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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?

Computers are very, very fast at making calculations. Moreover, they can be counted on to calculate faithfully—without getting tired or emotional or changing their mode of analysis in midstream. But this does not mean that computers produce perfect forecasts, or even necessarily good ones. The acronym GIGO (“garbage in, garbage out”) sums up this problem. If you give a computer bad data, or devise a foolish set of instructions for it to analyze, it won’t spin straw into gold. Meanwhile, computers are not very good at tasks that require creativity and imagination, like devising strategies or developing theories about the way the world works. Computers are most useful to forecasters, therefore, in fields like weather forecasting and chess where the system abides by relatively simple and well-understood laws, but where the equations that govern the system must be solved many times over in order to produce a good forecast. They seem to have helped very little in fields like economic or earthquake forecasting where our understanding of root causes is blurrier and the data is noisier. In each of those fields, there were high hopes for computer-driven forecasting in the 1970s and 1980s when computers became more accessible to everyday academics and scientists, but little progress has been made since then.

It seems we may all be vulnerable to moral illusions the ethical equivalent of the bending lines that trick the eye on cereal boxes and in psychology textbooks. Illusions are a favorite tool of perception scientists for exposing the workings of the five senses, and of philosophers for shaking people out of the naïve belief that our minds give us a transparent window onto the world (since if our eyes can be fooled by an illusion, why should we trust them at other times?). Today, a new field is using illusions to unmask a sixth sense, the moral sense.

The first hallmark of moralization is that the rules it invokes are felt to be universal. Prohibitions of rape and murder, for example, are felt not to be matters of local custom but to be universally and objectively warranted. One can easily say, “I don’t like brussels sprouts, but I don’t care if you eat them,” but no one would say, “I don’t like killing, but I don’t care if you murder someone.”The other hallmark is that people feel that those who commit immoral acts deserve to be punished.

Until recently, it was understood that some people didn’t enjoy smoking or avoided it because it was hazardous to their health. But with the discovery of the harmful effects of secondhand smoke, smoking is now treated as immoral. Smokers are ostracized; images of people smoking are censored; and entities touched by smoke are felt to be contaminated (so hotels have not only nonsmoking rooms but nonsmoking floors). The desire for retribution has been visited on tobacco companies, who have been slapped with staggering “punitive damages.” At the same time, many behaviors have been amoralized, switched from moral failings to lifestyle choices.

Predicting the Next Financial CrisisWhy do financial crises occur – and when will the next one come? In the past, economic theory has failed to answer these questions. In this week’s Science Journal Perspectives, economists, physicists, epidemiologists, climate scientists and ecologists call to establish a new early warning system to avoid future global financial crises. They argue that the methods used by scientists to predict weather, traffic or disease epidemics should be used to simulate the financial systems, which could help to avoid the failures we have seen in the past. Professor Doyne tells Jack how the analysis of complex networks could and should be applied to the economy.

A landmark 2015 report that cast doubt on the results of dozens of published psychology studies has exposed deep divisions in the field, serving as a reality check for many working researchers but as an affront to others who continue to insist the original research was sound. On Thursday, a group of four researchers publicly challenged the report, arguing that it was statistically flawed and, as a result, wrong.The 2015 report, called the Reproducibility Project, found that less than 40 studies in a sample of 100 psychology papers in leading journals held up when retested by an independent team. The new critique by the four researchers countered that when that team’s statistical methodology was adjusted, the rate was closer to 100 percent.

Does bad behavior in movies or other media lead people to behave badly? There’s plenty of research on the link between onscreen media and risky behaviors like unprotected sex, binge drinking, fast driving and even violence. One large meta-analysis of such studies concluded that exposure to risk-glorifying media is associated with risky behaviors by people who consume that media. But causality issues plague most studies in this area: People who engage in risky behaviors may prefer to consume risk-glorifying media. These studies also tend to measure attitudes in controlled lab settings rather than in real life.

Much of the moral case for bodycams, that they reduce police violence, rests on a single experiment: the 2012 Rialto study