambivalence, pseudo-modernism’s typical intellectual states are ignorance, fanaticism and anxiety

pseudo-modernism lashes fantastically sophisticated technology to the pursuit of medieval barbarism – as in the uploading of videos of beheadings onto the internet, or the use of mobile phones to film torture in prisons. Beyond this, the destiny of everyone else is to suffer the anxiety of getting hit in the cross-fire. But this fatalistic anxiety extends far beyond geopolitics, into every aspect of contemporary life; from a general fear of social breakdown and identity loss, to a deep unease about diet and health; from anguish about the destructiveness of climate change, to the effects of a new personal ineptitude and helplessness, which yield TV programmes about how to clean your house, bring up your children or remain solvent.

Pseudo-modernism belongs to a world pervaded by the encounter between a religiously fanatical segment of the United States, a largely secular but definitionally hyper-religious Israel, and a fanatical sub-section of Muslims scattered across the planet: pseudo-modernism was not born on 11 September 2001, but postmodernism was interred in its rubble.

pseudo-modernist communicates constantly with the other side of the planet, yet needs to be told to eat vegetables to be healthy, a fact self-evident in the Bronze Age. He or she can direct the course of national television programmes, but does not know how to make him or herself something to eat – a characteristic fusion of the childish and the advanced, the powerful and the helpless. For varying reasons, these are people incapable of the “disbelief of Grand Narratives” which Lyotard argued typified postmodernists

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?

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.

religion becomes its own secular catalyst, or, rather, secularization itself is the result of religion. This approach will mature in the most elaborate formulation of what Habermas calls the “linguistification of the sacred,” in volume two of The Theory of Communicative Action. There, basing himself on Durkheim and Mead, Habermas shows how ritual practices and religious worldviews release rational imperatives through the establishment of a communicative grammar that conditions how believers can and should interact with each other, and how they relate to the idea of a supreme being. Habermas writes: worldviews function as a kind of drive belt that transforms the basic religious consensus into the energy of social solidarity and passes it on to social institutions, thus giving them a moral authority. [. . .] Whereas ritual actions take place at a pregrammatical level, religious worldviews are connected with full-fledged communicative actions.

The thrust of Habermas’s argumentation in this section of The Theory of Communicative Action is to show that religion is the source of the normative binding power of ethical and moral commandments. Yet there is an ambiguity here. While the contents of worldviews may be sublimated into the normative, binding of social systems, it is not entirely clear that the structure, or the grammar, of religious worldviews is itself exhausted. Indeed, in “A Genealogical Analysis of the Cognitive Content of Morality,” Habermas resolves this ambiguity by claiming that the horizontal relationship among believers and the vertical relationship between each believer and God shape the structure of our moral relationship to our neighbour, but now under two corresponding aspects: that of solidarity and that of justice. Here, the grammar of one’s religious relationship to God and the corresponding community of believers are like the exoskeleton of a magnificent species, which, once the religious worldviews contained in them have desiccated under the impact of the forces of secularization, leave behind a casing to be used as a structuring shape for other contents.

Metaphysical thinking, which for Habermas has become untenable by the very logic of philosophical development, is characterized by three aspects: identity thinking, or the philosophy of origins that postulates the correspondence between being and thought; the doctrine of ideas, which becomes the foundation for idealism, which in turn postulates a tension between what is perceived and what can be conceptualized; and a concomitant strong concept of theory, where the bios theoretikos takes on a quasi-sacred character, and where philosophy becomes the path to salvation through dedication to a life of contemplation. By “postmetaphysical” Habermas means the new self-understanding of reason that we are able to obtain after the collapse of the Hegelian idealist system—the historicization of reason, or the de-substantivation that turns it into a procedural rationality, and, above all, its humbling. It is noteworthy that one of the main aspects of the new postmetaphysical constellation is that in the wake of the collapse of metaphysics, philosophy is forced to recognize that it must co-exist with religious practices and language: Philosophy, even in its postmetaphysical form, will be able neither to replace nor to repress religion as long as religious language is the bearer of semantic content that is inspiring and even indispensable, for this content eludes (for the time being?) the explanatory force of philosophical language and continues to resist translation into reasoning discourses.

metaphysical thinking either surrendered philosophy to religion or sought to eliminate religion altogether. In contrast, postmetaphysical thinking recognizes that philosophy can neither replace nor dismissively reject religion, for religion continues to articulate a language whose syntax and content elude philosophy, but from which philosophy continues to derive insights into the universal dimensions of human existence.

