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Drug companies have a problem: they are finding it ever harder to get painkillers through clinical trials. But this isn't necessarily because the drugs are getting worse. An extensive analysis of trial data1 has found that responses to sham treatments have become stronger over time, making it harder to prove a drug’s advantage over placebo. The change in reponse to placebo treatments for pain, discovered by researchers in Canada, holds true only for US clinical trials. "We were absolutely floored when we found out," says Jeffrey Mogil, who directs the pain-genetics lab at McGill University in Montreal and led the analysis. Simply being in a US trial and receiving sham treatment now seems to relieve pain almost as effectively as many promising new drugs. Mogil thinks that as US trials get longer, larger and more expensive, they may be enhancing participants’ expectations of their effectiveness.

Mischel’s story isn’t surprising—nicotine is addictive, and quitting is difficult—except for one thing: Mischel is the creator of the marshmallow test, one of the most famous experiments in the history of psychology, which is often cited as evidence of the importance of self-control. In the original test, which was administered at the Bing Nursery School, at Stanford, in the nineteen-sixties, Mischel’s team would present a child with a treat (marshmallows were just one option) and tell her that she could either eat the one treat immediately or wait alone in the room for several minutes until the researcher returned, at which point she could have two treats. The promised treats were always visible and the child knew that all she had to do to stop the agonizing wait was ring a bell to call the experimenter back—although in that case, she wouldn’t get the second treat. The longer a child delayed gratification, Mischel found—that is, the longer she was able to wait—the better she would fare later in life at numerous measures of what we now call executive function. She would perform better academically, earn more money, and be healthier and happier. She would also be more likely to avoid a number of negative outcomes, including jail time, obesity, and drug use.

A group of organizations, including Microsoft and the Rembrandthuis museum, have collaborated to produce a new painting by Rembrandt. Or rather, "by" Rembrandt. The team wrote software that analyzed the Dutch master's entire catalog of paintings and used the data to create a 3D-printed Rembrandt-esque painting.

Knowledge, then, is less a canon than a consensus in a state of constant disruption. Part of the disruption has to do with error and its correction, but another part with simple newness—outright discoveries or new modes of classification and analysis, often enabled by technology.

ore commonly, however, changes in scientific facts reflect the way that science is done. Mr. Arbesman describes the "Decline Effect"—the tendency of an original scientific publication to present results that seem far more compelling than those of later studies. Such a tendency has been documented in the medical literature over the past decade by John Ioannidis, a researcher at Stanford, in areas as diverse as HIV therapy, angioplasty and stroke treatment. The cause of the decline may well be a potent combination of random chance (generating an excessively impressive result) and publication bias (leading positive results to get preferentially published). If shaky claims enter the realm of science too quickly, firmer ones often meet resistance. As Mr. Arbesman notes, scientists struggle to let go of long-held beliefs, something that Daniel Kahneman has described as "theory-induced blindness." Had the Austrian medical community in the 1840s accepted the controversial conclusions of Dr. Ignaz Semmelweis that physicians were responsible for the spread of childbed fever—and heeded his hand-washing recommendations—a devastating outbreak of the disease might have been averted.

The opposite of that is the hot-hand fallacy — the belief that winning streaks, whether in basketball or coin tossing, have a tendency to continue, as if propelled by their own momentum. Both misconceptions are reflections of the brain’s wired-in rejection of the power that randomness holds over our lives. Look deep enough, we instinctively believe, and we may uncover a hidden order.

A working paper published this summer has caused a stir by proposing that a classic body of research disproving the existence of the hot hand in basketball is flawed by a subtle misperception about randomness. If the analysis is correct, the possibility remains that the hot hand is real.

Taken to extremes, seeing connections that don’t exist can be a symptom of a psychiatric condition called apophenia. In less pathological forms, the brain’s hunger for pattern gives rise to superstitions (astrology, numerology) and is a driving factor in what has been called a replication crisis in science — a growing number of papers that cannot be confirmed by other laboratories.

Last October we introduced a new feature in which, each Monday morning this school year, we posted a New York Times photograph without a caption, then invited students to answer three deceptively simple questions about it: What’s going on in this picture? What do you see that makes you say that? What more can you find? As student answers poured in to the blog each week — this shows someone learning a back-flip; I think he’s in the military because of his camouflage shirt; The background makes it look like a movie set — our collaborators for the feature, Visual Thinking Strategies, acted as live moderators, linking thoughts and posting further questions intended to help them go deeper and see more. Most weeks that created a lively debate in our comments section, as students of all ages, backgrounds and places pushed each other to find detail and defend interpretations.

