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The researchers - Peera Wongupparaj, Veena Kumari and Robin Morris at Kings College London - did not themselves ask anyone to sit an IQ test, but they analysed data from 405 previous studies. Altogether, they harvested IQ test data from more than 200,000 participants, captured over 64 years and from 48 countries. Focusing on one part of the IQ test, the Raven's Progressive Matrices, they found that on average intelligence has risen the equivalent of 20 IQ points since 1950. IQ tests are designed to ensure that the average result is always 100, so this is a significant jump.

Today it is safe to say there are no unknown territories with dragons. However, it’s not quite true to say that every corner of the planet is charted. We may seem to have a map for everywhere, but that doesn’t mean they are complete, accurate or even trustworthy.For starters, all maps are biased toward their creator’s subjective view of the world. As Lewis Carroll famously pointed out, a perfectly objective and faithful 1:1 representation of the world would literally have to be the same size as the place it depicted. Therefore, mapmakers must make sensible design decisions in order to compress the physical world into a much smaller, flatter depiction. Those decisions inevitably introduce personal biases, however, such as our tendency to place ourselves at the centre of the world. “We always want to put ourselves on the map,” says Jerry Brotton, a professor of renaissance studies at Queen Mary University London, and author of A History of the World in 12 Maps. “Maps address an existential question as much as one that’s about orientation and coordinates.“We want to find ourselves on the map, but at the same time, we are also outside of the map, rising above the world and looking down as if we were god,” he continues. “It’s a transcendental experience.”

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.

‘“What if?” is a waste of time’ went the headline to the Cambridge historian Richard Evans’ piece in The Guardian last year. Surveying the many instances of public counterfactual discourse in the anniversary commemorations of the First World War, Evans wrote: ‘This kind of fantasising is now all the rage, and threatens to overwhelm our perceptions of what really happened in the past, pushing aside our attempts to explain it in favour of a futile and misguided attempt to decide whether the decisions taken in August 1914 were right or wrong.’

But hold on a minute.

If well-done counterfactuals can help us think them through, shouldn’t we allow what-ifs some space at the history table?

n a dissenting opinion in 1981, Supreme Court Justice William Brennan wrote that “eyewitness identification evidence is notoriously unreliable.” Dozens of scientific studies support this claim. Nevertheless, eyewitness testimony continues to be used widely, and many criminal cases hinge on it almost exclusively. Since 1989, two hundred and eighty people have been exonerated of sexual-assault charges in the U.S. Nearly three-quarters of those wrongful convictions relied, in whole or in part, on a mistaken identification by an eyewitness. Psychologists have long recognized that human memory is highly fallible. Hugo Münsterberg taught in one of the first American psychology departments, at Harvard. In a 1908 book called “On the Witness Stand,” he argued that, because people could not know when their memories had deceived them, the legal system’s safeguards against lying—oaths, penalties for perjury, and so on—were ineffective. He expected that teachers, doctors, and politicians would all be eager to reform their fields. “The lawyer alone is obdurate,” Münsterberg wrote.

Graphs can be as manipulative as words. Using tricks such as cutting axes, rescaling things, changing data from positive to negative, etc. Sometimes putting zero on the y-axis is wrong. So to be sure that you are communicating the right things, you need to evaluate the message that people are taking away. There are no absolute rules. It all depends on what you want to communicate.

The bottom line is that humans are very bad at understanding probability. Everyone finds it difficult, even I do. We just have to get better at it. We need to learn to spot when we are being manipulated.

To what extent can we and should we aspire to create machines that can outthink us? For example, Netflix has an algorithm that can predict what movies you will like based on the ones you've already seen and rated. Suppose a dating site were to develop a similar algorithm—maybe even a more sophisticated one—and predict with some accuracy which partner would be the best match for you. Whose advice would you trust more? The advice of the smart dating app or the advice of your parents or your friends?

The question, it seems to me, is should we use new genetic technologies only to cure disease and repair injury, or also to make ourselves better-than-well. Should we aspire to become the masters of our natures to protect our children and improve their life prospects?AdvertisementAdvertisement This goes back to the role of accident. Is the unpredictability of the child an important precondition of the unconditional love of parents for children? My worry is that if we go beyond health, we run the risk of turning parenthood into an extension of the consumer society.

The researcher who met with S. that day was twenty-seven-year-old Alexander Luria, whose fame as a founder of neuropsychology still lay before him. Luria began reeling off lists of random numbers and words and asking S. to repeat them, which he did, in ever-lengthening series. Even more remarkably, when Luria retested S. more than fifteen years later, he found those numbers and words still preserved in S.’s memory. “I simply had to admit that the capacity of his memory had no distinct limits,” Luria writes in his famous case study of S., “The Mind of a Mnemonist,” published in 1968 in both Russian and English.

A former journalist, equipped with an algorithm and the largest collection of murder records in the country, finds patterns in crime.

As a direct consequence of the evolution of the human social brain, and owing to the importance of our theory-of-mind skills in that process, we sometimes can't help but see intentions, desires, and beliefs in things that haven't even a smidgeon of a neural system. In particular, when inanimate objects do unexpected things, we sometimes reason about them just as we do for oddly behaving—or misbehaving—people. More than a few of us have kicked our broken-down vehicles in the sides and verbally abused our incompetent computers. Most of us stop short of actually believing these objects possess mental states—indeed, we would likely be hauled away to an asylum if we genuinely believed that they held malicious intent—but our emotions and behaviors toward such objects seem to betray our primitive, unconscious thinking: we act as though they're morally culpable for their actions.