Habermas claims that even moral discourse cannot translate religious language without something being lost: “Secular languages which only eliminate the substance once intended leave irritations. When sin was converted to culpability, and the breaking of divine commands to an offence against human laws, something was lost.” Still, Habermas’s concern with religion is no longer solely philosophical, nor merely socio-theoretical, but has taken on political urgency. Indeed, he now asks whether modern rule of law and constitutional democracies can generate the motivational resources that nourish them and make them durable. In a series of essays, now gathered in Between Naturalism and Religion, as well as in his Europe: The Faltering Project, Habermas argues that as we have become members of a world society (Weltgesellschaft), we have also been forced to adopt a societal “post-secular self-consciousness.” By this term Habermas does not mean that secularization has come to an end, and even less that it has to be reversed. Instead, he now clarifies that secularization refers very specifically to the secularization of state power and to the general dissolution of metaphysical, overarching worldviews (among which religious views are to be counted). Additionally, as members of a world society that has, if not a fully operational, at least an incipient global public sphere, we have been forced to witness the endurance and vitality of religion. As members of this emergent global public sphere, we are also forced to recognize the plurality of forms of secularization. Secularization did not occur in one form, but in a variety of forms and according to different chronologies.

through a critical reading of Rawls, Habermas has begun to translate the postmetaphysical orientation of modern philosophy into a postsecular self-understanding of modern rule of law societies in such a way that religious citizens as well as secular citizens can co-exist, not just by force of a modus vivendi, but out of a sincere mutual respect. “Mutual recognition implies, among other things, that religious and secular citizens are willing to listen and to learn from each other in public debates. The political virtue of treating each other civilly is an expression of distinctive cognitive attitudes.” The cognitive attitudes Habermas is referring to here are the very cognitive competencies that are distinctive of modern, postconventional social agents. Habermas’s recent work on religion, then, is primarily concerned with rescuing for the modern liberal state those motivational and moral resources that it cannot generate or provide itself. At the same time, his recent work is concerned with foregrounding the kind of ethical and moral concerns, preoccupations, and values that can guide us between the Scylla of a society administered from above by the system imperatives of a global economy and political power and the Charybdis of a technological frenzy that places us on the slippery slope of a liberally sanctioned eugenics.

But other researchers, both with and without Templeton grants, say that they find the foundation remarkably open and non-dogmatic. "The Templeton Foundation has never in my experience pressured, suggested or hinted at any kind of ideological slant," says Michael Shermer, editor of Skeptic, a magazine that debunks pseudoscience, who was hired by the foundation to edit an essay series entitled 'Does science make belief in God obsolete?'

The debate highlights some of the challenges facing the Templeton Foundation after the death of its founder in July 2008, at the age of 95.

With the help of a $528-million bequest from Templeton, the foundation has been radically reframing its research programme. As part of that effort, it is reducing its emphasis on religion to make its programmes more palatable to the broader scientific community. Like many of his generation, Templeton was a great believer in progress, learning, initiative and the power of human imagination — not to mention the free-enterprise system that allowed him, a middle-class boy from Winchester, Tennessee, to earn billions of dollars on Wall Street. The foundation accordingly allocates 40% of its annual grants to programmes with names such as 'character development', 'freedom and free enterprise' and 'exceptional cognitive talent and genius'.

Unlike most of his peers, however, Templeton thought that the principles of progress should also apply to religion. He described himself as "an enthusiastic Christian" — but was also open to learning from Hinduism, Islam and other religious traditions. Why, he wondered, couldn't religious ideas be open to the type of constructive competition that had produced so many advances in science and the free market?

That question sparked Templeton's mission to make religion "just as progressive as medicine or astronomy".

Early Templeton prizes had nothing to do with science: the first went to the Catholic missionary Mother Theresa of Calcutta in 1973.

By the 1980s, however, Templeton had begun to realize that fields such as neuroscience, psychology and physics could advance understanding of topics that are usually considered spiritual matters — among them forgiveness, morality and even the nature of reality. So he started to appoint scientists to the prize panel, and in 1985 the award went to a research scientist for the first time: Alister Hardy, a marine biologist who also investigated religious experience. Since then, scientists have won with increasing frequency.

"There's a distinct feeling in the research community that Templeton just gives the award to the most senior scientist they can find who's willing to say something nice about religion," says Harold Kroto, a chemist at Florida State University in Tallahassee, who was co-recipient of the 1996 Nobel Prize in Chemistry and describes himself as a devout atheist.

Yet Templeton saw scientists as allies. They had what he called "the humble approach" to knowledge, as opposed to the dogmatic approach. "Almost every scientist will agree that they know so little and they need to learn," he once said.

Templeton wasn't interested in funding mainstream research, says Barnaby Marsh, the foundation's executive vice-president. Templeton wanted to explore areas — such as kindness and hatred — that were not well known and did not attract major funding agencies. Marsh says Templeton wondered, "Why is it that some conflicts go on for centuries, yet some groups are able to move on?"

Templeton's interests gave the resulting list of grants a certain New Age quality (See Table 1). For example, in 1999 the foundation gave $4.6 million for forgiveness research at the Virginia Commonwealth University in Richmond, and in 2001 it donated $8.2 million to create an Institute for Research on Unlimited Love (that is, altruism and compassion) at Case Western Reserve University in Cleveland, Ohio. "A lot of money wasted on nonsensical ideas," says Kroto. Worse, says Coyne, these projects are profoundly corrupting to science, because the money tempts researchers into wasting time and effort on topics that aren't worth it. If someone is willing to sell out for a million dollars, he says, "Templeton is there to oblige him".

At the same time, says Marsh, the 'dean of value investing', as Templeton was known on Wall Street, had no intention of wasting his money on junk science or unanswerables such as whether God exists. So before pursuing a scientific topic he would ask his staff to get an assessment from appropriate scholars — a practice that soon evolved into a peer-review process drawing on experts from across the scientific community.

