Reading Passage 1

You should spend about 20 minutes on Questions 1-13, which are based on Reading Passage 1 below.

Do animals dream?

Studies using electrodes attached to the heads of sleepers have shown that when we sleep, we do so in two ways that alternate throughout the night. The first is rapid eye movement (REM) or active sleep. During this stage our eyes move, even though our eyelids are closed. Our muscles also twitch slightly, though they are largely paralysed so we don't hurt ourselves. In contrast, we also engage in non-REM sleep, during which we barely move at all. Most dream states, and certainly those with the most vivid dreams, happen during REM sleep.

There's some evidence that other mammals may also dream. For example, researchers compared the brain patterns of rats running through a maze when awake with their brain patterns during REM sleep. They found the patterns were very similar and concluded that the sleeping rats were dreaming about going through the maze.

But finding evidence of dreaming in non-mammals has proved more difficult. Their brains are very different from those of humans, and it can often be difficult to record their activity while they are sleeping. Recently, however, researchers succeeded in recording brain activity in sleeping pigeons. As in mammals, the recordings revealed both REM and non-REM sleep. Intriguingly, REM sleep activity was high in brain regions involved in processing visual information, especially images related to physical activities such as flying, which suggests that this may possibly be what the pigeons were dreaming about.

That said, dreaming and REM sleep are unlikely to be universal in the animal kingdom. For example, sponges don't have brains, so they lack the machinery for dreaming. There are also some animals with unusual sleep patterns. These include whales and dolphins, which do not shut down their entire brain when they sleep, but only half of it, keeping the rest awake. They also show no sign of REM sleep, suggesting that they may only experience non-REM dreams, which are less vivid. This is surprising because we tend to think of whales and dolphins as having complex inner lives. It's thought that they don't experience REM sleep because during REM sleep animals are more vulnerable to extremes of temperature.

Nevertheless, in many cases REM sleep does seem to have benefits. Growing evidence from birds and mammals suggests that REM sleep and dreaming are important for forming memories and learning. It is believed that when events are replayed in dreams, this helps to integrate memories into longer-term storage. As soon as animals evolved moderately complex lifestyles, they would have needed to dream in order to manage these lifestyles.

However, we still don't understand how this outward behaviour relates to internal experience. It seems impossible to know what it is like to be a rat or a pigeon, let alone imagine their dreamscapes. We are quick to interpret the twitching limbs and quiet barks of sleeping dogs, but the truth is that we don't know if there is an internal experience of chasing rabbits that comes along with that.

Another non-human dreamer offers insight here. In 2019, while making a documentary, David Scheel of Alaska Pacific University in the USA housed an octopus named Heidi in a tank in his living room. At one point, in the middle of the night, Heidi seemed to dream: her limbs and head moved, and her skin rapidly changed colour, as though she was pursuing a crab.

Similarly, a report recently emerged of a sleeping octopus apparently having a nightmare. Costello, as the octopus was called, thrashed around, extended his mantle as if trying to make himself look bigger, and squirted ink as though he were being attacked by a predator. The nightmare study is intriguing, says Scheel, but is only based on one animal. He argues that as well as outward behaviour, brain imaging is needed to show that the octopuses are replaying sequences of activities from their waking lives in dreams.

The trouble is that we will never be able to experience any animal's dreams. That goes for other humans' dreams too. But we can try to imagine what these dreamscapes are like by meeting animals on their own terms. For example, vision is the dominant sense for many humans, and so our dreams are heavily visual too. Dogs primarily navigate the world using smell while spiders rely much more on vibrations.

It is likely that dreaming has served multiple purposes since the first complex animals evolved. And if this is the case, it is possible that better understanding of these purposes might shed light on the true purpose of our own dreams.

Reading Passage 2

You should spend about 20 minutes on Questions 14–26, which are based on Reading Passage 2 below.

