Group items tagged

Cognitive errors result from incomplete information or the inability to analyze the information that is available. These cognitive errors can be classified as either belief perseverance or processing errors

Processing errors occur when an individual fails to manage and organize information properly, which can be due in part to the mental effort required to compute and analyze data.

Conservatism bias, where people emphasize original, pre-existing information over new data.

Base rate neglect is the opposite effect, whereby people put too little emphasis on the original information. 

Confirmation bias, where people seek information that affirms existing beliefs while discounting or discarding information that might contradict them.

Anchoring and Adjustment happens when somebody fixates on a target number, such as the result of a calculation or valuation.

Hindsight bias occurs when people perceive actual outcomes as reasonable and expected, but only after the fact.

Sample size neglect is an error made when people infer too much from a too-small sample size.

Mental accounting is when people earmark certain funds for certain goals and keep them separate. When this happens, the risk and reward of projects undertaken to achieve these goals are not considered as an overall portfolio and the effect of one on another is ignored.

Availability bias, or recency bias skews perceived future probabilities based on memorable past events

Framing bias is when a person will process the same information differently depending on how it is presented and received.

Cognitive errors in the way people process and analyze information can lead them to make irrational decisions which can negatively impact business or investing decisions

. These information processing errors could have arisen to help primitive humans survive in a time before money or finance came into existence.

Last summer, Olympics ticketholders were baffled when the London 2012 Olympic Games committee oversold the synchronized swimming event by thousands of tickets--a hapless clerk had entered "20,000" instead of "10,000" in a spreadsheet cell.

A year prior, the town of Framingham, Massachusetts, announced that it would request $600,000 in state aid to cover a budget shortfall caused by miscalculating "monstrous spreadsheets.

The term “fallacy” is not a precise term. One reason is that it is ambiguous. It can refer either to (a) a kind of error in an argument, (b) a kind of error in reasoning (including arguments, definitions, explanations, and so forth), (c) a false belief, or (d) the cause of any of the previous errors including what are normally referred to as “rhetorical techniques.” Philosophers who are researchers in fallacy theory prefer to emphasize (a), but their lead is often not followed in textbooks and public discussion.

Consulting the list below will give a general idea of the kind of error involved in passages to which the fallacy name is applied. However, simply applying the fallacy name to a passage cannot substitute for a detailed examination of the passage and its context or circumstances because there are many instances of reasoning to which a fallacy name might seem to apply, yet, on further examination, it is found that in these circumstances the reasoning is really not fallacious.

The WHO, CDC and other bureaucracies initially failed to quickly realize that the benefits of masks compound, simply because two people are wearing them and you have to look at the interaction.

Let us say (to simplify) that masks reduce both transmission and reception to p. What effect on the R0(that is, the rate of spreading of the infection)?

Simply the naive approach (used by the CDC/WHO bureaucrats and other imbeciles) is to say if masks reduce the transmission probability to ¼, one would think it would then drop from, say R0= 5, to R0=1 ¼. Yuuge, but there is better.

For one should count both sides. Under our simplification, with p=1/4 we get R0'= p² R0 . The drop in R becomes 93.75%! You divide R by 16! Even with masks working at 50% we get a 75% drop in R0.

Second error: Missing the Nonlinearity of the Risk of Infection

we are in the convex part of the curve. For example, to use the case above, a reduction of viral load by 75% for a short exposure could reduce the probability of infection by 95% or more!

Third Error: Mistaking Absence of Evidence for Evidence of Absence

“There is no evidence that masks work”, I kept hearing repeated to me by the usual idiots calling themselves “evidence based” scientists. The point is that there is no evidence that locking the door tonight will prevent me from being burglarized. But everything that may block transmission could help.

Unlike school, real life is not about certainties. When in doubt, use what protection you can

Fourth Error: Misunderstanding the Market and PeoplePaternalistic bureaucrats resisted inviting the general public to use masks on grounds that the supply was limited and would be needed by health professionals — hence they lied to us saying “masks are not effective”

Fifth Error: Missing Extremely Strong Statistical Signals

they fear to be presenting “anecdotes”, and fail to grasp the broader notion of statistical signals where you look at the whole story, not the body parts.

evidence compounds.

We have a) the salon story where two infected stylists failed to infect all their 140 clients (making the probability of infection for bilateral mask wearing safely below 1% for a salon-style exposure)

plus b) the rate of infection of countries where masks were mandatory

plus c) tons of papers with more or less flawed methodologies, etc.

Sixth Error: The Non-Aggression Principle

“Libertarians” (in brackets) are resisting mask wearing on grounds that it constrains their freedom. Yet the entire concept of liberty lies in the Non-Aggression Principle, the equivalent of the Silver Rule: do not harm others; they in turn should not harm you.

Even more insulting is the demand by pseudolibertarians that Costco should banned from forcing customers to wear mask — but libertarianism allows you to set the rules on your own property. Costco should be able to force visitors to wear pink shirts and purple glasses if they wished.

Note that by infecting another person you are not infecting just another person. You are infecting many many more and causing systemic risk.

That allows quantum computers to make many calculations in one pass, while digital ones have to perform each calculation separately. By speeding up computation, quantum computers could potentially solve big, complex problems in fields like chemistry and materials science that are out of reach today.

When Google researchers made their supremacy claim in 2019, they said their quantum computer performed a calculation in 3 minutes 20 seconds that would take about 10,000 years on a state-of-the-art conventional supercomputer.

The IBM researchers in the new study performed a different task, one that interests physicists. They used a quantum processor with 127 qubits to simulate the behavior of 127 atom-scale bar magnets — tiny enough to be governed by the spooky rules of quantum mechanics — in a magnetic field. That is a simple system known as the Ising model, which is often used to study magnetism.

This problem is too complex for a precise answer to be calculated even on the largest, fastest supercomputers.

On the quantum computer, the calculation took less than a thousandth of a second to complete. Each quantum calculation was unreliable — fluctuations of quantum noise inevitably intrude and induce errors — but each calculation was quick, so it could be performed repeatedly.

Indeed, for many of the calculations, additional noise was deliberately added, making the answers even more unreliable. But by varying the amount of noise, the researchers could tease out the specific characteristics of the noise and its effects at each step of the calculation.“We can amplify the noise very precisely, and then we can rerun that same circuit,” said Abhinav Kandala, the manager of quantum capabilities and demonstrations at IBM Quantum and an author of the Nature paper. “And once we have results of these different noise levels, we can extrapolate back to what the result would have been in the absence of noise.”In essence, the researchers were able to subtract the effects of noise from the unreliable quantum calculations, a process they call error mitigation.

Altogether, the computer performed the calculation 600,000 times, converging on an answer for the overall magnetization produced by the 127 bar magnets.

Although an Ising model with 127 bar magnets is too big, with far too many possible configurations, to fit in a conventional computer, classical algorithms can produce approximate answers, a technique similar to how compression in JPEG images throws away less crucial data to reduce the size of the file while preserving most of the image’s details

Certain configurations of the Ising model can be solved exactly, and both the classical and quantum algorithms agreed on the simpler examples. For more complex but solvable instances, the quantum and classical algorithms produced different answers, and it was the quantum one that was correct.