Because Templeton didn't like bureaucracy, adds Marsh, the foundation outsourced much of its peer review and grant giving. In 1996, for example, it gave $5.3 million to the American Association for the Advancement of Science (AAAS) in Washington DC, to fund efforts that work with evangelical groups to find common ground on issues such as the environment, and to get more science into seminary curricula. In 2006, Templeton gave $8.8 million towards the creation of the Foundational Questions Institute (FQXi), which funds research on the origins of the Universe and other fundamental issues in physics, under the leadership of Anthony Aguirre, an astrophysicist at the University of California, Santa Cruz, and Max Tegmark, a cosmologist at the Massachusetts Institute of Technology in Cambridge.

But external peer review hasn't always kept the foundation out of trouble. In the 1990s, for example, Templeton-funded organizations gave book-writing grants to Guillermo Gonzalez, an astrophysicist now at Grove City College in Pennsylvania, and William Dembski, a philosopher now at the Southwestern Baptist Theological Seminary in Fort Worth, Texas. After obtaining the grants, both later joined the Discovery Institute — a think-tank based in Seattle, Washington, that promotes intelligent design. Other Templeton grants supported a number of college courses in which intelligent design was discussed. Then, in 1999, the foundation funded a conference at Concordia University in Mequon, Wisconsin, in which intelligent-design proponents confronted critics. Those awards became a major embarrassment in late 2005, during a highly publicized court fight over the teaching of intelligent design in schools in Dover, Pennsylvania. A number of media accounts of the intelligent design movement described the Templeton Foundation as a major supporter — a charge that Charles Harper, then senior vice-president, was at pains to deny.

Some foundation officials were initially intrigued by intelligent design, Harper told The New York Times. But disillusionment set in — and Templeton funding stopped — when it became clear that the theory was part of a political movement from the Christian right wing, not science. Today, the foundation website explicitly warns intelligent-design researchers not to bother submitting proposals: they will not be considered.

Avowedly antireligious scientists such as Coyne and Kroto see the intelligent-design imbroglio as a symptom of their fundamental complaint that religion and science should not mix at all. "Religion is based on dogma and belief, whereas science is based on doubt and questioning," says Coyne, echoing an argument made by many others. "In religion, faith is a virtue. In science, faith is a vice." The purpose of the Templeton Foundation is to break down that wall, he says — to reconcile the irreconcilable and give religion scholarly legitimacy.

Foundation officials insist that this is backwards: questioning is their reason for being. Religious dogma is what they are fighting. That does seem to be the experience of many scientists who have taken Templeton money. During the launch of FQXi, says Aguirre, "Max and I were very suspicious at first. So we said, 'We'll try this out, and the minute something smells, we'll cut and run.' It never happened. The grants we've given have not been connected with religion in any way, and they seem perfectly happy about that."

John Cacioppo, a psychologist at the University of Chicago, also had concerns when he started a Templeton-funded project in 2007. He had just published a paper with survey data showing that religious affiliation had a negative correlation with health among African-Americans — the opposite of what he assumed the foundation wanted to hear. He was bracing for a protest when someone told him to look at the foundation's website. They had displayed his finding on the front page. "That made me relax a bit," says Cacioppo.

Yet, even scientists who give the foundation high marks for openness often find it hard to shake their unease. Sean Carroll, a physicist at the California Institute of Technology in Pasadena, is willing to participate in Templeton-funded events — but worries about the foundation's emphasis on research into 'spiritual' matters. "The act of doing science means that you accept a purely material explanation of the Universe, that no spiritual dimension is required," he says.

It hasn't helped that Jack Templeton is much more politically and religiously conservative than his father was. The foundation shows no obvious rightwards trend in its grant-giving and other activities since John Templeton's death — and it is barred from supporting political activities by its legal status as a not-for-profit corporation. Still, many scientists find it hard to trust an organization whose president has used his personal fortune to support right-leaning candidates and causes such as the 2008 ballot initiative that outlawed gay marriage in California.

Scientists' discomfort with the foundation is probably inevitable in the current political climate, says Scott Atran, an anthropologist at the University of Michigan in Ann Arbor. The past 30 years have seen the growing power of the Christian religious right in the United States, the rise of radical Islam around the world, and religiously motivated terrorist attacks such as those in the United States on 11 September 2001. Given all that, says Atran, many scientists find it almost impossible to think of religion as anything but fundamentalism at war with reason.

the foundation has embraced the theme of 'science and the big questions' — an open-ended list that includes topics such as 'Does the Universe have a purpose?'

Towards the end of Templeton's life, says Marsh, he became increasingly concerned that this reaction was getting in the way of the foundation's mission: that the word 'religion' was alienating too many good scientists.

The peer-review and grant-making system has also been revamped: whereas in the past the foundation ran an informal mix of projects generated by Templeton and outside grant seekers, the system is now organized around an annual list of explicit funding priorities.

