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Mashable always give misleading news with misleading titles and ridiculous analysis. In France, you cannot do neither good nor bad ad for any brand or company in a TV program (unless you pay your ad slot of course). With the coming of social networks, people advertise their page and by the way facebook and twitter. That’s why the ban comes to say that facebook and twitter are also brands and companies like others. Actually, you can say “Facebook” and “twitter” and whatever you want… in any TV program in France, but you cannot advertise for them. So please be less simplistic and a little more percise in you articles.

By this logic no personal brand (i.e. Brad Pitt, Angelina Jolie, and so on) could be mentioned without them paying for it. And by this logic, public relations could not exist as a profession in France.

Teenagers become adults: I may not win any scientific breakthrough awards for this statement, but people are missing the boat on this piece of the puzzle. What happens when a teenager becomes an adult in the workplace? Not only do they dress, speak, and act differently - they use different approaches to communicate, too. The first thing a new employee typical gets is…an e-mail address. And guess what? They use it, even if they have been reliant on social, IM, and texting for their primary communication channels. They will correspond for work via e-mail and opt in to e-mails from their favorite brands (including brands that they certainly did not like as a teenager). They likely will also "Like" their favorite companies on Facebook, follow them on Twitter, and opt in to SMS offers as well. They will also expect different value and information in each of these channels.

The problems with reliable access to analytics and measurement information is by no means limited to Twitter. Facebook data is also tightly controlled. With Facebook, privacy controls built into the API are designed to prevent mass data scraping. This is absolutely the right decision. However, a reality of social media measurement is that Facebook Insights isn’t always reachable and the data collected from the tool is sometimes inaccurate.It’s no surprise there’s a disconnect between the data that marketers and community managers want and the data that can be reliably accessed. Twitter and Facebook were both designed as tools for consumers. It’s only been in the last two years that the platform ecosystem aimed at serving large brands and companies

The data that companies like Twitter, Facebook and Foursquare collect are some of their most valuable assets. It isn’t fair to expect a free ride or first-class access to the data by anyone who wants it.Having said that, more transparency about what data is available to services and brands is needed and necessary.We’re just scraping the service of what social media monitoring, measurement and management tools can do. To get to the next level, it’s important that we all question who has access to the firehose.

We Need More Transparency for How to Access and Connect with Data

it is not quite true, even among tenured professors in the humanities, that idea-mongers can entirely ignore "external" checks. Even academics want to be respectable, which means they can't entirely ignore the realities that others notice. There were lots of academics talking about the achievements of socialism in the 1970s (I can remember them) but very few talking that way after China and Russia repudiated these fantasies.

THE MOST DISTORTING ASPECT of Sowell's account is that, in focusing so much on the delusions of intellectuals, he leaves us more confused about what motivates the rest of society. In a characteristic passage, Sowell protests that "intellectuals...have sought to replace the groups into which people have sorted themselves with groupings created and imposed by the intelligentsia. Ties of family, religion, and patriotism, for example, have long been rated as suspect or detrimental by the intelligentsia, and new ties that intellectuals have created, such as class -- and more recently 'gender' -- have been projected as either more real or more important."

There's no disputing the claim that most "intellectuals" -- surely most professors in the humanities-are down on "patriotism" and "religion" and probably even "family." But how did people get to be patriotic and religious in the first place? In Sowell's account, they just "sorted themselves" -- as if by the invisible hand of the market.

Let's put aside all the violence and intimidation that went into building so many nations and so many faiths in the past. What is it, even today, that makes people revere this country (or some other); what makes people adhere to a particular faith or church? Don't inspiring words often move people? And those who arrange these words -- aren't they doing something similar to what Sowell says intellectuals do? Is it really true, when it comes to embracing national or religious loyalties, that "the proof of the pudding is in the eating"?

Even when it comes to commercial products, people don't always want to be guided by mundane considerations of reliable performance. People like glamour, prestige, associations between the product and things they otherwise admire. That's why companies spend so much on advertising. And that's part of the reason people are willing to pay more for brand names -- to enjoy the associations generated by advertising. Even advertising plays on assumptions about what is admirable and enticing-assumptions that may change from decade to decade, as background opinions change. How many products now flaunt themselves as "green" -- and how many did so 20 years ago?