Thus, for other cases where the quantum and classical calculations diverged and no exact solutions are known, “there is reason to believe that the quantum result is more accurate,”

Mr. Anand is currently trying to add a version of error mitigation for the classical algorithm, and it is possible that could match or surpass the performance of the quantum calculations.

In the long run, quantum scientists expect that a different approach, error correction, will be able to detect and correct calculation mistakes, and that will open the door for quantum computers to speed ahead for many uses.

Error correction is already used in conventional computers and data transmission to fix garbles. But for quantum computers, error correction is likely years away, requiring better processors able to process many more qubits

“This is one of the simplest natural science problems that exists,” Dr. Gambetta said. “So it’s a good one to start with. But now the question is, how do you generalize it and go to more interesting natural science problems?”

Those might include figuring out the properties of exotic materials, accelerating drug discovery and modeling fusion reactions.

The second step is starting to understand why it is that big data, super computers, and mathematical sophistication haven’t made us better at separating signals (information with true predictive value) from noise (misleading information). 

Silver’s background in sports and poker turns out to be invaluable. Successful analysts in gambling and sports are different from fans and partisans—far more aware that “sure things” are likely to be illusions,

he blends the best of modern statistical analysis with research on cognition biases pioneered by Princeton psychologist and Nobel laureate in economics  Daniel Kahneman and the late Stanford psychologist Amos Tversky. 

One of the biggest problems we have in separating signal from noise is that when we look too hard for certainty that isn’t there, we often end up attracted to noise, either because it is more prominent or because it confirms what we would like to believe.

In discipline after discipline, Silver shows in his book that when you look at even the best single forecast, the average of all independent forecasts is 15 to 20 percent more accurate. 

Silver has taken the next major step: constantly incorporating both state polls and national polls into Bayesian models that also incorporate economic data.

Silver explains why we will be misled if we only consider significance tests—i.e., statements that the margin of error for the results is, for example, plus or minus four points, meaning there is one chance in 20 that the percentages reported are off by more than four. Calculations like these assume the only source of error is sampling error—the irreducible error—while ignoring errors attributable to house effects, like the proportion of cell-phone users, one of the complex set of assumptions every pollster must make about who will actually vote. In other words, such an approach ignores context in order to avoid having to justify and defend judgments. 

You’re in a collective extended “survival vehicle” relationship.

In a kind of no-brainer biochemical “social contract,” bacterial colonies, like human communities, have to handle the “common good” (suppressing cheating, free-riding, the “tragedy of the commons,” etc).

We dominate because we’re the best cooperators (Yuval Harari).

Evolution is itself a free-floating logic pattern (for discovering other, ever more effective logic patterns, and enacting “competence without comprehension").

Evolution’s logic is like geometry’s: in both relevant patterns and results arise from the intrinsic logic of the elements involved. In geometry, it’s lines, planes, etc. In evolution it’s kinetic functions like survival, varying replication, and adaptation.

you know now, if you did not before, that the police departments of your country have been endowed with the authority to destroy your body. It does not matter if the destruction is the result of an unfortunate overreaction. It does not matter if it originates in a misunderstanding. It does not matter if the destruction springs from a foolish policy

But a society that protects some people through a safety net of schools, government-backed home loans, and ancestral wealth but can only protect you with the club of criminal justice has either failed at enforcing its good intentions or has succeeded at something much darker.

It is hard to face this. But all our phrasing—race relations, racial chasm, racial justice, racial profiling, white privilege, even white supremacy—serves to obscure that racism is a visceral experience, that it dislodges brains, blocks airways, rips muscle, extracts organs, cracks bones, breaks teeth

ou must never look away from this. You must always remember that the sociology, the history, the economics, the graphs, the charts, the regressions all land, with great violence, upon the body.

And should one live in such a body? What should be our aim beyond meager survival of constant, generational, ongoing battery and assault? I have asked this question all my life.

The question is unanswerable, which is not to say futile. The greatest reward of this constant interrogation, of confrontation with the brutality of my country, is that it has freed me from ghosts and myths.

I was afraid long before you, and in this I was unoriginal. When I was your age the only people I knew were black, and all of them were powerfully, adamantly, dangerously afraid. It was always right in front of me. The fear was there in the extravagant boys of my West Baltimore neighborhood

The fear lived on in their practiced bop, their slouching denim, their big T- shirts, the calculated angle of their baseball caps, a catalog of behaviors and garments enlisted to inspire the belief that these boys were in firm possession of everything they desired.

To be black in the Baltimore of my youth was to be naked before the elements of the world, before all the guns, fists, knives, crack, rape, and disease. The law did not protect us. And now, in your time, the law has become an excuse for stopping and frisking you, which is to say, for furthering the assault on your body

I remember being amazed that death could so easily rise up from the nothing of a boyish afternoon, billow up like fog. I knew that West Baltimore, where I lived; that the north side of Philadelphia, where my cousins lived; that the South Side of Chicago, where friends of my father lived, comprised a world apart. Somewhere out there beyond the firmament, past the asteroid belt, there were other worlds where children did not regularly fear for their bodies

here will surely always be people with straight hair and blue eyes, as there have been for all history. But some of these straight-haired people with blue eyes have been “black,” and this points to the great difference between their world and ours. We did not choose our fences. They were imposed on us by Virginia planters obsessed with enslaving as many Americans as possible. Now I saw that we had made something down here, in slavery, in Jim Crow, in ghettoes. At The Mecca I saw how we had taken their one-drop rule and flipped it. They made us into a race. We made ourselves into a people.

I came to understand that my country was a galaxy, and this galaxy stretched from the pandemonium of West Baltimore to the happy hunting grounds of Mr. Belvedere. I obsessed over the distance between that other sector of space and my own. I knew that my portion of the American galaxy, where bodies were enslaved by a tenacious gravity, was black and that the other, liberated portion was not. I knew that some inscrutable energy preserved the breach. I felt, but did not yet understand, the relation between that other world and me. And I felt in this a cosmic injustice, a profound cruelty, which infused an abiding, irrepressible desire to unshackle my body and achieve the velocity of escape.

Before I could escape, I had to survive, and this could only mean a clash with the streets, by which I mean not just physical blocks, nor simply the people packed into them, but the array of lethal puzzles and strange perils which seem to rise up from the asphalt itself. The streets transform every ordinary day into a series of trick questions, and every incorrect answer risks a beat-down, a shooting, or a pregnancy. No one survives unscathed

When I was your age, fully one-third of my brain was concerned with who I was walking to school with, our precise number, the manner of our walk, the number of times I smiled, who or what I smiled at, who offered a pound and who did not—all of which is to say that I practiced the culture of the streets, a culture concerned chiefly with securing the body.