The foundation is still a work in progress, says Jack Templeton — and it always will be. "My father believed," he says, "we were all called to be part of an ongoing creative process. He was always trying to make people think differently." "And he always said, 'If you're still doing today what you tried to do two years ago, then you're not making progress.'"&nbsp;

Agar directly tackles Hughes’ ideas of a “democratic transhumanism.” Here as post-humans and humans live shoulder to shoulder in wonderful harmony, all persons have access to the technologies they want in order to promote their own flourishing.&nbsp; Under girding all of this is the belief that no human should feel pressurised to become enhance. Agar finds no comfort with this and instead can foresee a situation where it would be very difficult for humans to ‘choose’ to remain human.&nbsp; The pressure to radically enhance would be considerable given the fact that the radically enhanced would no doubt be occupying the positions of power in society and would consider the moral obligation to utilise to the full enhancement techniques as being a moral imperative for the good of society.&nbsp; For those who were able to withstand then a new underclass would no doubt emerge between the enhanced and the un-enhanced. This is precisely the kind of society which Hughes appears to be overly optimistic will not emerge but which is more akin to Lee Silver’s prediction of the future with the distinction made between the "GenRich" and the "naturals”.&nbsp; This being the case, the author proposes that we have two options: radical enhancement is either enforced across the board or banned outright. It is the latter option which Agar favours but crucially does not elaborate further on so it is unclear as to how he would attempt such a ban given the complexity of the issue. This is disappointing as any general initial reflections which the author felt able to offer would have added to the discussion and added further strength to his line of argument.

A Transhuman Manifesto The final focus for Agar is James Hughes, who published his transhumanist manifesto Citizen Cyborg in 2004. Given the direct connection with politics and public policy this for me was a particularly interesting read. The basic premise to Hughes argument is that once humans and post humans recognise each other as citizens then this will mark the point at which they will be able to get along with each other.

Agar takes to task the argument Bostrom made with Toby Ord, concerning claims against enhancement. Bostrom and Ord argue that it boils down to a preference for the status quo; current human intellects and life spans are preferred and deemed best because they are what we have now and what we are familiar with (p. 134).&nbsp; Agar discusses the fact that in his view, Bostrom falls into a focalism – focusing on and magnifying the positives whilst ignoring the negative implications.&nbsp; Moreover, Agar goes onto develop and reiterate his earlier point that the sort of radical enhancements Bostrom et al enthusiastically support and promote take us beyond what is human so they are no longer human. It therefore cannot be said to be human enhancement given the fact that the traits or capacities that such enhancement afford us would be in many respects superior to ours, but they would not be ours.

With his law of accelerating returns and talk of the Singularity Ray Kurzweil proposes that we are speeding towards a time when our outdated systems of neurons and synapses will be traded for far more efficient electronic circuits, allowing us to become artificially super-intelligent and transferring our minds from brains into machines.

Having laid out the main ideas and thinking behind Kurzweil’s proposals, Agar makes the perceptive comment that despite the apparent appeal of greater processing power it would nevertheless be no longer human. Introducing chips to the human body and linking into the human nervous system to computers as per Ray Kurzweil’s proposals will prove interesting but it goes beyond merely creating a copy of us in order to that future replication and uploading can take place. Rather it will constitute something more akin to an upgrade. Electrochemical signals that the brain use to achieve thought travel at 100 metres per second. This is impressive but contrast this with the electrical signals in a computer which travel at 300 million metres per second then the distinction is clear. If the predictions are true how will such radically enhanced and empowered beings live not only the unenhanced but also what will there quality of life really be? In response, Agar favours something what he calls “rational biological conservatism” (pg. 57) where we set limits on how intelligent we can become in light of the fact that it will never be rational to us for human beings to completely upload their minds onto computers.

Agar then proceeds to argue that in the pursuit of Kurzweil enhanced capacities and capabilities we might accidentally undermine capacities of equal value. This line of argument would find much sympathy from those who consider human organisms in “ecological” terms, representing a profound interconnectedness which when interfered with presents a series of unknown and unexpected consequences. In other words, our specifies-specific form of intelligence may well be linked to species-specific form of desire. Thus, if we start building upon and enhancing our capacity to protect and promote deeply held convictions and beliefs then due to the interconnectedness, it may well affect and remove our desire to perform such activities (page 70). Agar’s subsequent discussion and reference to the work of Jerry Foder, philosopher and cognitive scientist is particularly helpful in terms of the functioning of the mind by modules and the implications of human-friendly AI verses human-unfriendly AI.

In terms of the author’s discussion of Aubrey de Grey, what is refreshing to read from the outset is the author’s clear grasp of Aubrey’s ideas and motivation. Some make the mistake of thinking he is the man who wants to live forever, when in actual fact this is not the case.&nbsp; De Grey wants to reverse the ageing process - Strategies for Engineered Negligible Senescence (SENS) so that people are living longer and healthier lives. Establishing this clear distinction affords the author the opportunity to offer more grounded critiques of de Grey’s than some of his other critics. The author makes plain that de Grey’s immediate goal is to achieve longevity escape velocity (LEV), where anti-ageing therapies add years to life expectancy faster than age consumes them.