If we closed down universities and stopped subsidizing intellectual publications, would people really judge every proposed policy by external results? Intellectuals tend to see what they expect to see, as Sowell's examples show -- but that's true of almost everyone. We have background notions about how the world works that help us make sense of what we experience. We might have distorted and confused notions, but we don't just perceive isolated facts. People can improve in their understanding, developing background understandings that are more defined or more reliable. That's part of what makes people interested in the ideas of intellectuals -- the hope of improving their own understanding.

On Sowell's account, we wouldn't need the contributions of a Friedrich Hayek -- or a Thomas Sowell -- if we didn't have so many intellectuals peddling so many wrong-headed ideas. But the wealthier the society, the more it liberates individuals to make different choices and the more it can afford to indulge even wasteful or foolish choices. I'd say that means not that we have less need of intellectuals, but more need of better ones. 

that is tragedy because just at the moment when we celebrate the product of these two wonders—Zuckerberg and the Internet—working together, policymakers are conspiring ferociously with old world powers to remove the conditions for this success. As “network neutrality” gets bargained away—to add insult to injury, by an administration that was elected with the promise to defend it—the opportunities for the Zuckerbergs of tomorrow will shrink. And as they do, we will return more to the world where success depends upon permission. And privilege. And insiders. And where fewer turn their souls to inventing the next great idea.

Zuckerberg is a rightful hero of our time. I want my kids to admire him. To his credit, Sorkin gives him the only lines of true insight in the film: In response to the twins’ lawsuit, he asks, does “a guy who makes a really good chair owe money to anyone who ever made a chair?” And to his partner who signed away his ownership in Facebook: “You’re gonna blame me because you were the business head of the company and you made a bad business deal with your own company?” Friends who know Zuckerberg say such insight is common. No doubt his handlers are panicked that the film will tarnish the brand. He should listen less to these handlers. As I looked around at the packed theater of teens and twenty-somethings, there was no doubt who was in the right, however geeky and clumsy and sad. That generation will judge this new world. If, that is, we allow that new world to continue to flourish.

The MIT researchers’ paper, however, suggests that the danger of information cascades may not be as dire as it previously seemed.

a mathematical model that describes attempts by members of a social network to make binary decisions — such as which of two brands of cell phone to buy — on the basis of decisions made by their neighbors. The model assumes that for all members of the population, there is a single right decision: one of the cell phones is intrinsically better than the other. But some members of the network have bad information about which is which.

The MIT researchers analyzed the propagation of information under two different conditions. In one case, there’s a cap on how much any one person can know about the state of the world: even if one cell phone is intrinsically better than the other, no one can determine that with 100 percent certainty. In the other case, there’s no such cap. There’s debate among economists and information theorists about which of these two conditions better reflects reality, and Kleinberg suggests that the answer may vary depending on the type of information propagating through the network. But previous models had suggested that, if there is a cap, information cascades are almost inevitable.

if there’s no cap on certainty, an expanding social network will eventually converge on an accurate representation of the state of the world; that wasn’t a big surprise. But they also showed that in many common types of networks, even if there is a cap on certainty, convergence will still occur.

people in the past have looked at it using more myopic models,” says Acemoglu. “They would be averaging type of models: so my opinion is an average of the opinions of my neighbors’.” In such a model, Acemoglu says, the views of people who are “oversampled” — who are connected with a large enough number of other people — will end up distorting the conclusions of the group as a whole.