Why we need silence

A
Humans are finely attuned to noise, and for good reason. From an evolutionary perspective, sounds give us vital information, helping us navigate the world and avoid danger. To help ensure loud or unexpected noises get the attention they deserve, our internal chemistry alters in response to them. Our blood pressure goes up, muscles tense and glands release hormones that prepare us for fight or flight. In the short term, this is a good thing. When we are exposed to too much noise over the long term, however, those responses can lead to a multitude of health issues, from sleep disturbance to even cardiovascular disease.

B
The World Health Organization has recently designated excessive noise as an 'underestimated threat' to public health, and has said that people living in cities such as Mumbai, Tokyo and Buenos Aires are being exposed to far more than the recommended 40 decibels of noise at night. A report from the European Environment Agency concluded that noise was an ongoing and widespread issue in Europe, with at least 1 in 5 people consistently exposed to levels considered harmful to health. 'There are no 'earlids' that can protect your brain from noise,' says Nick Antonio, an acoustic consultant who has contributed to the British and international standards for noise.

C
The good news is that several cities have been working to turn the volume down. One of the first to do so was London. 'By providing recommendations for quieter buses, reducing noise from roads and also controlling noise from aircraft, they were able to make the city quieter,' says Antonio. Other cities have introduced noise-reducing road coatings, for instance, alongside greenery that muffles sound. Some solutions are more specific: Washington DC's ban on petrol-powered leaf blowers came into effect recently, while in New York City, legislation has been approved to fine people who modify their vehicles to make them noisier. 'People are seeing the benefits of these more quiet environments in their cities,' Antonio says. 'I expect we will see much more of this in the future.'

D
Researchers are also seeking to understand what aspects of silent experiences are most beneficial to our health. One of the best-researched is the flotation tank: a lightproof, soundproof tank of salt water in which a person floats as a form of deep relaxation. While some people experience altered perception in the tanks, involving subtle humming sounds and visual effects, these effects are benign and do not detract from the benefits of the experience, says Justin Feinstein, a clinical neuropsychologist. 'When you don't have external sensory stimuli coming in, the brain tries to fill the void to make sense of this dark and silent world,' he explains. 'In these tanks, some people can even hear the sound of their eyes blinking,' says Feinstein. 'But it is the ability to focus on the breath that helps people reach a relaxed or meditative state.'

E
To further explore flotation tanks as a therapeutic tool, Feinstein and his colleagues recruited 50 people with a variety of conditions related to stress and had them answer a questionnaire prior to and following a flotation session. Participants reported decreases in muscle tension, pain and symptoms of their conditions after a single, 1-hour float, alongside an increase in feelings of relaxation and overall wellbeing.

Less is known about what effects sensory deprivation can have on the brain. To investigate, Feinstein's team had 48 people participate in either three 90-minute float sessions or three 90-minute periods of relaxing on a chair which reclined. Participants had their brains scanned using functional magnetic resonance imaging at the beginning and end of the trial. Float sessions uniquely decreased activity in the default mode network (DMN), a collection of brain regions commonly linked with depression. Feinstein says it is an exciting finding, because flotation tanks seem to offer a way of 'resetting' our nervous system to prevent it from getting out of balance.

F
Neurobiologist Tai Dotan Ben-Soussan is also an advocate of silence as a therapy. 'When we find ways to be quiet, we are not only quiet in our environment, but quiet in our inner selves,' she explains. 'This allows us to be more aware of what is happening around us and what the situation may require from us so we can provide [a more] adequate response.'

Not everyone will benefit from silence to the same extent, but Ben-Soussan says one characteristic is key: the person must need to want to engage in the experience. 'We see from animal models and human studies that volition and intentionality is important,' she says. 'When people do not want silence, it can be very distressing.'