Why were only our heroes nonviolent? Back then all I could do was measure these freedom-lovers by what I knew. Which is to say, I measured them against children pulling out in the 7-Eleven parking lot, against parents wielding extension cords, and the threatening intonations of armed black gangs saying, “Yeah, nigger, what’s up now?” I judged them against the country I knew, which had acquired the land through murder and tamed it under slavery, against the country whose armies fanned out across the world to extend their dominion. The world, the real one, was civilization secured and ruled by savage means. How could the schools valorize men and women whose values society actively scorned? How could they send us out into the streets of Baltimore, knowing all that they were, and then speak of nonviolence?

the beauty of the black body was never celebrated in movies, in television, or in the textbooks I’d seen as a child. Everyone of any import, from Jesus to George Washington, was white. This was why your grandparents banned Tarzan and the Lone Ranger and toys with white faces from the house. They were rebelling against the history books that spoke of black people only as sentimental “firsts”—first black four-star general, first black congressman, first black mayor—always presented in the bemused manner of a category of Trivial Pursuit.

erious history was the West, and the West was white. This was all distilled for me in a quote I once read, from the novelist Saul Bellow. I can’t remember where I read it, or when—only that I was already at Howard. “Who is the Tolstoy of the Zulus?,” Bellow quipped

this view of things was connected to the fear that passed through the generations, to the sense of dispossession. We were black, beyond the visible spectrum, beyond civilization. Our history was inferior because we were inferior, which is to say our bodies were inferior. And our inferior bodies could not possibly be accorded the same respect as those that built the West. Would it not be better, then, if our bodies were civilized, improved, and put to some legitimate Christian use?

now I looked back on my need for a trophy case, on the desire to live by the standards of Saul Bellow, and I felt that this need was not an escape but fear again—fear that “they,” the alleged authors and heirs of the universe, were right. And this fear ran so deep that we accepted their standards of civilization and humanity.

“Tolstoy is the Tolstoy of the Zulus,” wrote Wiley. “Unless you find a profit in fencing off universal properties of mankind into exclusive tribal ownership.” And there it was. I had accepted Bellow’s premise. In fact, Bellow was no closer to Tolstoy than I was to Nzinga. And if I were closer it would be because I chose to be, not because of destiny written in DNA. My great error was not that I had accepted someone else’s dream but that I had accepted the fact of dreams, the need for escape, and the invention of racecraft.

still and all I knew that we were something, that we were a tribe—on one hand, invented, and on the other, no less real. The reality was out there on the Yard, on the first warm day of spring when it seemed that every sector, borough, affiliation, county, and corner of the broad diaspora had sent a delegate to the great world party

I could see now that that world was more than a photonegative of that of the people who believe they are white. “White America” is a syndicate arrayed to protect its exclusive power to dominate and control our bodies. Sometimes this power is direct (lynching), and sometimes it is insidious (redlining). But however it appears, the power of domination and exclusion is central to the belief in being white, and without it, “white people” would cease to exist for want of reasons

There is nothing uniquely evil in these destroyers or even in this moment. The destroyers are merely men enforcing the whims of our country, correctly interpreting its heritage and legacy. This legacy aspires to the shackling of black bodies

Think of all the embraces, all the private jokes, customs, greetings, names, dreams, all the shared knowledge and capacity of a black family injected into that vessel of flesh and bone. And think of how that vessel was taken, shattered on the concrete, and all its holy contents, all that had gone into each of them, was sent flowing back to the earth. It is terrible to truly see our particular beauty, Samori, because then you see the scope of the loss. But you must push even further. You must see that this loss is mandated by the history of your country, by the Dream of living white.

I don’t know if you remember how the film we saw at the Petersburg Battlefield ended as though the fall of the Confederacy were the onset of a tragedy, not jubilee. I doubt you remember the man on our tour dressed in the gray wool of the Confederacy, or how every visitor seemed most interested in flanking maneuvers, hardtack, smoothbore rifles, grapeshot, and ironclads, but virtually no one was interested in what all of this engineering, invention, and design had been marshaled to achieve. You were only 10 years old. But even then I knew that I must trouble you, and this meant taking you into rooms where people would insult your intelligence, where thieves would try to enlist you in your own robbery and disguise their burning and looting as Christian charity. But robbery is what this is, what it always was.

American reunion was built on a comfortable narrative that made enslavement into benevolence, white knights of body snatchers, and the mass slaughter of the war into a kind of sport in which one could conclude that both sides conducted their affairs with courage, honor, and élan. This lie of the Civil War is the lie of innocence, is the Dream.

I, like every kid I knew, loved The Dukes of Hazzard. But I would have done well to think more about why two outlaws, driving a car named the General Lee, must necessarily be portrayed as “just some good ole boys, never meanin’ no harm”—a mantra for the Dreamers if there ever was one. But what one “means” is neither important nor relevant. It is not necessary that you believe that the officer who choked Eric Garner set out that day to destroy a body. All you need to understand is that the officer carries with him the power of the American state and the weight of an American legacy, and they necessitate that of the bodies destroyed every year, some wild and disproportionate number of them will be black.

Here is what I would like for you to know: In America, it is traditional to destroy the black body—it is heritage. Enslavement was not merely the antiseptic borrowing of labor—it is not so easy to get a human being to commit their body against its own elemental interest. And so enslavement must be casual wrath and random manglings, the gashing of heads and brains blown out over the river as the body seeks to escape. It must be rape so regular as to be industrial. There is no uplifting way to say this.

It had to be blood. It had to be the thrashing of kitchen hands for the crime of churning butter at a leisurely clip. It had to be some woman “chear’d ... with thirty lashes a Saturday last and as many more a Tuesday again.” It could only be the employment of carriage whips, tongs, iron pokers, handsaws, stones, paperweights, or whatever might be handy to break the black body, the black family, the black community, the black nation. The bodies were pulverized into stock and marked with insurance. And the bodies were an aspiration, lucrative as Indian land, a veranda, a beautiful wife, or a summer home in the mountains. For the men who needed to believe themselves white, the bodies were the key to a social club, and the right to break the bodies was the mark of civilization.

“The two great divisions of society are not the rich and poor, but white and black,” said the great South Carolina senator John C. Calhoun. “And all the former, the poor as well as the rich, belong to the upper class, and are respected and treated as equals.” And there it is—the right to break the black body as the meaning of their sacred equality. And that right has always given them meaning, has always meant that there was someone down in the valley because a mountain is not a mountain if there is nothing below.

There is no them without you, and without the right to break you they must necessarily fall from the mountain, lose their divinity, and tumble out of the Dream. And then they would have to determine how to build their suburbs on something other than human bones, how to angle their jails toward something other than a human stockyard, how to erect a democracy independent of cannibalism. I would like to tell you that such a day approaches when the people who believe themselves to be white renounce this demon religion and begin to think of themselves as human. But I can see no real promise of such a day. We are captured, brother, surrounded by the majoritarian bandits of America. And this has happened here, in our only home, and the terrible truth is that we cannot will ourselves to an escape on our own.

I think now of the old rule that held that should a boy be set upon in someone else’s chancy hood, his friends must stand with him, and they must all take their beating together. I now know that within this edict lay the key to all living. None of us were promised to end the fight on our feet, fists raised to the sky. We could not control our enemies’ number, strength, or weaponry. Sometimes you just caught a bad one. But whether you fought or ran, you did it together, because that is the part that was in our control. What we must never do is willingly hand over our own bodies or the bodies of our friends. That was the wisdom: We knew we did not lay down the direction of the street, but despite that, we could—and must—fashion the way of our walk. And that is the deeper meaning of your name—that the struggle, in and of itself, has meaning.