What we’re doing is looking at it in a much more game-theoretic manner, where individuals are realizing where the information comes from. So there will be some correction factor,” Acemoglu says. “If I’m seeing you, your action, and I’m seeing Munzer’s action, and I also know that there is some probability that you might have observed Munzer, then I discount his opinion appropriately, because I know that I don’t want to overweight it. And that’s the reason why, even though you have these influential agents — it might be that Munzer is everywhere, and everybody observes him — that still doesn’t create a herd on his opinion.”

the new paper leaves a few salient questions unanswered, such as how quickly the network will converge on the correct answer, and what happens when the model of agents’ knowledge becomes more complex.

the MIT researchers begin to address both questions. One paper examines rate of convergence, although Dahleh and Acemoglu note that that its results are “somewhat weaker” than those about the conditions for convergence. Another paper examines cases in which different agents make different decisions given the same information: some people might prefer one type of cell phone, others another. In such cases, “if you know the percentage of people that are of one type, it’s enough — at least in certain networks — to guarantee learning,” Dahleh says. “I don’t need to know, for every individual, whether they’re for it or against it; I just need to know that one-third of the people are for it, and two-thirds are against it.” For instance, he says, if you notice that a Chinese restaurant in your neighborhood is always half-empty, and a nearby Indian restaurant is always crowded, then information about what percentages of people prefer Chinese or Indian food will tell you which restaurant, if either, is of above-average or below-average quality.

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.

user-rating will have the tendency of giving prominence to widely-shared opinion. Comments expressing unpopular opinions will get fewer “stars” from other readers and sink in display priority. In theory, it doesn’t have to be so. People may very well give “stars” to well-thought-out comments that argue cogently for a view they don’t agree with, lauding the quality of expression rather than the conclusion, but let’s get real. Most people like to hear what they already believe. That being the case, the effect of such a scheme would be to crowd out unpopular opinion even if they have merit; it produces a majoritarian effect in newspapers’ comments sections.

it is open to abuse in that a small group of people wanting to push a particular opinion could repeatedly vote for a certain comment, thereby giving it increased ranking and more prominent display. Such action would be akin to astroturfing.

The value of discussion lies not in hearing what we already know or what we already believe in. It lies in hearing alternative arguments and learning new facts. Structuring a discussion forum by giving prominence to merely popular opinion just makes it an echo chamber. The greater public purpose is better served when contrary opinion is aired. That is why I disagree with a scheme whereby users apply ratings and prominence is given to highly-rated comments.

nonymous comments have their uses. Most obviously, there will be times when whistle-blowing serves the public purpose, and so, even if displayed less prominently, they should still be allowed.

thanks to Wikileaks, the world has been enlightened to the fact that the Obama administration not only refused to prosecute these individuals itself, it also exerted pressure on the governments of Germany and Spain not to prosecute, or even indict, any of the torturers or war criminals from the Bush dictatorship.

we see many right-wing commentators demanding that Assange be hunted down, with some even calling for his murder, on the grounds that he may have endangered lives by releasing confidential government documents. Yet, for the right-wing, this apparently was not a concern when the late columnist Robert Novak "outed" CIA agent Valerie Plame after her husband Joseph Wilson authored an OP-ED piece in The New York Times criticizing the motivations for waging war against Iraq. Even though there was evidence of involvement within the highest echelons of the Bush dictatorship, only one person, Lewis "Scooter" Libby, was indicted and convicted of "outing" Plame to Novak. And, despite the fact that this "outing" potentially endangered the lives of Plame's overseas contacts, Bush commuted Libby's thirty-month prison sentence, calling it "excessive."

Why the disparity? The answer is simple: The Plame "outing" served the interests of the military-industrial complex and helped to conceal the Bush dictatorship's lies, tortures and war crimes, while Wikileaks not only exposed such evils, but also revealed how Obama's administration, and Obama himself, are little more than "snake oil" merchants pontificating about government accountability while undermining it at every turn.

When the United States Constitution was being created, a conflict emerged between delegates who wanted a strong federal government (the Federalists) and those who wanted a weak federal government (the anti-Federalists). Although the Federalists won the day, one of the most distinguished anti-Federalists, George Mason, refused to sign the new Constitution, sacrificing in the process, some historians say, a revered place amongst America's founding fathers. Two of Mason's concerns were that the Constitution did not contain a Bill of Rights, and that the presidential pardon powers would allow corrupt presidents to pardon people who had committed crimes on presidential orders.

Mason's concerns about the abuse of the pardon powers were eventually proven right when Gerald Ford pardoned Richard Nixon, when Ronald Reagan pardoned FBI agents convicted of authorizing illegal break-ins, and when George H.W. Bush pardoned six individuals involved in the Iran-Contra Affair.

