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out, gesticulate, exchange insurance details and then drive off. But not on this occasion. No one got out of the cars for the simple reason that they had no humans inside them; the Tahoe and Land Rover were being controlled by computers competing in November's DARPA (the U.S. Defence Advanced Research Projects Agency) Urban Challenge.

B The idea that machines could perform to such standards is startling. Driving is a complex task that takes humans a long time to perfect. Yet here, each car had its on-board computer loaded with a digital map and route plans, and was instructed to negotiate busy roads; differentiate between pedestrians and stationary objects; determine whether other vehicles were parked or moving off; and handle various parking manoeuvres, which robots turn out to be unexpectedly adept at. Even more striking was the fact that the collision between the robot Land Rover, built by researchers at the Massachusetts Institute of Technology, and the Tahoe, fitted out by Cornell University Artificial Intelligence (AI) experts, was the only scrape in the entire competition. Yet only three years earlier, at DARPA's previous driverless car race, every robot competitor - directed to navigate across a stretch of open desert-either crashed or seized up before getting near the finishing line.

C It is a remarkable transition that has clear implications for the car of the future. More importantly, it demonstrates how robotics sciences and Artificial Intelligence have progressed in the past few years - a point stressed by Bill Gates, the Microsoft boss who is a convert to these causes. ‘The robotics industry is developing in much the same way the computer business did 30 years ago,’ he argues. As he points out, electronics companies make toys that mimic pets and children with increasing sophistication. 'I can envision a future in which robotic devices will become a nearly ubiquitous part of our day-to-day lives,’ says Gates. 'We may be on the verge of a new era, when the PC will get up off the desktop and allow us to see, hear, touch and manipulate objects in places where we are not physically present.’

D What is the potential for robots and computers in the near future? ‘The fact is we still have a way to go before real robots catch up with their science fiction counterparts,’ Gates says. So what are the stumbling blocks? One key difficulty is getting robots to know their place. This has nothing to do with class or etiquette,

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but concerns the simple issue of positioning. Humans

orient themselves with other objects in a room very easily. Robots find the task almost impossible. ‘Even something as simple as telling the difference between an open door and a window can be tricky for a robot,’ says Gates. This has, until recently, reduced robots to fairly static and cumbersome roles.

E For a long time, researchers tried to get round the problem by attempting to re-create the visual processing that goes on in the human cortex. However, that challenge has proved to be singularly exacting and complex. So scientists have turned to simpler alternatives: 'We have become far more pragmatic in our work,’ says Mello Cristianini, Professor of Artificial Intelligence at the University of Bristol in England and associate editor of the Journal of Artificial Intelligence Research. 'We are no longer trying to re-create human functions. Instead, we are looking for simpler solutions with basic electronic sensors, for example.’ This approach is exemplified by vacuuming robots such as the Electrolux Trilobite. The Trilobite scuttles around homes emitting ultrasound signals to create maps of rooms, which are remembered for future cleaning. Technology like this is now changing the face of robotics, says philosopher Ron Chrisley, director of the Centre for Research in Cognitive Science at the University of Sussex in England.

F Last year, a new Hong Kong restaurant, Robot Kitchen, opened with a couple of sensor-laden humanoid machines directing customers to their seats. Each possesses a touch-screen on which orders can be keyed in. The robot then returns with the correct dishes. In Japan, University of Tokyo researchers recently unveiled a kitchen 'android7 that could wash dishes, pour tea and make a few limited meals. The ultimate aim is to provide robot home helpers for the sick and the elderly, a key concern in a country like Japan where 22 per cent of the population is 65 or older. Over US$1 billion a year is spent on research into robots that will be able to care for the elderly. 'Robots first learn basic competence-how to move around a house without bumping into things. Then we can think about teaching them how to interact with humans,’ Chrisley said. Machines such as these take researchers into the field of socialized robotics: how to make robots act in a way that does not scare or offend individuals. 'We need to study how robots should approach people, how they should appear. That is going to be a key area for future research,’ adds Chrisley.

Questions 20-23

Look at the following statements (Questions 20-23) and the list of people below. Match each statement with the correct person, A, B or C. Write the correct letter in boxes 20-23 on your answer sheet. NB You may use any letter more than once. A Bill Gates B Nello Cristianini C Ron Chrisley

20 An important concern for scientists is to ensure that robots do not seem frightening.

21 We have stopped trying to enable robots to perceive objects as humans do. 22 It will take considerable time for modern robots to match the ones we have created in films and books.

23 We need to enable robots to move freely before we think about trying to communicate with them. Questions 24-26

Complete the notes below.

Choose NO MORE THAN THREE WORDS from the text for each answer. Write your answers in boxes 24-26 on your answer sheet.

READING PASSAGE 3

You should spend about 20 minutes on Questions 27-40, which are based on Reading Passage 3 below.

It’s your choice! - Or is it really?

As we move from the industrial age to the information age, societal demands on our mental capabilities are no less taxing……

We are constantly required to process a wide range of information to make decisions.

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Sometimes, these decisions are trivial, such as what marmalade to buy. At other times, the stakes are higher, such as deciding which symptoms to report to the doctor. However, the fact that we are accustomed to processing large amounts of information does not mean that are better at it (Chabris & Simons, 2009). Our sensory and cognitive systems have systematic ways of failing of which we are often, perhaps blissfully, unaware.

Imagine that you are taking a walk in your local city park when a tourist approaches you asking for directions. During the conversation, two men carrying a door pass between the two of you. If the person asking for directions had changed places with one of the people carrying the door, would you notice? Research suggests that you might not. Harvard psychologists Simons and Levi (1998) conducted a field study using this exact set-up and found that the change in identity went unnoticed by 7 (46.6%) of the 15 participants. This phenomenon has been termed 'change blindness' and refers to the difficulty that observers have in noticing changes to visual scenes (e.g. the person swap), when the changes are accompanied by some other visual disturbance (e.g. the passing of the door).

Over the past decade, the change blindness phenomenon has been replicated many times. Especially noteworthy is an experiment by Davies and Hine (2007) who studied whether change blindness affects eyewitness identification. Specifically, participants were presented with a video enactment of a burglary. In the video, a man entered a house, walking through the different rooms and putting valuables into a knapsack. However, the identity of the

burglar changed after the first half of the film while the initial burglar was out of sight. Out of the 80 participants, 49 (61%) did not notice the change of the burglar's identity, suggesting that change blindness may have serious implications for criminal proceedings.

To most of us, it seems bizarre that people could miss such obvious changes while they are paying active attention. However, to catch those changes, attention must be targeted to the changing feature. In the study described above, participants were likely not to have been expecting the change to happen, and so their attention may have been focused on the valuables the burglar was stealing, rather than the burglar. Drawing from change blindness research, scientists have come to the conclusion that we perceive the world in much less detail than previously thought (Johansson, Hall, &