In weighing up the benefits of living significantly longer lives, Agar posits a compelling argument that I had not fully seen before. In terms of risk, those radically enhanced to live longer may actually be the most risk adverse and fearful people to live. Taking the example of driving a car, a forty year-old senescing human being who gets into their car to drive to work and is involved in a fatal accident “stands to lose, at most, a few healthy, youthful years and a slightly larger number of years with reduced quality” (p.116). In stark contrast should a negligibly senescent being who drives a car and is involved in an accident resulting in their death, stands to lose on average one thousand, healthy, youthful years (p.116). &nbsp;

De Grey’s response to this seems a little flippant; with the end of ageing comes an increased sense of risk-aversion so the desire for risky activity such as driving will no longer be prevalent. Moreover, plus because we are living for longer we will not be in such a hurry to get to places!&nbsp; Virtual reality comes into its own at this point as a means by which the negligibly senescent being ‘adrenaline junkie’ can be engaged with activities but without the associated risks. But surely the risk is part of the reason why they would want to engage in snow boarding, bungee jumping et al in the first place. De Grey’s strategy seemingly fails to appreciate the extent to which human beings want “direct” contact with the “real” world.

Continuing this idea further though, Agar’s subsequent discussion of the role of fire-fighters is an interesting one.&nbsp; A negligibly senescent fire fighter may stand to loose more when they are trapped in a burning inferno but being negligibly senescent means that they are better fire-fighters by virtue of increase vitality. Having recently heard de Grey speak and had the privilege of discussing his ideas further with him, Agar’s discussion of De Grey were a particular highlight of the book and made for an engaging discussion. Whilst expressing concern and doubt in relation to De Grey’s ideas, Agar is nevertheless quick and gracious enough to acknowledge that if such therapies could be achieved then De Grey is probably the best person to comment on and achieve such therapies given the depth of knowledge and understanding that he has built up in this area.

In this New York Times’ article, “Teachers Wonder, Why the scorn?“, the writer notes the often scathing comments from counter-demonstrators – “Oh you pathetic teachers, read the online comments and placards of counterdemonstrators.&nbsp;You are glorified baby sitters who leave work at 3 p.m. You deserve minimum wage.” What had begun as an ostensibly ‘economic reform’ targeted at teachers’ unions has gradually transmogrified into a kind of “character attack” to this section of American society – teachers are people who wage violent protests (thanks to borrowed footage from the West Coast) and they are undeserving of their economic benefits, and indeed treat these privileges as ‘rights’. The ‘war’ is waged on multiple fronts, economic, political, social, psychological even — or at least one gets this sort of picture from reading these articles.

as Singaporeans with a uniquely Singaporean work ethic, we may perceive functioning ‘trade unions’ as those institutions in the so-called “West” where they amass lots of membership, then hold the government ‘hostage’ in order to negotiate higher wages and benefits. Think of trade unions in the Singaporean context, and I think of SIA pilots. And of LKY’s various firm and stern comments on those issues. Think of trade unions and I think of strikes in France, in South Korea, when I was younger, and of my mum saying, “How irresponsible!” before flipping the TV channel.

The reason why I think the teachers’ protests should not be seen solely as an issue about trade-unions, and evaluated myopically and naively in terms of whether trade unions are ‘good’ or ‘bad’ is because the protests feature in a larger political context with the billionaire Koch brothers at the helm, financing and directing much of what has transpired in recent weeks. Or at least according to certain articles which I present here.

In this NYT article entitled “Billionaire Brothers’ Money Plays Role in Wisconsin Dispute“, the writer noted that Koch Industries had been “one of the biggest contributors to the election campaign of Gov.&nbsp;Scott Walker of Wisconsin, a Republican who has championed the proposed cuts.” Further, the president of Americans for Prosperity, a nonprofit group financed by the Koch brothers, had reportedly addressed counter-demonstrators last Saturday saying that “the cuts were not only necessary, but they also represented the start of a much-needed nationwide move to slash public-sector union benefits.” and in his own words -“ ‘We are going to bring fiscal sanity back to this great nation’ ”. All this rhetoric would be more convincing to me if they weren’t funded by the same two billionaires who financially enabled Walker’s governorship.

I now refer you to a long piece by Jane Mayer for The New Yorker titled, “Covert Operations: The billionaire brothers who are waging a war against Obama“. According to her, “The Kochs are longtime libertarians who believe in drastically lower personal and corporate taxes, minimal social services for the needy, and much less oversight of industry—especially environmental regulation. These views dovetail with the brothers’ corporate interests.”

Their libertarian modus operandi involves great expenses in lobbying, in political contributions and in setting up think tanks. From 2006-2010, Koch Industries have led energy companies in political contributions; “[i]n the second quarter of 2010, David Koch was the biggest individual contributor to the Republican Governors Association, with a million-dollar donation.”&nbsp;More statistics, or at least those of the non-anonymous donation records, can be found on page 5 of Mayer’s piece.

Naturally, the Democrats also have their billionaire donors, most notably in the form of George Soros. Mayer writes that he has made ‘generous private contributions to various Democratic campaigns, including Obama’s.” Yet what distinguishes him from the Koch brothers here is, as Michael Vachon, his spokesman, argued, ‘that Soros’s giving is transparent, and that “none of his contributions are in the service of his own economic interests.” ‘ Of course, this must be taken with a healthy dose of salt, but I will note here that in Charles Ferguson’s documentary&nbsp;Inside Job, which was about the 2008 financial crisis,&nbsp;George Soros was one of those interviewed who was not portrayed negatively. (My review of it is&nbsp;here.)

