Traffic Jams
Nobody likes traffic jams, yet they have been one of the plagues of life since at least Roman times. Why is this so? The short explanation is that they take place whenever more people want to use a given transportation facility than it can handle. Yet there is clearly more to the story than the simple bottleneck. Why do so many traffic jams seem to come out of nowhere?
A Mathematicians, physicists and computer programmers have been trying to disentangle traffic jams for decades. Traffic-flow theory had its beginnings in the 1930s, the first computer simulations of traffic were designed in the 1950s, and theoretical breakthroughs have followed regularly in every decade since. In the 1980s and '90s, as computers became exponentially faster, new models of traffic flow employing analytical methods based on, for example, non-linear dynamics and statistical physics, were developed.
B Most traffic is tied to predetermined patterns: the rush hour, the weekend exodus, the holiday getaway. So, in rudimentary computer models of traffic flow, everyone leaves home at a predetermined time, everyone knows exactly what route to take and so forth. Many recent models, however, throw a bit of human capriciousness into the equation: their virtual people accelerate at different speeds from day to day, for instance, or they do not always change lanes in the same circumstances. Radically different traffic patterns can result.
C Traffic often appears chaotic: virtually imperceptible changes can give rise to large effects. Ironically, computer simulations suggest that traffic is most sensitive to disturbances when it is flowing most efficiently. Both an empty system and a gridlocked system are easy to predict, but a stream of cars hurtling at top speed along a highway is highly unpredictable, and it can become ensnarled simply as a result of the speed. Would you prefer a trip to the airport in a definite thirty minutes, or a faster route that usually takes twenty minutes except every tenth time, when it takes two hours?
D The laws governing spontaneous traffic jams are dismayingly fundamental: even grains of sand falling down a glass tube can form traffic jams, as investigators in Germany have shown. The mathematics of granular flow and of water flowing down a river is very similar to the mathematics of traffic flow. It is not yet clear, however, to what extent spontaneous jams play a role in everyday traffic. Computer simulations confirm that most jams are caused by tunnels, construction sites and other simple reasons.
E Once drivers are caught in a jam, they almost always exacerbate the problem. The road beyond the jam may be wide and clear, but the number of cars accelerating away from the jam every hour in every lane will usually be far less than the lane capacity. Recent research suggests the cause is quite straightforward: people are sloppy about getting their cars back up to speed. Even if drivers take an average of three seconds to get going – only a second more than the typical reaction time – only 1,200 will leave the jam after an hour while 1,800 will join it. The damage has been done.
F A familiar scenario: the freeway becomes like a parking lot, so transportation planners add a new lane, and traffic flows more freely. For a while everybody is happy: people get home faster. But then a few people realise they now have time to stop off at home, after work, before going shopping. Others recognise that they can live farther away from the city, on a larger plot, without increasing their commuting time. Soon the congestion builds up. This 'induced travel' may be the hardest element of transportation to model. Erratic as drivers may be, driving is heavily constrained by physics: a car occupies a fixed amount of space, and can accelerate and brake only so fast. The wish for travel, by contrast, can be entirely whimsical.
G Research has shown that cities could build their way out of congestion, but the results might not be places where many people would want to live. In any event, congestion is a poor measure of the efficiency of a transportation system. Are you better off in a congested city such as New York, where you can walk to five movie theatres in ten minutes, or in a relatively uncongested city such as Santa Fe, New Mexico, where you drive to five movie theatres in twenty minutes? Congested cities can be more convenient than uncongested cities. And perhaps in trying to solve the problem of congestion we are actually on a fool's mission.
Understanding and Protecting Elephants
A The future of the African elephant is at risk. They are often shot by poachers for their ivory and this is responsible for most of the decline in elephant numbers. But habitat loss is important too, and not just the changing of bush into farmland. Roads, railways and fences stop elephants moving around, and an elephant needs a lot of room. According to George Wittemyer of Save the Elephants, an average elephant ranges over 1,500 square kilometres over a year and may travel as much as 60 kilometres a day.