Mason was also proven right after the Federalists realized that the States would not ratify the Constitution unless a Bill of Rights was added. But this was done begrudgingly, as demonstrated by America's second president, Federalist John Adams, who essentially destroyed the right to freedom of speech via the Alien and Sedition Acts, which made it a crime to say, write or publish anything critical of the United States government.

Most criminals break laws that others have created, and people who assist in exposing or apprehending them are usually lauded as heroes. But with the "espionage" acts, the criminals themselves have actually created laws to conceal their crimes, and exploit these laws to penalize people who expose them.

The problem with America's system of government is that it has become too easy, and too convenient, to simply stamp "classified" on documents that reveal acts of government corruption, cover-up, mendacity and malfeasance, or to withhold them "in the interest of national security." Given this web of secrecy, is it any wonder why so many Americans are still skeptical about the "official" versions of the John F. Kennedy or Martin Luther King Jr. assassinations, or the events surrounding the attacks of September 11, 2001?

I want to believe that the Wikileaks documents will change America for the better. But what undoubtedly will happen is a repetition of the past: those who expose government crimes and cover-ups will be prosecuted or branded as criminals; new laws will be passed to silence dissent; new Liebermans will arise to intimidate the corporate-controlled media; and new ways will be found to conceal the truth.

What Wikileaks has done is make people understand why so many Americans are politically apathetic and content to lose themselves in one or more of the addictions American culture offers, be it drugs, alcohol, the Internet, video games, celebrity gossip, text-messaging-in essence anything that serves to divert attention from the harshness of reality.

the evils committed by those in power can be suffocating, and the sense of powerlessness that erupts from being aware of these evils can be paralyzing, especially when accentuated by the knowledge that government evildoers almost always get away with their crimes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Three months later I was summoned to appear before an Examining Magistrate in Paris based on a complaint of criminal defamation lodged by the author. Why Paris you might ask? Indeed. The author of the book was an Israeli academic. The book was in English. The publisher was Dutch. The reviewer was a distinguished German professor. The review was published on a New York website.

Beyond doubt, once a text or image go online, they become available worldwide, including France. But should that alone give jurisdiction to French courts in circumstances such as this? Does the fact that the author of the book, it turned out, retained her French nationality before going to live and work in Israel make a difference? Libel tourism – libel terrorism to some — is typically associated with London, where notorious high legal fees and punitive damages coerce many to throw in the towel even before going to trial. Paris, as we would expect, is more egalitarian and less materialist. It is very plaintiff friendly.

In France an attack on one’s honor is taken as seriously as a bodily attack. Substantively, if someone is defamed, the bad faith of the defamer is presumed just as in our system, if someone slaps you in the face, it will be assumed that he intended to do so. Procedurally it is open to anyone who feels defamed, to avoid the costly civil route, and simply lodge a criminal complaint.  At this point the machinery of the State swings into action. For the defendant it is not without cost, I discovered. Even if I win I will not recover my considerable legal expenses and conviction results in a fine the size of which may depend on one’s income (the egalitarian reflex at its best). But money is not the principal currency here. It is honor and shame. If I lose, I will stand convicted of a crime, branded a criminal. The complainant will not enjoy a windfall as in London, but considerable moral satisfaction. The chilling effect on book reviewing well beyond France will be considerable.

The case was otiose for two reasons: It was in our view an egregious instance of ‘forum shopping,’ legalese for libel tourism. We wanted it thrown out. But if successful, the Court would never get to the merits –  and it was important to challenge this hugely dangerous attack on academic freedom and liberty of expression. Reversing custom, we specifically asked the Court not to examine our jurisdictional challenge as a preliminary matter but to join it to the case on the merits so that it would have the possibility to pronounce on both issues.