Is big data really all it’s cracked up to be? There is no doubt that big data is a valuable tool that has already had a critical impact in certain areas. For instance, almost every successful artificial intelligence computer program in the last 20 years, from Google’s search engine to the I.B.M. “Jeopardy!” champion Watson, has involved the substantial crunching of large bodies of data. But precisely because of its newfound popularity and growing use, we need to be levelheaded about what big data can — and can’t — do.The first thing to note is that although big data is very good at detecting correlations, especially subtle correlations that an analysis of smaller data sets might miss, it never tells us which correlations are meaningful.

hortly before the dreadful crash of Germanwings Flight 9525, I happened to be reading part of “The Second Machine Age,” a book by two academics at M.I.T., Erik Brynjolfsson and Andrew McAfee, about the coming automation of many professions previously thought of as impervious to technological change, such as those of drivers, doctors, market researchers, and soldiers. With the advances being made in robotics, data analysis, and artificial intelligence, Brynjolfsson and McAfee argue, we are on the cusp of a third industrial revolution.

Scientists are beginning to tap into a wellspring of knowledge buried in the ancient stories of Australia's Aboriginal peoples. But the loss of indigenous languages could mean it is too late to learn from them.

If we’re going to rely on science as a means for reaching the truth — and it’s still the best tool we have — it’s important that we understand and respect just how difficult it is to get a rigorous result

Scientists’ overreliance on p-values has led at least one journal to decide it has had enough of them. In February, Basic and Applied Social Psychology announced that it will no longer publish p-values.

P-hacking and similar types of manipulations often arise from human biases. “You can do it in unconscious ways — I’ve done it in unconscious ways,” Simonsohn said. “You really believe your hypothesis and you get the data and there’s ambiguity about how to analyze it.” When the first analysis you try doesn’t spit out the result you want, you keep trying until you find one that does.

Is there a connection between language and how we think and behave? In particular, Chen wanted to know: does our language affect our economic decisions? Chen designed a study — which he describes in detail in this blog post — to look at how language might affect individual’s ability to save for the future. According to his results, it does — big time.

Using vast inventories of data and meticulous analysis, Chen found that huge economic differences accompany this linguistic discrepancy. Futureless language speakers are 30 percent more likely to report having saved in any given year than futured language speakers.

But that’s only the beginning. There’s a wide field of research on the link between language and both psychology and behavior. Here, a few fascinating examples:

In 1998 the journalist Ron Rosenbaum published Explaining Hitler. Contrary to what the title might suggest, it is not an explanation of Hitler, per se, but rather a 500-page meta-analysis of different theories intended to explain Hitler. Ron Rosenbaum traveled from the ruins of Hitler's Austrian birthplace to meet the historians, psychologists, and Nazi-hunters who have promoted different explanations for Hitler's evil. Whether the basis of the theories are plausible (Hitler's Jewish ancestry) or extremely unlikely (Hitler's penis was bitten off while he attempted to pee into the mouth of a billy goat) they are all presented with a relentless skepticism that makes reading Explaining Hitler a unique and destabilizing experience.

Illegal public art is in the news. The most notorious instance this summer was the switch of flags on the Brooklyn Bridge, by two German artists, from the Stars and Stripes to all-white versions of the same. Others include a Canadian artist’s scrawls, partly in blood, on a wall in the Jeff Koons retrospective at the Whitney Museum and, in Moscow, the painting of a star ornament atop a Stalin-era tower, in Ukrainian national colors. Internationally, the British midnight muralist Banksy continues his waggish depredations, rivalled of late by a female upstart called Bambi, who likewise stencils images, only with a sexy-feminist spin. The over-all phenomenon could use a name—I propose Stunt art—and some analysis, starting with distinctions.

As a category of volunteer art, Stunt art borders the genres of spray-can graffiti and spectacular illegal sport, such as scaling or parachuting from tall buildings.

Stuntism is to art as weeds are to horticulture: plants in the wrong place. Authorities, social or botanical, define the wrongness, which becomes more arbitrary the more you think about it. Some weeds are as lovely as tulips. A superb gardener I know welcomes the sceptered majesty of common mullein (distinct from the mannerly hybrid varieties) wherever it opts to sprout. So may it be with Stunt art, in a time given to fanatical constraints on human-natural cussedness.