B The question is whether elephants and people can ever coexist peacefully. People who worry that the answer may be 'no' fear the loss of more than just another species of animal. Elephants seem to have evolved intelligence, and possibly even consciousness. Though they may not be alone in this (similar claims are made for certain whales, some carnivores like lions and hyenas, and some birds), they are certainly part of a small group. Self-awareness is one indication of the vast capacity for thinking and intellect that exists in the elephant. They can, in fact, identify themselves in a mirror, something that is extremely rare in the animal kingdom. Another example of superior intellect is the elephant's ability to have fun and display a sense of humour. Elephants in zoos have even been seen stealing onlookers' caps and hiding them in playful teasing. Losing even one example of how intelligence develops would reduce the ability of biologists to understand the process of how intelligence has evolved in animals.
C Apart from people, no species on Earth has a more complex society than elephants. Their social arrangements centre around groups of four or five females and their young that are led by a matriarch who is mother, grandmother, great-grandmother, sister or aunt to most of them. Though males are forced to depart their birth group when they mature, females usually remain in it their entire lives. Elephant families are part of bigger 'kinship' groups that come together and separate at will. Moreover, each kinship group is part of what is called a clan. Clans gather in the dry season, when the resources capable of supporting elephants are limited. All clan members know each other and, since a clan will usually have 100 to 200 adult members, this means an adult female can recognise and have meaningful social relations with that many other individuals. A figure of between 100 and 200 acquaintances is similar to the number of people a human being can maintain meaningful social relationships with – a value known as Dunbar's number. Dunbar's number for people is about 150.
D Being able to recall details of such large numbers of individuals means elephants require enormous mental powers. Details of how their brains work are not known, but one thing which is known is that they have big hippocampuses. These structures, one in each hemisphere of the brain, are involved in the formation of long-term recall. Compared with the size of its brain, an elephant's hippocampuses are about 40 per cent larger than those of a human being.
E Elephants can seemingly solve problems by thinking about them in abstract terms. Experiments conducted on domesticated Asian elephants show that they are able to manipulate nearby objects, such as branches, as tools to get food which is out of reach. This is something some other species, such as great apes, can do, but which most animals find impossible. For all of these reasons then, elephants are of great scientific interest. But the focus of almost all elephant researchers has shifted from understanding the animals to trying to preserve them.
F Another, though secondary, cause of elephant decline, is changes in land use in Africa. The human inhabitants of areas around African elephant reserves have traditionally survived by moving herds of cattle from one grazing place to another. One source of conflict with elephants has been competition for pasture, as the herders' populations have grown. But, additionally, some herders have begun to settle down. Buildings and fences are appearing on land which elephants have traditionally crossed as they travel from one place to another. Elephants have places where they prefer to live and, when travelling between these, which they often do at night, they tend to follow narrow corridors. Keeping these corridors clear of development is essential to the well-being of elephants.
G Understanding elephants' behaviour also permits it to be changed in ways that help reduce direct conflict between elephants and people. One such project uses elephants' fear of bees. Bees are the only animals, apart from humans, that elephants seem truly afraid of. This is because, although a bee's sting cannot penetrate most parts of an elephant's hide, groups of bees tend to attack the eyes and the tips of the trunks, an elephant's most sensitive parts. Elephants can't protect themselves from the bees – not even by swinging their tails and flapping their ears.
H Knowing this, scientists developed the idea of protecting farms with bee fences. The sort of fence most African farmers can afford is too weak to keep an elephant away from their crops, but a bee fence, though even weaker, will achieve this. The fence consists of pairs of poles placed at three-metre intervals, between which beehives are hung. This fence is enough to stop elephants immediately. They are so scared that half the hives can be fake, and the fence still keeps the elephants out. Bee-fenced farms suffer far fewer elephant attacks than those with conventional protection. As a bonus, the farmers earn extra income from the honey the bees produce.
Is artificial intelligence a threat?