I have raised you to respect every human being as singular, and you must extend that same respect into the past. Slavery is not an indefinable mass of flesh. It is a particular, specific enslaved woman, whose mind is as active as your own, whose range of feeling is as vast as your own; who prefers the way the light falls in one particular spot in the woods, who enjoys fishing where the water eddies in a nearby stream, who loves her mother in her own complicated way, thinks her sister talks too loud, has a favorite cousin, a favorite season, who excels at dressmaking and knows, inside herself, that she is as intelligent and capable as anyone. “Slavery” is this same woman born in a world that loudly proclaims its love of freedom and inscribes this love in its essential texts, a world in which these same professors hold this woman a slave, hold her mother a slave, her father a slave, her daughter a slave, and when this woman peers back into the generations all she sees is the enslaved. She can hope for more. She can imagine some future for her grandchildren. But when she dies, the world—which is really the only world she can ever know—ends. For this woman, enslavement is not a parable. It is damnation. It is the never-ending night. And the length of that night is most of our history. Never forget that we were enslaved in this country longer than we have been free. Never forget that for 250 years black people were born into chains—whole generations followed by more generations who knew nothing but chains.

You must resist the common urge toward the comforting narrative of divine law, toward fairy tales that imply some irrepressible justice. The enslaved were not bricks in your road, and their lives were not chapters in your redemptive history. They were people turned to fuel for the American machine. Enslavement was not destined to end, and it is wrong to claim our present circumstance—no matter how improved—as the redemption for the lives of people who never asked for the posthumous, untouchable glory of dying for their children. Our triumphs can never redeem this. Perhaps our triumphs are not even the point. Perhaps struggle is all we have

I am not a cynic. I love you, and I love the world, and I love it more with every new inch I discover. But you are a black boy, and you must be responsible for your body in a way that other boys cannot know. Indeed, you must be responsible for the worst actions of other black bodies, which, somehow, will always be assigned to you. And you must be responsible for the bodies of the powerful—the policeman who cracks you with a nightstick will quickly find his excuse in your furtive movements. You have to make your peace with the chaos, but you cannot lie.

“I could have you arrested,” he said. Which is to say: “One of your son’s earliest memories will be watching the men who sodomized Abner Louima and choked Anthony Baez cuff, club, tase, and break you.” I had forgotten the rules, an error as dangerous on the Upper West Side of Manhattan as on the West Side of Baltimore. One must be without error out here. Walk in single file. Work quietly. Pack an extra No. 2 pencil. Make no mistakes.

the price of error is higher for you than it is for your countrymen, and so that America might justify itself, the story of a black body’s destruction must always begin with his or her error, real or imagined—with Eric Garner’s anger, with Trayvon Martin’s mythical words (“You are gonna die tonight”), with Sean Bell’s mistake of running with the wrong crowd, with me standing too close to the small-eyed boy pulling out.

You are called to struggle, not because it assures you victory but because it assures you an honorable and sane life

I am sorry that I cannot save you—but not that sorry. Part of me thinks that your very vulnerability brings you closer to the meaning of life, just as for others, the quest to believe oneself white divides them from it. The fact is that despite their dreams, their lives are also not inviolable. When their own vulnerability becomes real—when the police decide that tactics intended for the ghetto should enjoy wider usage, when their armed society shoots down their children, when nature sends hurricanes against their cities—they are shocked by the rages of logic and the natural world in a way that those of us who were born and bred to understand cause and effect can never be.

I would not have you live like them. You have been cast into a race in which the wind is always at your face and the hounds are always at your heels. And to varying degrees this is true of all life. The difference is that you do not have the privilege of living in ignorance of this essential fact.

I never wanted you to be twice as good as them, so much as I have always wanted you to attack every day of your brief bright life determined to struggle. The people who must believe they are white can never be your measuring stick. I would not have you descend into your own dream. I would have you be a conscious citizen of this terrible and beautiful world.

This is the big problem in science that no one is talking about: even an honest person is a master of self-deception. Our brains evolved long ago on the African savannah, where jumping to plausible conclusions about the location of ripe fruit or the presence of a predator was a matter of survival. But a smart strategy for evading lions does not necessarily translate well to a modern laboratory, where tenure may be riding on the analysis of terabytes of multidimensional data. In today's environment, our talent for jumping to conclusions makes it all too easy to find false patterns in randomness, to ignore alternative explanations for a result or to accept 'reasonable' outcomes without question — that is, to ceaselessly lead ourselves astray without realizing it.

Failure to understand our own biases has helped to create a crisis of confidence about the reproducibility of published results

Although it is impossible to document how often researchers fool themselves in data analysis, says Ioannidis, findings of irreproducibility beg for an explanation. The study of 100 psychology papers is a case in point: if one assumes that the vast majority of the original researchers were honest and diligent, then a large proportion of the problems can be explained only by unconscious biases. “This is a great time for research on research,” he says. “The massive growth of science allows for a massive number of results, and a massive number of errors and biases to study. So there's good reason to hope we can find better ways to deal with these problems.”

Although the human brain and its cognitive biases have been the same for as long as we have been doing science, some important things have changed, says psychologist Brian Nosek, executive director of the non-profit Center for Open Science in Charlottesville, Virginia, which works to increase the transparency and reproducibility of scientific research. Today's academic environment is more competitive than ever. There is an emphasis on piling up publications with statistically significant results — that is, with data relationships in which a commonly used measure of statistical certainty, the p-value, is 0.05 or less. “As a researcher, I'm not trying to produce misleading results,” says Nosek. “But I do have a stake in the outcome.” And that gives the mind excellent motivation to find what it is primed to find.

Another reason for concern about cognitive bias is the advent of staggeringly large multivariate data sets, often harbouring only a faint signal in a sea of random noise. Statistical methods have barely caught up with such data, and our brain's methods are even worse, says Keith Baggerly, a statistician at the University of Texas MD Anderson Cancer Center in Houston. As he told a conference on challenges in bioinformatics last September in Research Triangle Park, North Carolina, “Our intuition when we start looking at 50, or hundreds of, variables sucks.”

One trap that awaits during the early stages of research is what might be called hypothesis myopia: investigators fixate on collecting evidence to support just one hypothesis; neglect to look for evidence against it; and fail to consider other explanations.

when it comes to mistaken judgments and unfortunate decisions, there is another type of error that attracts far less attention: noise.

To see the difference between bias and noise, consider your bathroom scale. If on average the readings it gives are too high (or too low), the scale is biased

It is hard to escape the conclusion that sentencing is in part a lottery, because the punishment can vary by many years depending on which judge is assigned to the case and on the judge’s state of mind on that day. The judicial system is unacceptably noisy.

While bias is the average of errors, noise is their variability.

Although it is often ignored, noise is a large source of malfunction in society.