Of the Koch brothers’ political investments, what interested me more was the US’ “first libertarian thinktank”, the Cato Institute. Mayer writes, ‘When President Obama, in a 2008 speech, described the science on global warming as “beyond dispute,” the Cato Institute took out a full-page ad in the&nbsp;Times to contradict him. Cato’s resident scholars have relentlessly criticized political attempts to stop global warming as expensive, ineffective, and unnecessary. Ed Crane, the Cato Institute’s founder and president, told [Mayer] that “global-warming theories give the government more control of the economy.” ‘

K Street refers to a major street in Washington, D.C. where major think tanks, lobbyists and advocacy groups are located.

with recent developments as the Citizens United case where corporations are now ‘persons’ and have no caps in political contributions, the Koch brothers are ever better-positioned to take down their perceived big, bad government and carry out their ideological agenda as sketched in Mayer’s piece

with much important news around the world jostling for our attention – earthquake in Japan, Middle East revolutions – the passing of an anti-union bill (which finally happened today, for better or for worse) in an American state is unlikely to make a headline able to compete with natural disasters and revolutions. Then, to quote Wisconsin Governor Scott Walker during that prank call conversation, “Sooner or later the media stops finding it [the teacher protests] interesting.”

What remains more puzzling for me is why the American public seems to buy into the Koch-funded libertarian rhetoric. Mayer writes, ‘ “Income inequality in America is greater than it has been since the nineteen-twenties, and since the seventies the tax rates of the wealthiest have fallen more than those of the middle class. Yet the brothers’ message has evidently resonated with voters: a recent poll found that fifty-five per cent of Americans agreed that Obama is a socialist.” I suppose that not knowing who is funding the political rhetoric makes it easier for the public to imbibe it.

But the problem is deeper than simply intellectual inertia. It goes back, ultimately, to the unconsidered differentiations we make—at every moment when we distinguish among objects—between those in the foreground of our consciousness and the background places in which the objects happen to be situated. Moreover, this distinction creates a hierarchy of objects. We are conscious not only of the skin that encloses and defines the object, but of bits and pieces of that object, each of which must have its own “skin.” That is the problem of anatomization. A car has a motor and brakes and a transmission and an outer body that, at appropriate moments, become separate objects of our consciousness, objects that at least some knowledgeable person recognizes as coherent entities.

Evelyn Fox Keller sees “The Mirage of a Space Between Nature and Nurture” as a consequence of our false division of the world into living objects without sufficient consideration of the external milieu in which they are embedded, since organisms help create effective environments through their own life activities.

The central point of her analysis has been that gender itself (as opposed to sex) is socially constructed, and that construction has influenced the development of science:If there is a single point on which all feminist scholarship…has converged, it is the importance of recognizing the social construction of gender…. All of my work on gender and science proceeds from this basic recognition. My endeavor has been to call attention to the ways in which the social construction of a binary opposition between “masculine” and “feminine” has influenced the social construction of science.

major critical concern of Fox Keller’s present book is the widespread attempt to partition in some quantitative way the contribution made to human variation by differences in biological inheritance, that is, differences in genes, as opposed to differences in life experience. She wants to make clear a distinction between analyzing the relative strength of the causes of variation among individuals and groups, an analysis that is coherent in principle, and simply assigning the relative contributions of biological and environmental causes to the value of some character in an individual

It is, for example, all very well to say that genetic variation is responsible for 76 percent of the observed variation in adult height among American women while the remaining 24 percent is a consequence of differences in nutrition. The implication is that if all variation in nutrition were abolished then 24 percent of the observed height variation among individuals in the population in the next generation would disappear. To say, however, that 76 percent of Evelyn Fox Keller’s height was caused by her genes and 24 percent by her nutrition does not make sense. The nonsensical implication of trying to partition the causes of her individual height would be that if she never ate anything she would still be three quarters as tall as she is.

In fact, Keller is too optimistic about the assignment of causes of variation even when considering variation in a population. As she herself notes parenthetically, the assignment of relative proportions of population variation to different causes in a population depends on there being no specific interaction between the causes.

Keller’s rather casual treatment of the interaction between causal factors in the case of the drummers, despite her very great sophistication in analyzing the meaning of variation, is a symptom of a fault that is deeply embedded in the analytic training and thinking of both natural and social scientists. If there are several variable factors influencing some phenomenon, how are we to assign the relative importance to each in determining total variation? Let us take an extreme example. Suppose that we plant seeds of each of two different varieties of corn in two different locations with the following results measured in bushels of corn produced (see Table 1). There are differences between the varieties in their yield from location to location and there are differences between locations from variety to variety. So, both variety and location matter. But there is no average variation between locations when averaged over varieties or between varieties when averaged over locations. Just by knowing the variation in yield associated with location and variety separately does not tell us which factor is the more important source of variation; nor do the facts of location and variety exhaust the description of that variation.

After the Academy dropped Borda’s method, it plumped for a simple suggestion by the astronomer and mathematician Pierre-Simon Laplace, who was an important contributor to the theory of probability. Laplace’s rule insisted on an over-all majority: at least half the votes plus one. If no candidate achieved this, nobody was elected to the Academy.