Science correspondent Gary Marcus gives his views on whether we should be concerned about the future development of artificial intelligence
If the latest reports are accurate, artificial intelligence (AI) is moving so fast it seems almost 'magical.' Self-driving cars have arrived; computers can listen to your voice and find the nearest movie theatre for you; there may soon be computers training medical students, and eventually helping diagnose patients. Scarcely a month goes by without the announcement of a new AI product or technique. Yet, it may be too soon to express such enthusiasm: we still haven't produced machines with common sense, natural language processing, or the ability to create other machines. Our efforts at directly simulating human brains remain primitive.
However, the only real difference between enthusiasts and sceptics is the time frame. The futurist and inventor Ray Kurzweil thinks true, human-level AI will arrive in less than two decades. I'd predict that it will be at least double that, given how the challenges in building AI, especially at the software level, are much greater than Kurzweil admits. But in the future, nobody will care about how long it took, only what happened next. It's likely that machines will be smarter than us at almost everything in a century from now. There might be a few jobs left for entertainers, writers, and other creative types, but computers will eventually be able to program themselves and reason in ways that we can only dimly imagine. And they will be able to do it every second of every day, without sleep or coffee breaks.
For many, this vision of the future is inspiring. Ray Kurzweil has written about the point when AI becomes more intelligent than humans and speculated that we may then replace our brains with computers and modify our bodies with robotic enhancements; scientist and entrepreneur Peter Diamandis has argued that advances in AI will bring in a new era of 'abundance,' with enough food, water, and consumer gadgets for all. However, even if you put aside the worries about what super-advanced AI might do to the labour market, there's another concern: that powerful AI might ultimately battle us for the control of resources. Most people dismiss such fears, believing them to be the result of the over-influence of science-fiction movies. To the extent that people plan for the medium-term future, they worry about asteroids, the decline of fossil fuels, and global warming, not robots taking over the world.
But a new book by writer and documentary filmmaker James Barrat argues we should be at least slightly worried. Barrat's core argument is that the drive for self-preservation and resource acquisition may be inherent in all goal-driven systems with a certain degree of intelligence. A purely rational artificial intelligence might expand 'its idea of self-preservation to include proactive attacks on future threats', including, presumably, people who might be unwilling to surrender their assets to the machine. Barrat worries that without precise and detailed instructions, AI might go to extremes we'd consider ridiculous to fulfil its goals, perhaps taking control of all the world's energy supplies in order to maximize whatever calculation it was interested in.
Of course, one could try to ban super-intelligent computers altogether. But the competitive advantage of every advance in automation is so strong that many share my suspicion that passing laws forbidding such things will guarantee that someone else develops the technology in secret or in another country.
If machines eventually overtake us, as virtually everyone in the AI field believes they will, the key question is about values: how we instil them in machines, and how we negotiate with machines if their values differ greatly from our own. Some argue it would be wrong to assume that a super-intelligent machine will share the values we typically associate with human beings, such as kindness and empathy. Research might one day show that constructing a super-intelligence that has certain of these attitudes is possible, but the replication of the full range of human attributes seems unlikely – it is certainly technically easier to build a machine that is solely concerned with numbers and data. The cyberneticist Kevin Warwick was also right to ask how we can understand AI when its 'thinking' will occur in dimensions humans cannot conceive of.
It is important to realize that the machines' objectives may well alter as they get smarter. Once computers can effectively reprogram themselves, and therefore constantly develop themselves, the risk of machines outwitting humans in battles for resources cannot be dismissed. AI entrepreneur Danny Hillis believes we are close to one of the greatest transitions in the history of biological evolution, and that we are not fully aware of the capabilities of what we are in the process of creating. Already, advances in AI have created risks that we never dreamt of. Thanks to the internet, a huge amount of data is being collected about us and being fed to algorithms to make predictions about our behaviour as consumers, for example. Worryingly, people don't always know what information is being gathered or even that it is accurate. Although this subject now sparks a great deal of argument and is a cause for concern, few people thought about it seriously until recently. So what other risks lie ahead? Nobody really knows.