The average difference between the sentences that two randomly chosen judges gave for the same crime was more than 3.5 years. Considering that the mean sentence was seven years, that was a disconcerting amount of noise.

If it shows different readings when you step on it several times in quick succession, the scale is noisy.

How much of a difference would you expect to find between the premium values that two competent underwriters assigned to the same risk?

Executives in the insurance company said they expected about a 10 percent difference.

But the typical difference we found between two underwriters was an astonishing 55 percent of their average premium — more than five times as large as the executives had expected.

Many other studies demonstrate noise in professional judgments. Radiologists disagree on their readings of images and cardiologists on their surgery decisions

Wherever there is judgment, there is noise — and more of it than you think.

Noise causes error, as does bias, but the two kinds of error are separate and independent.

A company’s hiring decisions could be unbiased overall if some of its recruiters favor men and others favor women. However, its hiring decisions would be noisy, and the company would make many bad choices

Where does noise come from?

There is much evidence that irrelevant circumstances can affect judgments.

for instance, a judge’s mood, fatigue and even the weather can all have modest but detectable effects on judicial decisions.

people can have different general tendencies. Judges often vary in the severity of the sentences they mete out: There are “hanging” judges and lenient ones.

People can have not only different general tendencies (say, whether they are harsh or lenient) but also different patterns of assessment (say, which types of cases they believe merit being harsh or lenient about).

Underwriters differ in their views of what is risky, and doctors in their views of which ailments require treatment.

Once you become aware of noise, you can look for ways to reduce it.

independent judgments from a number of people can be averaged (a frequent practice in forecasting)

Guidelines, such as those often used in medicine, can help professionals reach better and more uniform decisions

imposing structure and discipline in interviews and other forms of assessment tends to improve judgments of job candidates.

No noise-reduction techniques will be deployed, however, if we do not first recognize the existence of noise.

Organizations and institutions, public and private, will make better decisions if they take noise seriously.

Confirmation bias shows up most blatantly in our current political divide, where each side seems unable to allow that the other side is right about anything.

The whole idea of cognitive biases and faulty heuristics—the shortcuts and rules of thumb by which we make judgments and predictions—was more or less invented in the 1970s by Amos Tversky and Daniel Kahneman

versky died in 1996. Kahneman won the 2002 Nobel Prize in Economics for the work the two men did together, which he summarized in his 2011 best seller, Thinking, Fast and Slow. Another best seller, last year’s The Undoing Project, by Michael Lewis, tells the story of the sometimes contentious collaboration between Tversky and Kahneman

Another key figure in the field is the University of Chicago economist Richard Thaler. One of the biases he’s most linked with is the endowment effect, which leads us to place an irrationally high value on our possessions.

In an experiment conducted by Thaler, Kahneman, and Jack L. Knetsch, half the participants were given a mug and then asked how much they would sell it for. The average answer was $5.78. The rest of the group said they would spend, on average, $2.21 for the same mug. This flew in the face of classic economic theory, which says that at a given time and among a certain population, an item has a market value that does not depend on whether one owns it or not. Thaler won the 2017 Nobel Prize in Economics.

“The question that is most often asked about cognitive illusions is whether they can be overcome. The message … is not encouraging.”

that’s not so easy in the real world, when we’re dealing with people and situations rather than lines. “Unfortunately, this sensible procedure is least likely to be applied when it is needed most,” Kahneman writes. “We would all like to have a warning bell that rings loudly whenever we are about to make a serious error, but no such bell is available.”

At least with the optical illusion, our slow-thinking, analytic mind—what Kahneman calls System 2—will recognize a Müller-Lyer situation and convince itself not to trust the fast-twitch System 1’s perception

Kahneman and others draw an analogy based on an understanding of the Müller-Lyer illusion, two parallel lines with arrows at each end. One line’s arrows point in; the other line’s arrows point out. Because of the direction of the arrows, the latter line appears shorter than the former, but in fact the two lines are the same length.

Because biases appear to be so hardwired and inalterable, most of the attention paid to countering them hasn’t dealt with the problematic thoughts, judgments, or predictions themselves

Is it really impossible, however, to shed or significantly mitigate one’s biases? Some studies have tentatively answered that question in the affirmative.

what if the person undergoing the de-biasing strategies was highly motivated and self-selected? In other words, what if it was me?

Over an apple pastry and tea with milk, he told me, “Temperament has a lot to do with my position. You won’t find anyone more pessimistic than I am.”

I met with Kahneman

“I see the picture as unequal lines,” he said. “The goal is not to trust what I think I see. To understand that I shouldn’t believe my lying eyes.” That’s doable with the optical illusion, he said, but extremely difficult with real-world cognitive biases.

In this context, his pessimism relates, first, to the impossibility of effecting any changes to System 1—the quick-thinking part of our brain and the one that makes mistaken judgments tantamount to the Müller-Lyer line illusion

he most effective check against them, as Kahneman says, is from the outside: Others can perceive our errors more readily than we can.

“slow-thinking organizations,” as he puts it, can institute policies that include the monitoring of individual decisions and predictions. They can also require procedures such as checklists and “premortems,”

A premortem attempts to counter optimism bias by requiring team members to imagine that a project has gone very, very badly and write a sentence or two describing how that happened. Conducting this exercise, it turns out, helps people think ahead.

“My position is that none of these things have any effect on System 1,” Kahneman said. “You can’t improve intuition.

Perhaps, with very long-term training, lots of talk, and exposure to behavioral economics, what you can do is cue reasoning, so you can engage System 2 to follow rules. Unfortunately, the world doesn’t provide cues. And for most people, in the heat of argument the rules go out the window.

Kahneman describes an even earlier Nisbett article that showed subjects’ disinclination to believe statistical and other general evidence, basing their judgments instead on individual examples and vivid anecdotes. (This bias is known as base-rate neglect.)

over the years, Nisbett had come to emphasize in his research and thinking the possibility of training people to overcome or avoid a number of pitfalls, including base-rate neglect, fundamental attribution error, and the sunk-cost fallacy.

Nisbett’s second-favorite example is that economists, who have absorbed the lessons of the sunk-cost fallacy, routinely walk out of bad movies and leave bad restaurant meals uneaten.

When Nisbett asks the same question of students who have completed the statistics course, about 70 percent give the right answer. He believes this result shows, pace Kahneman, that the law of large numbers can be absorbed into System 2—and maybe into System 1 as well, even when there are minimal cues.

about half give the right answer: the law of large numbers, which holds that outlier results are much more frequent when the sample size (at bats, in this case) is small. Over the course of the season, as the number of at bats increases, regression to the mean is inevitabl

When Nisbett has to give an example of his approach, he usually brings up the baseball-phenom survey. This involved telephoning University of Michigan students on the pretense of conducting a poll about sports, and asking them why there are always several Major League batters with .450 batting averages early in a season, yet no player has ever finished a season with an average that high.

we’ve tested Michigan students over four years, and they show a huge increase in ability to solve problems. Graduate students in psychology also show a huge gain.”

