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As forests are cleared and species vanish, there's one other loss: a world of languages A new report shows a direct link between disappearing habitats and the loss of languages. One in four of the world's 7,000 spoken tongues is now at risk of falling silent for ever as the threat to cultural biodiversity grows

Who decides what constitutes “proof”? Can “proof” come only from experiments? If so, we’re in trouble, because we can never do an experiment in humans for any exposure that is suspected to be harmful.

The problem is that as new data come along, what was once proven can become unproven again by new expert panels who now consider this new evidence and come to a different conclusion. This leads to the perhaps uncomfortable definition of “proof” as “a consensus of experts.”

The point of emphasis is that there is no hard formula on how to consider the evidence; it is a group decision by a panel of experts (the scientific jury) in which sometimes the epidemiological evidence is so strong that it doesn’t matter whether mice get cancer or not. And sometimes the epidemiology is insufficient to render a verdict on causation and so the toxicology becomes important in making the decision.

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.

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.

“Just as with the physical world, where hurricanes, tornadoes, and other ‘acts of God’ just happen, the same is true of the social world,” he wrote. “Some people just do things. They assassinate world leaders, act on poorly thought out ideologies, and leave clues at the scene of the crime. Too strong a belief in the rationality of people in general, or of the world, will lead us to seek purposive explanations where none exists.”

He says conspiracy theorists rely on what he calls “errant data,” or random minutiae within a terror attack or major event that can—and maybe should—go unexplained in reality. Those pushing conspiracies, however, seize on that unexplained info and attempt to explain it in full.It is an effort to connect every dot on the map—every blade of grass on the Grassy Knoll—even if some dots have nothing to with the larger event at all

Crisis class theory is a weirdly hopeful, terribly reductionist coping mechanism, a way to explain a world that can be unjust and needlessly cruel—but wouldn’t be if the “bad guys” controlling it all were vanquished.“There is surely some psychological comfort in believing that a horrific event like a mass murder of schoolchildren never really happened at all—that it was all fake,” he writes.

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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:

There is indeed ample data that institutions and individuals can wreak havoc when they deviate from certain principles of logic and objectivity. There is also a good deal of dispiriting evidence about the rationality of voters that spurs questions about the effectiveness—and even the legitimacy—of democratic government. Yet much of the work of cognitive scientists—even fascinating Nobel Prize-winning research by Daniel Kahneman—leaves me edified but not alarmed. The human capacity for reason may be fragile and partial but it is not belied by studies in which large percentages of subjects answer a few tricky questions incorrectly.

My hypothesis is that while we love reading about humanity’s tendency toward the irrational, we take offense when light is thrown on our own individual incompetencies. 

Today, machines seem to get better every day at digesting vast gulps of information—and they remain as emotionally inert as ever. But since the nineteen-nineties a small number of researchers have been working to give computers the capacity to read our feelings and react, in ways that have come to seem startlingly human. Experts on the voice have trained computers to identify deep patterns in vocal pitch, rhythm, and intensity; their software can scan a conversation between a woman and a child and determine if the woman is a mother, whether she is looking the child in the eye, whether she is angry or frustrated or joyful. Other machines can measure sentiment by assessing the arrangement of our words, or by reading our gestures. Still others can do so from facial expressions. Our faces are organs of emotional communication; by some estimates, we transmit more data with our expressions than with what we say, and a few pioneers dedicated to decoding this information have made tremendous progress. Perhaps the most successful is an Egyptian scientist living near Boston, Rana el Kaliouby. Her company, Affectiva, formed in 2009, has been ranked by the business press as one of the country’s fastest-growing startups, and Kaliouby, thirty-six, has been called a “rock star.” There is good money in emotionally responsive machines, it turns out. For Kaliouby, this is no surprise: soon, she is certain, they will be ubiquitous.

A recent paper in the journal Cognition, for instance, quipped that if people were as bad at naming sights as they are at naming scents, “they would be diagnosed as aphasic and sent for medical help.” The paper quoted scattershot attempts by participants in a previous study to label the smell of lemon: “air freshener,” “bathroom freshener,” “magic marker,” “candy,” “lemon-fresh Pledge,” “some kind of fruit.” This sort of difficulty seems to have very little to do, however, with the nose’s actual capabilities. Last spring, an article in the journal Science reported that we are capable of discriminating more than a trillion different odors. (A biologist at Caltech subsequently disputed the finding, arguing that it contained mathematical errors, though he acknowledged the “richness of human olfactory experience.”) Whence, then, our bumbling translation of scent into speech?

He's here to illustrate one of his more provocative experiments - who is more likely to stop for pedestrians, the rich or the poor?