The trial was impeccable by any standard with which I am familiar. The Court, comprised three judges specialized in defamation and the Public Prosecutor. Being a criminal case within the Inquisitorial System, the case began by my interrogation by the President of the Court. I was essentially asked to explain the reasons for refusing to remove the article. The President was patient with my French – fluent but bad!  I was then interrogated by the other judges, the Public Prosecutor and the lawyers for the complainant. The complainant was then subjected to the same procedure after which the lawyers made their (passionate) legal arguments. The Public Prosecutor then expressed her Opinion to the Court. I was allowed the last word. It was a strange mélange of the criminal and civil virtually unknown in the Common Law world. The procedure was less formal, aimed at establishing the truth, and far less hemmed down by rules of evidence and procedure. Due process was definitely served. It was a fair trial.

we steadfastly refused to engage the complainants challenges to the veracity of the critical statements made by the reviewer. The thrust of our argument was that absent bad faith and malice, so long as the review in question addressed the book and did not make false statement about the author such as plagiarism, it should be shielded from libel claims, let alone criminal libel. Sorting out of the truth should be left to academic discourse, even if academic discourse has its own biases and imperfections.

Other Anonymous targets include the Church of Scientology and, most recently, cyber-security company HBGary, which attempted to infiltrate Anonymous. In response, the lose-knit hacker group released 71,800 HBGary emails, which revealed highly dubious activities by the company, almost instantaneously destroying HBGary’s reputation and potentially setting it on a path to financial ruin.

At the other end of the spectrum, scare stories are - of course - a stalwart of media science. Based on minimal evidence and expanded with poor understanding of its significance, they help perform the most crucial function for the media, which is selling you, the reader, to their advertisers. The MMR disaster was a fantasy entirely of the media's making (www.badscience.net/?p=23), which failed to go away. In fact the Daily Mail is still publishing hysterical anti-immunisation stories, including one calling the pneumococcus vaccine a "triple jab", presumably because they misunderstood that the meningitis, pneumonia, and septicaemia it protects against are all caused by the same pneumococcus bacteria (www.badscience.net/?p=118).

people periodically come up to me and say, isn't it funny how that Wakefield MMR paper turned out to be Bad Science after all? And I say: no. The paper always was and still remains a perfectly good small case series report, but it was systematically misrepresented as being more than that, by media that are incapable of interpreting and reporting scientific data.

Once journalists get their teeth into what they think is a scare story, trivial increases in risk are presented, often out of context, but always using one single way of expressing risk, the "relative risk increase", that makes the danger appear disproportionately large (www.badscience.net/?p=8).

he media obsession with "new breakthroughs": a more subtly destructive category of science story. It's quite understandable that newspapers should feel it's their job to write about new stuff. But in the aggregate, these stories sell the idea that science, and indeed the whole empirical world view, is only about tenuous, new, hotly-contested data

Articles about robustly-supported emerging themes and ideas would be more stimulating, of course, than most single experimental results, and these themes are, most people would agree, the real developments in science. But they emerge over months and several bits of evidence, not single rejiggable press releases. Often, a front page science story will emerge from a press release alone, and the formal academic paper may never appear, or appear much later, and then not even show what the press reports claimed it would (www.badscience.net/?p=159).

there was an interesting essay in the journal PLoS Medicine, about how most brand new research findings will turn out to be false (www.tinyurl.com/ceq33). It predictably generated a small flurry of ecstatic pieces from humanities graduates in the media, along the lines of science is made-up, self-aggrandising, hegemony-maintaining, transient fad nonsense; and this is the perfect example of the parody hypothesis that we'll see later. Scientists know how to read a paper. That's what they do for a living: read papers, pick them apart, pull out what's good and bad.

there is no useful information in most science stories. A piece in the Independent on Sunday from January 11 2004 suggested that mail-order Viagra is a rip-off because it does not contain the "correct form" of the drug. I don't use the stuff, but there were 1,147 words in that piece. Just tell me: was it a different salt, a different preparation, a different isomer, a related molecule, a completely different drug? No idea. No room for that one bit of information.

Remember all those stories about the danger of mobile phones? I was on holiday at the time, and not looking things up obsessively on PubMed; but off in the sunshine I must have read 15 newspaper articles on the subject. Not one told me what the experiment flagging up the danger was. What was the exposure, the measured outcome, was it human or animal data? Figures? Anything? Nothing. I've never bothered to look it up for myself, and so I'm still as much in the dark as you.