, “I know from my own research on teaching people how to reason statistically that just a few examples in two or three domains are sufficient to improve people’s reasoning for an indefinitely large number of events.”

isbett suggested another factor: “You and Amos specialized in hard problems for which you were drawn to the wrong answer. I began to study easy problems, which you guys would never get wrong but untutored people routinely do … Then you can look at the effects of instruction on such easy problems, which turn out to be huge.”

Nisbett suggested that I take “Mindware: Critical Thinking for the Information Age,” an online Coursera course in which he goes over what he considers the most effective de-biasing skills and concepts. Then, to see how much I had learned, I would take a survey he gives to Michigan undergraduates. So I did.

he course consists of eight lessons by Nisbett—who comes across on-screen as the authoritative but approachable psych professor we all would like to have had—interspersed with some graphics and quizzes. I recommend it. He explains the availability heuristic this way: “People are surprised that suicides outnumber homicides, and drownings outnumber deaths by fire. People always think crime is increasing” even if it’s not.

When I finished the course, Nisbett sent me the survey he and colleagues administer to Michigan undergrads

It contains a few dozen problems meant to measure the subjects’ resistance to cognitive biases

I got it right. Indeed, when I emailed my completed test, Nisbett replied, “My guess is that very few if any UM seniors did as well as you. I’m sure at least some psych students, at least after 2 years in school, did as well. But note that you came fairly close to a perfect score.”

Nevertheless, I did not feel that reading Mindware and taking the Coursera course had necessarily rid me of my biases

For his part, Nisbett insisted that the results were meaningful. “If you’re doing better in a testing context,” he told me, “you’ll jolly well be doing better in the real world.”

The New York–based NeuroLeadership Institute offers organizations and individuals a variety of training sessions, webinars, and conferences that promise, among other things, to use brain science to teach participants to counter bias. This year’s two-day summit will be held in New York next month; for $2,845, you could learn, for example, “why are our brains so bad at thinking about the future, and how do we do it better?”

Philip E. Tetlock, a professor at the University of Pennsylvania’s Wharton School, and his wife and research partner, Barbara Mellers, have for years been studying what they call “superforecasters”: people who manage to sidestep cognitive biases and predict future events with far more accuracy than the pundits

One of the most important ingredients is what Tetlock calls “the outside view.” The inside view is a product of fundamental attribution error, base-rate neglect, and other biases that are constantly cajoling us into resting our judgments and predictions on good or vivid stories instead of on data and statistics

In 2006, seeking to prevent another mistake of that magnitude, the U.S. government created the Intelligence Advanced Research Projects Activity (iarpa), an agency designed to use cutting-edge research and technology to improve intelligence-gathering and analysis. In 2011, iarpa initiated a program, Sirius, to fund the development of “serious” video games that could combat or mitigate what were deemed to be the six most damaging biases: confirmation bias, fundamental attribution error, the bias blind spot (the feeling that one is less biased than the average person), the anchoring effect, the representativeness heuristic, and projection bias (the assumption that everybody else’s thinking is the same as one’s own).

most promising are a handful of video games. Their genesis was in the Iraq War

Together with collaborators who included staff from Creative Technologies, a company specializing in games and other simulations, and Leidos, a defense, intelligence, and health research company that does a lot of government work, Morewedge devised Missing. Some subjects played the game, which takes about three hours to complete, while others watched a video about cognitive bias. All were tested on bias-mitigation skills before the training, immediately afterward, and then finally after eight to 12 weeks had passed.

“The literature on training suggests books and classes are fine entertainment but largely ineffectual. But the game has very large effects. It surprised everyone.”

he said he saw the results as supporting the research and insights of Richard Nisbett. “Nisbett’s work was largely written off by the field, the assumption being that training can’t reduce bias,

even the positive results reminded me of something Daniel Kahneman had told me. “Pencil-and-paper doesn’t convince me,” he said. “A test can be given even a couple of years later. But the test cues the test-taker. It reminds him what it’s all about.”

Morewedge told me that some tentative real-world scenarios along the lines of Missing have shown “promising results,” but that it’s too soon to talk about them.

In the future, I will monitor my thoughts and reactions as best I can

Beyond the grammars of geometry and algebra lies a domain of not math-like but text-like compositions and meanings (of semantics beyond mathematics).

17. Word and world both have grammars that don’t fit our available mathematical rules.

18. Reality is relational, and not entirely objective. Subject and object aren’t separable, they’re entangled, inescapably. “Objective” is always relative to some other system/observer. 

The new process may also help in other procedures where doctors need to analyze tissue while they are still operating, such as head and neck, breast, skin and gynecologic surgery, the report said. It also noted that there is a shortage of neuropathologists, and suggested that the new technology might help fill the gap in medical centers that lack the specialty. Video Advertisement LIVE 00:00 1:05

Algorithms are also being developed to help detect lung cancers on CT scans, diagnose eye disease in people with diabetes and find cancer on microscope slides.

The diagnoses were later judged right or wrong based on whether they agreed with the findings of lengthier and more extensive tests performed after the surgery.The result was a draw: humans, 93.9 percent correct; A.I., 94.6 percent.

At some centers, he said, brain surgeons do not even order frozen sections because they do not trust them and prefer to wait for tissue processing after the surgery, which may take weeks to complete.

Some types of brain tumor are so rare that there is not enough data on them to train an A.I. system, so the system in the study was designed to essentially toss out samples it could not identify.

“It won’t change brain surgery,” he said, “but it’s going to add a significant new tool, more significant than they’ve stated.”

a new book, The Experience Machine: How Our Minds Predict and Shape Reality, which is remarkable for how it connects the high-level concepts to everyday examples of how our brains make predictions, how that process can lead us astray, and what we can do about it.

being driven to stay within your own viability envelope is crucial to the kind of intelligence that we know about—the kind of intelligence that we are

If you ask what is a predictive brain for, the answer has to be: staying alive. Predictive brains are a way of staying within your viability envelope as an embodied biological organism: getting food when you need it, getting water when you need it.

in predictive processing, perception is structured around prediction. Perception is about the brain having a guess at what’s most likely to be out there and then using sensory information to refine the guess.

artificial curiosity. Predictive-processing systems automatically have that. They’re set up so that they predict the conditions of their own survival, and they’re always trying to get rid of prediction errors. But if they’ve solved all their practical problems and they’ve got nothing else to do, then they’ll just explore. Getting rid of any error is going to be a good thing for them. If you’re a creature like that, you’re going to be a really good learning system. You’re going to love to inhabit the environments that you can learn most from, where the problems are not too simple, not too hard, but just right.

It’s an effect that you also see in Marieke Jepma et al.’s work on pain. They showed that if you predict intense pain, the signal that you get will be interpreted as more painful than it would otherwise be, and vice versa. Then they asked why you don’t correct your misimpression. If it’s my expectation that is making it feel more painful, why don’t I get prediction errors that correct it?