“Non-overlapping magisteria” has a nice ring to it. The problem is that there are many religious claims that not only “overlap” with empirical data but are incompatible with it. As a scientist who also spends a fair amount of time in the public arena, if I am asked if our understanding of the Big Bang conflicts with the idea of a six-thousand-year-old universe, I face a choice: I can betray my scientific values, or encourage that person to doubt his or her own beliefs. More often than you might think, teaching science is inseparable from teaching doubt.

“The Copernicus Complex addresses some of the deepest questions humans have ever asked. How weird are we? Was our existence highly probable, or improbable? Even miraculous? You can break this question down into more specific questions: How probable was our universe? Our galaxy? Solar system? Planet? How probable was life? And how probable were creatures like us, who can ponder their probability?

Scientists still don’t have a clue why our universe has the form we observe, or how life began on the Earth some 3.6 billion years ago, or whether life exists elsewhere. During his talk at Stevens, Scharf acknowledged that we may never observe exoplanets in sufficient detail to know, with certainty, that they harbor life.

“Unfortunately, you cannot determine the probability of the universe or of life on Earth when you have only one universe and one history of life to contemplate. Statistics require more than one data point.

The invention of religion is a big bang in human history. Gods and spirits helped explain the unexplainable, and religious belief gave meaning and purpose to people struggling to survive. But what if everything we thought we knew about religion was wrong? What if belief in the supernatural is window dressing on what really matters—elaborate rituals that foster group cohesion, creating personal bonds that people are willing to die for. Anthropologist Harvey Whitehouse thinks too much talk about religion is based on loose conjecture and simplistic explanations. Whitehouse directs the Institute of Cognitive and Evolutionary Anthropology at Oxford University. For years he’s been collaborating with scholars around the world to build a massive body of data that grounds the study of religion in science. Whitehouse draws on an array of disciplines—archeology, ethnography, history, evolutionary psychology, cognitive science—to construct a profile of religious practices.

I suppose people do try to fill in the gaps in their knowledge by invoking supernatural explanations. But many other situations prompt supernatural explanations. Perhaps the most common one is thinking there’s a ritual that can help us when we’re doing something with a high risk of failure. Lots of people go to football matches wearing their lucky pants or lucky shirt. And you get players doing all sorts of rituals when there’s a high-risk situation like taking a penalty kick.

We tend to take a few bits and pieces of the most familiar religions and see them as emblematic of what’s ancient and pan-human. But those things that are ancient and pan-human are actually ubiquitous and not really part of world religions. Again, it really depends on what we mean by “religion.” I think the best way to answer that question is to try and figure out which cognitive capacities came first.

last month, Bill Gates released a video of one of the latest ventures funded by the Bill and Melinda Gates Foundation: the Omniprocessor, a Seattle-based processing plant that burns sewage to make clean drinking water. In the video, Gates raises a glass of water to his lips. Just five minutes ago, the caption explains, that water was human waste. Gates takes a sip. “It’s water,” he says. “Having studied the engineering behind it,” he writes, on the foundation’s blog, “I would happily drink it every day. It’s that safe.”

Gerd Gigerenzer's test In 2006 and 2007 Gigerenzer gave a series of statistics workshops to gynaecologists, and kicked off every session with the same question: A 50-year-old woman, no symptoms, participates in routine mammography screening. She tests positive, is alarmed, and wants to know from you whether she has breast cancer for certain or what the chances are. Apart from the screening results, you know nothing else about this woman. How many women who test positive actually have breast cancer? What is the best answer? nine in 10 eight in 10 one in 10 one in 100 Gigerenzer then supplied the doctors with data about Western women of this age. (His figures were based on US studies from the 1990s, rounded up or down for simplicity - recent stats from Britain's National Health Service are slightly different.) The probability that a woman has breast cancer is 1% ("prevalence") If a woman has breast cancer, the probability that she tests positive is 90% ("sensitivity") If a woman does not have breast cancer, the probability that she nevertheless tests positive is 9% ("false alarm rate") In one session, almost half the gynaecologists said the woman's chance of having cancer was nine in 10. Only 21% said that the figure was one in 10 - which is the correct answer.

There are approximately seven billion inhabitants of earth. They conduct their lives in one or several of about seven thousand languages—multilingualism is a global norm. Linguists acknowledge that the data are inexact, but by the end of this century perhaps as many as fifty per cent of the world’s languages will, at best, exist only in archives and on recordings. According to the calculations of the Catalogue of Endangered Languages (ELCat)—a joint effort of linguists at the University of Hawaii, Manoa, and at the University of Eastern Michigan—nearly thirty language families have disappeared since 1960. If the historical rate of loss is averaged, a language dies about every four months.