Another early advocate of proportional representation was John Stuart Mill, who, in 1861, wrote about the critical distinction between “government of the whole people by the whole people, equally represented,” which was the ideal, and “government of the whole people by a mere majority of the people exclusively represented,” which is what winner-takes-all elections produce. (The minority that Mill was most concerned to protect was the “superior intellects and characters,” who he feared would be swamped as more citizens got the vote.)

The key to proportional representation is to enlarge constituencies so that more than one winner is elected in each, and then try to align the share of seats won by a party with the share of votes it receives. These days, a few small countries, including Israel and the Netherlands, treat their entire populations as single constituencies, and thereby get almost perfectly proportional representation. Some places require a party to cross a certain threshold of votes before it gets any seats, in order to filter out extremists.

The main criticisms of proportional representation are that it can lead to unstable coalition governments, because more parties are successful in elections, and that it can weaken the local ties between electors and their representatives. Conveniently for its critics, and for its defenders, there are so many flavors of proportional representation around the globe that you can usually find an example of whatever point you want to make. Still, more than three-quarters of the world’s rich countries seem to manage with such schemes.

The alternative voting method that will be put to a referendum in Britain is not proportional representation: it would elect a single winner in each constituency, and thus steer clear of what foreigners put up with. Known in the United States as instant-runoff voting, the method was developed around 1870 by William Ware

In instant-runoff elections, voters rank all or some of the candidates in order of preference, and votes may be transferred between candidates. The idea is that your vote may count even if your favorite loses. If any candidate gets more than half of all the first-preference votes, he or she wins, and the game is over. But, if there is no majority winner, the candidate with the fewest first-preference votes is eliminated. Then the second-preference votes of his or her supporters are distributed to the other candidates. If there is still nobody with more than half the votes, another candidate is eliminated, and the process is repeated until either someone has a majority or there are only two candidates left, in which case the one with the most votes wins. Third, fourth, and lower preferences will be redistributed if a voter’s higher preferences have already been transferred to candidates who were eliminated earlier.

At first glance, this is an appealing approach: it is guaranteed to produce a clear winner, and more voters will have a say in the election’s outcome. Look more closely, though, and you start to see how peculiar the logic behind it is. Although more people’s votes contribute to the result, they do so in strange ways. Some people’s second, third, or even lower preferences count for as much as other people’s first preferences. If you back the loser of the first tally, then in the subsequent tallies your second (and maybe lower) preferences will be added to that candidate’s first preferences. The winner’s pile of votes may well be a jumble of first, second, and third preferences.

Such transferrable-vote elections can behave in topsy-turvy ways: they are what mathematicians call “non-monotonic,” which means that something can go up when it should go down, or vice versa. Whether a candidate who gets through the first round of counting will ultimately be elected may depend on which of his rivals he has to face in subsequent rounds, and some votes for a weaker challenger may do a candidate more good than a vote for that candidate himself. In short, a candidate may lose if certain voters back him, and would have won if they hadn’t. Supporters of instant-runoff voting say that the problem is much too rare to worry about in real elections, but recent work by Robert Norman, a mathematician at Dartmouth, suggests otherwise. By Norman’s calculations, it would happen in one in five close contests among three candidates who each have between twenty-five and forty per cent of first-preference votes. With larger numbers of candidates, it would happen even more often. It’s rarely possible to tell whether past instant-runoff elections have gone topsy-turvy in this way, because full ballot data aren’t usually published. But, in Burlington’s 2006 and 2009 mayoral elections, the data were published, and the 2009 election did go topsy-turvy.

Kenneth Arrow, an economist at Stanford, examined a set of requirements that you’d think any reasonable voting system could satisfy, and proved that nothing can meet them all when there are more than two candidates. So designing elections is always a matter of choosing a lesser evil. When the Royal Swedish Academy of Sciences awarded Arrow a Nobel Prize, in 1972, it called his result “a rather discouraging one, as regards the dream of a perfect democracy.” Szpiro goes so far as to write that “the democratic world would never be the same again,

There is something of a loophole in Arrow’s demonstration. His proof applies only when voters rank candidates; it would not apply if, instead, they rated candidates by giving them grades. First-past-the-post voting is, in effect, a crude ranking method in which voters put one candidate in first place and everyone else last. Similarly, in the standard forms of proportional representation voters rank one party or group of candidates first, and all other parties and candidates last. With rating methods, on the other hand, voters would give all or some candidates a score, to say how much they like them. They would not have to say which is their favorite—though they could in effect do so, by giving only him or her their highest score—and they would not have to decide on an order of preference for the other candidates.

One such method is widely used on the Internet—to rate restaurants, movies, books, or other people’s comments or reviews, for example. You give numbers of stars or points to mark how much you like something. To convert this into an election method, count each candidate’s stars or points, and the winner is the one with the highest average score (or the highest total score, if voters are allowed to leave some candidates unrated). This is known as range voting, and it goes back to an idea considered by Laplace at the start of the nineteenth century. It also resembles ancient forms of acclamation in Sparta. The more you like something, the louder you bash your shield with your spear, and the biggest noise wins. A recent variant, developed by two mathematicians in Paris, Michel Balinski and Rida Laraki, uses familiar language rather than numbers for its rating scale. Voters are asked to grade each candidate as, for example, “Excellent,” “Very Good,” “Good,” “Insufficient,” or “Bad.” Judging politicians thus becomes like judging wines, except that you can drive afterward.