The reason is that there are no errors. You’re expecting a certain level of pain, and your prediction helps bring that level about; there is nothing for you to correct. In fact, you’ve got confirmation of your own prediction. So it can be a vicious circle

Do you think this self-fulfilling loop in psychosis and pain perception helps to account for misinformation in our society’s and people’s susceptibility to certain narratives?Absolutely. We all have these vulnerabilities and self-fulfilling cycles. We look at the places that tend to support the models that we already have, because that’s often how we judge whether the information is good or not

Given that we know we’re vulnerable to self-fulfilling information loops, how can we make sure we don’t get locked into a belief?Unfortunately, it’s really difficult. The most potent intervention is to remind ourselves that we sample the world in ways that are guided by the models that we’ve currently got. The structures of science are there to push back against our natural tendency to cherry-pick.

common response to this situation is to argue that, even if individual scientists might fool themselves, others have no hesitation in critiquing their ideas or their results, and so it all comes out in the wash: Science as a communal activity is self-correcting. Sometimes this is true—but it doesn’t necessarily happen as quickly or smoothly as we might like to believe.

The idea, says Nosek, is that researchers “write down in advance what their study is for and what they think will happen.” Then when they do their experiments, they agree to be bound to analyzing the results strictly within the confines of that original plan

He is convinced that the process and progress of science would be smoothed by bringing these biases to light—which means making research more transparent in its methods, assumptions, and interpretations

Surprisingly, Nosek thinks that one of the most effective solutions to cognitive bias in science could come from the discipline that has weathered some of the heaviest criticism recently for its error-prone and self-deluding ways: pharmacology.

Psychologist Brian Nosek of the University of Virginia says that the most common and problematic bias in science is “motivated reasoning”: We interpret observations to fit a particular idea.

Sometimes it seems surprising that science functions at all.

Whereas the falsification model of the scientific method championed by philosopher Karl Popper posits that the scientist looks for ways to test and falsify her theories—to ask “How am I wrong?”—Nosek says that scientists usually ask instead “How am I right?” (or equally, to ask “How are you wrong?”).

Statistics may seem to offer respite from bias through strength in numbers, but they are just as fraught.

Given that science has uncovered a dizzying variety of cognitive biases, the relative neglect of their consequences within science itself is peculiar. “I was aware of biases in humans at large,” says Hartgerink, “but when I first ‘learned’ that they also apply to scientists, I was somewhat amazed, even though it is so obvious.”

Nosek thinks that peer review might sometimes actively hinder clear and swift testing of scientific claims.

they wanted to understand how these biases correlated with human intelligence.

self-awareness was not particularly useful: as the scientists note, “people who were aware of their own biases were not better able to overcome them.”

intelligence seems to make things worse.

This “meta-bias” is rooted in our ability to spot systematic mistakes in the decisions of others—we excel at noticing the flaws of friends—and inability to spot those same mistakes in ourselves.

it applies to every single bias under consideration, from anchoring to so-called “framing effects.” In each instance, we readily forgive our own minds but look harshly upon the minds of other people.

Perhaps our most dangerous bias is that we naturally assume that everyone else is more susceptible to thinking errors, a tendency known as the “bias blind spot.”

the driving forces behind biases—the root causes of our irrationality—are largely unconscious, which means they remain invisible to self-analysis and impermeable to intelligence. In fact, introspection can actually compound the error, blinding us to those primal processes responsible for many of our everyday failings. We spin eloquent stories, but these stories miss the point. The more we attempt to know ourselves, the less we actually understand.

Her core discovery, made with a co-author, Erik M. Conway, was twofold. They reported that dubious tactics had been used over decades to cast doubt on scientific findings relating to subjects like acid rain, the ozone shield, tobacco smoke and climate change. And most surprisingly, in each case, the tactics were employed by the same group of people.

The central players were serious scientists who had major career triumphs during the Cold War, but in subsequent years apparently came to equate environmentalism with socialism, and government regulation with tyranny.

In a 2010 book, Dr. Oreskes and Dr. Conway called these men “Merchants of Doubt,” and this spring the book became a documentary film, by Robert Kenner. At the heart of both works is a description of methods that were honed by the tobacco industry in the 1960s and have since been employed to cast doubt on just about any science being cited to support new government regulations.

Dr. Oreskes, the more visible and vocal of the “Merchants” authors, has been threatened with lawsuits and vilified on conservative websites, and routinely gets hate mail calling her a communist or worse.

She established her career as a historian with a book-length study examining the role of dissent in the scientific method. As she put it a few months ago to an audience at Indiana University, she wanted to wrestle with this question: “How do you distinguish a maverick from a crank?”

Dr. Oreskes found that Wegener had been treated badly, particularly by American geologists. But he did not abandon his faith in the scientific method. He kept publishing until his death in 1930, trying to convince fellow scientists of his position, and was finally vindicated three decades later by oceanographic research conducted during the Cold War.

As she completed that study, Dr. Oreskes sought to understand how science was affected not only by the Cold War but by its end. In particular, she started wondering about climate science. Global warming had seemed to rise as an important issue around the time the Iron Curtain came down. Was this just a way for scientists to scare up research money that would no longer be coming their way through military channels?

the widespread public impression was that scientists were still divided over whether humans were primarily responsible for the warming of the planet. But how sharp was the split, she wondered?

She decided to do something no climate scientist had thought to do: count the published scientific papers. Pulling 928 of them, she was startled to find that not one dissented from the basic findings that warming was underway and human activity was the main reason.

She published that finding in a short paper in the journal Science in 2004, and the reaction was electric. Advocates of climate action seized on it as proof of a level of scientific consensus that most of them had not fully perceived. Just as suddenly, Dr. Oreskes found herself under political attack.

Some of the voices criticizing her — scientists like Dr. Singer and groups like the George C. Marshall Institute in Washington — were barely known to her at the time, Dr. Oreskes said in an interview. Just who were they?

It did not take them long to document that this group, which included prominent Cold War scientists, had been attacking environmental research for decades, challenging the science of the ozone layer and acid rain, even the finding that breathing secondhand tobacco smoke was harmful. Trying to undermine climate science was simply the latest project.

Dr. Oreskes and Dr. Conway came to believe that the attacks were patterned on the strategy employed by the tobacco industry when evidence of health risks first emerged. Documents pried loose by lawyers showed that the industry had paid certain scientists to contrive dubious research, had intimidated reputable scientists, and had cherry-picked evidence to present a misleading pictur

The tobacco industry had used these tactics in defense of profits. But Dr. Oreskes and Dr. Conway wrote that the so-called merchants of doubt had adopted them for a deep ideological reason: contempt for government regulation. The insight gave climate scientists a new way of understanding the politics that had engulfed their field.

Following Dr. Oreskes’s cue, researchers have in recent years developed a cottage industry of counting scientific papers and polling scientists. The results typically show that about 97 percent of working climate scientists accept that global warming is happening, that humans are largely responsible, and that the situation poses long-term risks, though the severity of those risks is not entirely clear. That wave of evidence has prompted many national news organizations to stop portraying the field as split evenly between scientists who are convinced and unconvinced.

Dr. Oreskes’s critics have taken delight in searching out errors in her books and other writings, prompting her to post several corrections. They have generally been minor, though, like describing a pH of six as neutral, when the correct number is seven. Dr. Oreskes described that as a typographical error.