Because papers think you won't understand the "science bit", all stories involving science must be dumbed down, leaving pieces without enough content to stimulate the only people who are actually going to read them - that is, the people who know a bit about science.

Compare this with the book review section, in any newspaper. The more obscure references to Russian novelists and French philosophers you can bang in, the better writer everyone thinks you are. Nobody dumbs down the finance pages.

Statistics are what causes the most fear for reporters, and so they are usually just edited out, with interesting consequences. Because science isn't about something being true or not true: that's a humanities graduate parody. It's about the error bar, statistical significance, it's about how reliable and valid the experiment was, it's about coming to a verdict, about a hypothesis, on the back of lots of bits of evidence.

science journalists somehow don't understand the difference between the evidence and the hypothesis. The Times's health editor Nigel Hawkes recently covered an experiment which showed that having younger siblings was associated with a lower incidence of multiple sclerosis. MS is caused by the immune system turning on the body. "This is more likely to happen if a child at a key stage of development is not exposed to infections from younger siblings, says the study." That's what Hawkes said. Wrong! That's the "Hygiene Hypothesis", that's not what the study showed: the study just found that having younger siblings seemed to be somewhat protective against MS: it didn't say, couldn't say, what the mechanism was, like whether it happened through greater exposure to infections. He confused evidence with hypothesis (www.badscience.net/?p=112), and he is a "science communicator".

how do the media work around their inability to deliver scientific evidence? They use authority figures, the very antithesis of what science is about, as if they were priests, or politicians, or parent figures. "Scientists today said ... scientists revealed ... scientists warned." And if they want balance, you'll get two scientists disagreeing, although with no explanation of why (an approach at its most dangerous with the myth that scientists were "divided" over the safety of MMR). One scientist will "reveal" something, and then another will "challenge" it

The danger of authority figure coverage, in the absence of real evidence, is that it leaves the field wide open for questionable authority figures to waltz in. Gillian McKeith, Andrew Wakefield, Kevin Warwick and the rest can all get a whole lot further, in an environment where their authority is taken as read, because their reasoning and evidence is rarely publicly examined.

it also reinforces the humanities graduate journalists' parody of science, for which we now have all the ingredients: science is about groundless, incomprehensible, didactic truth statements from scientists, who themselves are socially powerful, arbitrary, unelected authority figures. They are detached from reality: they do work that is either wacky, or dangerous, but either way, everything in science is tenuous, contradictory and, most ridiculously, "hard to understand".

This misrepresentation of science is a direct descendant of the reaction, in the Romantic movement, against the birth of science and empiricism more than 200 years ago; it's exactly the same paranoid fantasy as Mary Shelley's Frankenstein, only not as well written. We say descendant, but of course, the humanities haven't really moved forward at all, except to invent cultural relativism, which exists largely as a pooh-pooh reaction against science. And humanities graduates in the media, who suspect themselves to be intellectuals, desperately need to reinforce the idea that science is nonsense: because they've denied themselves access to the most significant developments in the history of western thought for 200 years, and secretly, deep down, they're angry with themselves over that.

had a good spirited row with an eminent science journalist, who kept telling me that scientists needed to face up to the fact that they had to get better at communicating to a lay audience. She is a humanities graduate. "Since you describe yourself as a science communicator," I would invariably say, to the sound of derisory laughter: "isn't that your job?" But no, for there is a popular and grand idea about, that scientific ignorance is a useful tool: if even they can understand it, they think to themselves, the reader will. What kind of a communicator does that make you?

Science is done by scientists, who write it up. Then a press release is written by a non-scientist, who runs it by their non-scientist boss, who then sends it to journalists without a science education who try to convey difficult new ideas to an audience of either lay people, or more likely - since they'll be the ones interested in reading the stuff - people who know their way around a t-test a lot better than any of these intermediaries. Finally, it's edited by a whole team of people who don't understand it. You can be sure that at least one person in any given "science communication" chain is just juggling words about on a page, without having the first clue what they mean, pretending they've got a proper job, their pens all lined up neatly on the desk.