Range and approval voting deal neatly with the problem of vote-splitting: if a voter likes Nader best, and would rather have Gore than Bush, he or she can approve Nader and Gore but not Bush. Above all, their advocates say, both schemes give voters more options, and would elect the candidate with the most over-all support, rather than the one preferred by the largest minority. Both can be modified to deliver forms of proportional representation.

Whether such ideas can work depends on how people use them. If enough people are carelessly generous with their approval votes, for example, there could be some nasty surprises. In an unlikely set of circumstances, the candidate who is the favorite of more than half the voters could lose. Parties in an approval election might spend less time attacking their opponents, in order to pick up positive ratings from rivals’ supporters, and critics worry that it would favor bland politicians who don’t stand for anything much. Defenders insist that such a strategy would backfire in subsequent elections, if not before, and the case of Ronald Reagan suggests that broad appeal and strong views aren’t mutually exclusive.

Why are the effects of an unfamiliar electoral system so hard to puzzle out in advance? One reason is that political parties will change their campaign strategies, and voters the way they vote, to adapt to the new rules, and such variables put us in the realm of behavior and culture. Meanwhile, the technical debate about electoral systems generally takes place in a vacuum from which voters’ capriciousness and local circumstances have been pumped out. Although almost any alternative voting scheme now on offer is likely to be better than first past the post, it’s unrealistic to think that one voting method would work equally well for, say, the legislature of a young African republic, the Presidency of an island in Oceania, the school board of a New England town, and the assembly of a country still scarred by civil war. If winner takes all is a poor electoral system, one size fits all is a poor way to pick its replacements.

Mathematics can suggest what approaches are worth trying, but it can’t reveal what will suit a particular place, and best deliver what we want from a democratic voting system: to create a government that feels legitimate to people—to reconcile people to being governed, and give them reason to feel that, win or lose (especially lose), the game is fair.

Ruse’s somewhat surprising yet intriguing claim is that “before Charles Darwin, evolution was an epiphenomenon of the ideology of [social] progress, a pseudoscience and seen as such. Liked by some for that very reason, despised by others for that very reason.”

Indeed, the link between evolution and the idea of human social-cultural progress was very strong before Darwin, and was one of the main things Darwin got rid of.

The encyclopedist Denis Diderot was typical in this respect: “The Tahitian is at a primary stage in the development of the world, the European is at its old age. The interval separating us is greater than that between the new-born child and the decrepit old man.” Similar nonsensical views can be found in Lamarck, Erasmus, and Chambers, the anonymous author of The Vestiges of the Natural History of Creation, usually considered the last protoscientific book on evolution to precede the Origin.

On the other side of the divide were social conservatives like the great anatomist George Cuvier, who rejected the idea of evolution — according to Ruse — not as much on scientific grounds as on political and ideological ones. Indeed, books like Erasmus’ Zoonomia and Chambers’ Vestiges were simply not much better than pseudoscientific treatises on, say, alchemy before the advent of modern chemistry.

people were well aware of this sorry situation, so much so that astronomer John Herschel referred to the question of the history of life as “the mystery of mysteries,” a phrase consciously adopted by Darwin in the Origin. Darwin set out to solve that mystery under the influence of three great thinkers: Newton, the above mentioned Herschel, and the philosopher William Whewell (whom Darwin knew and assiduously frequented in his youth)

Darwin was a graduate of the University of Cambridge, which had also been Newton’s home. Chuck got drilled early on during his Cambridge education with the idea that good science is about finding mechanisms (vera causa), something like the idea of gravitational attraction underpinning Newtonian mechanics. He reflected that all the talk of evolution up to then — including his grandfather’s — was empty, without a mechanism that could turn the idea into a scientific research program.

The second important influence was Herschel’s Preliminary Discourse on the Study of Natural Philosophy, published in 1831 and read by Darwin shortly thereafter, in which Herschel sets out to give his own take on what today we would call the demarcation problem, i.e. what methodology is distinctive of good science. One of Herschel’s points was to stress the usefulness of analogical reasoning

Finally, and perhaps most crucially, Darwin also read (twice!) Whewell’s History of the Inductive Sciences, which appeared in 1837. In it, Whewell sets out his notion that good scientific inductive reasoning proceeds by a consilience of ideas, a situation in which multiple independent lines of evidence point to the same conclusion.

the first part of the Origin, where Darwin introduces the concept of natural selection by way of analogy with artificial selection can be read as the result of Herschel’s influence (natural selection is the vera causa of evolution)

the second part of the book, constituting Darwin's famous “long argument,” applies Whewell’s method of consilience by bringing in evidence from a number of disparate fields, from embryology to paleontology to biogeography.

What, then, happened to the strict coupling of the ideas of social and biological progress that had preceded Darwin? While he still believed in the former, the latter was no longer an integral part of evolution, because natural selection makes things “better” only in a relative fashion. There is no meaningful sense in which, say, a large brain is better than very fast legs or sharp claws, as long as you still manage to have dinner and avoid being dinner by the end of the day (or, more precisely, by the time you reproduce).