In the leaked emails, Dr. Singer told a group of his fellow climate change denialists that he felt that Dr. Oreskes and Dr. Conway had libeled him. But in an interview, when pressed for specific errors in the book that might constitute libel, he listed none. Nor did he provide such a list in response to a follow-up email request.

However much she might be hated by climate change denialists, Dr. Oreskes is often welcomed on college campuses these days. She usually outlines the decades of research supporting the idea that human emissions pose serious risks.

“One of the things that should always be asked about scientific evidence is, how old is it?” Dr. Oreskes said. “It’s like wine. If the science about climate change were only a few years old, I’d be a skeptic, too.”

Dr. Oreskes and Dr. Conway keep looking for ways to reach new audiences. Last year, they published a short work of science fiction, written as a historical essay from the distant future. “The Collapse of Western Civilization: A View From the Future” argues that conservatives, by fighting sensible action to cope with the climate crisis, are essentially guaranteeing the long-term outcome they fear, a huge expansion of government.

studies usually detect only modest effects that merely tend to whittle your chances of succumbing to a particular disease from small to somewhat smaller

The odds that anything useful will survive from any of these studies are poor,” says Ioannidis—dismissing in a breath a good chunk of the research into which we sink about $100 billion a year in the United States alone.

nutritional studies aren’t the worst. Drug studies have the added corruptive force of financial conflict of interest.

Even when the evidence shows that a particular research idea is wrong, if you have thousands of scientists who have invested their careers in it, they’ll continue to publish papers on it,” he says. “It’s like an epidemic, in the sense that they’re infected with these wrong ideas, and they’re spreading it to other researchers through journals.

Nature, the grande dame of science journals, stated in a 2006 editorial, “Scientists understand that peer review per se provides only a minimal assurance of quality, and that the public conception of peer review as a stamp of authentication is far from the truth.

The ultimate protection against research error and bias is supposed to come from the way scientists constantly retest each other’s results—except they don’t. Only the most prominent findings are likely to be put to the test, because there’s likely to be publication payoff in firming up the proof, or contradicting it.

even for medicine’s most influential studies, the evidence sometimes remains surprisingly narrow. Of those 45 super-cited studies that Ioannidis focused on, 11 had never been retested

even when a research error is outed, it typically persists for years or even decades.

much, perhaps even most, of what doctors do has never been formally put to the test in credible studies, given that the need to do so became obvious to the field only in the 1990s

Other meta-research experts have confirmed that similar issues distort research in all fields of science, from physics to economics (where the highly regarded economists J. Bradford DeLong and Kevin Lang once showed how a remarkably consistent paucity of strong evidence in published economics studies made it unlikely that any of them were right

His PLoS Medicine paper is the most downloaded in the journal’s history, and it’s not even Ioannidis’s most-cited work

while his fellow researchers seem to be getting the message, he hasn’t necessarily forced anyone to do a better job. He fears he won’t in the end have done much to improve anyone’s health. “There may not be fierce objections to what I’m saying,” he explains. “But it’s difficult to change the way that everyday doctors, patients, and healthy people think and behave.”

“Usually what happens is that the doctor will ask for a suite of biochemical tests—liver fat, pancreas function, and so on,” she tells me. “The tests could turn up something, but they’re probably irrelevant. Just having a good talk with the patient and getting a close history is much more likely to tell me what’s wrong.” Of course, the doctors have all been trained to order these tests, she notes, and doing so is a lot quicker than a long bedside chat. They’re also trained to ply the patient with whatever drugs might help whack any errant test numbers back into line.

What they’re not trained to do is to go back and look at the research papers that helped make these drugs the standard of care. “When you look the papers up, you often find the drugs didn’t even work better than a placebo. And no one tested how they worked in combination with the other drugs,” she says. “Just taking the patient off everything can improve their health right away.” But not only is checking out the research another time-consuming task, patients often don’t even like it when they’re taken off their drugs, she explains; they find their prescriptions reassuring.

Already feeling that they’re fighting to keep patients from turning to alternative medical treatments such as homeopathy, or misdiagnosing themselves on the Internet, or simply neglecting medical treatment altogether, many researchers and physicians aren’t eager to provide even more reason to be skeptical of what doctors do—not to mention how public disenchantment with medicine could affect research funding.

We could solve much of the wrongness problem, Ioannidis says, if the world simply stopped expecting scientists to be right. That’s because being wrong in science is fine, and even necessary—as long as scientists recognize that they blew it, report their mistake openly instead of disguising it as a success, and then move on to the next thing, until they come up with the very occasional genuine breakthrough

Science is a noble endeavor, but it’s also a low-yield endeavor,” he says. “I’m not sure that more than a very small percentage of medical research is ever likely to lead to major improvements in clinical outcomes and quality of life. We should be very comfortable with that fact.”

“The big problem is that the culture is such that researchers spin their work in a way that tells a prettier story than what they really found,” said Jonathan Schooler, a psychologist at the University of California, Santa Barbara. “It’s almost like everyone is on steroids, and to compete you have to take steroids as well.”

Dr. Stapel published papers on the effect of power on hypocrisy, on racial stereotyping and on how advertisements affect how people view themselves. Many of his findings appeared in newspapers around the world, including The New York Times, which reported in December on his study about advertising and identity.

Dr. Stapel was able to operate for so long, the committee said, in large measure because he was “lord of the data,” the only person who saw the experimental evidence that had been gathered (or fabricated). This is a widespread problem in psychology, said Jelte M. Wicherts, a psychologist at the University of Amsterdam. In a recent survey, two-thirds of Dutch research psychologists said they did not make their raw data available for other researchers to see. “This is in violation of ethical rules established in the field,” Dr. Wicherts said.

In a survey of more than 2,000 American psychologists scheduled to be published this year, Leslie John of Harvard Business School and two colleagues found that 70 percent had acknowledged, anonymously, to cutting some corners in reporting data. About a third said they had reported an unexpected finding as predicted from the start, and about 1 percent admitted to falsifying data.

Also common is a self-serving statistical sloppiness. In an analysis published this year, Dr. Wicherts and Marjan Bakker, also at the University of Amsterdam, searched a random sample of 281 psychology papers for statistical errors. They found that about half of the papers in high-end journals contained some statistical error, and that about 15 percent of all papers had at least one error tha

t changed a reported finding — almost always in opposition to the authors’ hypothesis.

an analysis of 49 studies appearing Wednesday in the journal PLoS One, by Dr. Wicherts, Dr. Bakker and Dylan Molenaar, found that the more reluctant that scientists were to share their data, the more likely that evidence contradicted their reported findings.

“We know the general tendency of humans to draw the conclusions they want to draw — there’s a different threshold,” said Joseph P. Simmons, a psychologist at the University of Pennsylvania’s Wharton School. “With findings we want to see, we ask, ‘Can I believe this?’ With those we don’t, we ask, ‘Must I believe this?’

That is the hardest thing to accept,”

“It proves not to have been a one-time error, but rather a chain of errors that were allowed to happen,” Mr. Pötsch said.

“a mind-set in some areas of the company that tolerated breaches of the rules.”

“We have to understand how this came about,” Mr. Pötsch said. “That is the only way we can prevent it from happening again.”