G
Eric Pfeifer, a psychotherapy researcher, also concedes that some people may not benefit from silence, particularly those who are in a heightened state of stress. 'People in these states may not be able to relax or calm down in a silent condition,' he says. Professional guidance can be useful, he adds, allowing people to approach silence slowly so that they can gradually enjoy the benefits. And Pfeifer is convinced that silence is more attainable in everyday life than people think. First, complete silence isn't necessary. In a recent study, he found that participants reported more relaxation and less boredom when they sat quietly in an outdoor garden compared with a completely silent room. Second, Pfeifer believes we don't need a lot of silence to gain benefits. 'You don't need to spend hours in silence,' he says. 'It is likely better to have more frequency of silence for a few minutes at a time than a longer period of silence only once a week. Just finding those places in your daily life where you can find some silence ... can make a big difference.'

Reading Passage 3

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

Artificial Intelligence

In many countries in the West, hysteria about the future of artificial intelligence (AI) is everywhere. There seems to be no shortage of sensationalist news about how AI could cure diseases, accelerate human innovation and improve human creativity. Just looking at the media headlines, you might think that we are already living in a future where AI has infiltrated every aspect of society.

While it is undeniable that AI has opened up a wealth of promising opportunities, it has also led to the emergence of a mindset that can be best described as 'AI solutionism'. This is the philosophy that, given enough data, machine learning algorithms can solve all of humanity's problems. But, in fact, instead of supporting AI progress, this mindset actually jeopardises the value of machine intelligence by disregarding important AI safety principles and setting unrealistic expectations about what AI can really do for humanity.

In only a few years, AI solutionism has made its way from the technology evangelists' mouths in Silicon Valley in California to the minds of government officials and policymakers around the world. The pendulum has swung from the dystopian notion that AI will destroy humanity to the utopian belief that our algorithmic saviour is here.

We are now seeing governments pledge support to national AI initiatives and compete in a technological race to dominate the burgeoning machine-learning sector. While many politicians proclaim the transformative effects of the coming 'AI revolution', they fail to realise the complexity around deploying advanced machine learning systems in the real world.

One of the most promising varieties of AI technologies are neural networks. This form of machine learning is loosely modelled on the neuronal structure of the human brain, but on a much smaller scale. But what many politicians do not understand is that simply adding a neural network to a problem will not automatically mean that you'll find a solution. Similarly, adding a neural network to a system of government does not mean it will be instantaneously more inclusive or fair.

AI systems need a lot of data to function, but the public sector typically does not have the appropriate data infrastructure to support advanced machine learning. Most of the data remains stored in offline archives. The few digitised sources of data that exist tend to be buried in bureaucracy. More often than not, data is spread across different government departments that each require special permissions to be accessed. Above all, the public sector typically lacks the human talent with the right technological capabilities to fully reap the benefits of machine intelligence.

For these reasons, the sensationalism over AI has attracted many critics. Stuart Russell, a professor of computer science at the University of California, Berkeley, has long advocated a more sensible and realistic approach that focuses on simple everyday applications of AI instead of the hypothetical takeover by super-intelligent robots. Similarly, Rodney Brooks, professor of robotics at Massachusetts Institute of Technology, writes that 'almost all innovations in robotics and AI take far, far, longer to be really widely deployed than people in the field and outside the field imagine'.

One of the many difficulties in deploying machine learning systems is that AI is extremely susceptible to adversarial attacks. This means that a malicious AI can target another AI to make it behave in a certain way, such as forcing it to make wrong predictions. Many researchers have warned against the rolling out of AI without appropriate security standards and defence mechanisms. Still, AI security remains an often overlooked topic when machine learning systems are installed.

If we are to reap the benefits and minimise the potential harms of AI, we must start thinking about how machine learning can be meaningfully applied to specific areas of government, business and society. This means we need to have a discussion about AI ethics and the distrust that many people have towards machine learning.

Most importantly, we need to be aware of the limitations of AI and where people still need to take the lead. Instead of painting an unrealistic picture of the power of AI, it is important to take a step back and separate the actual technological capabilities of AI from fantasy.

The medical profession has also recognised the drawbacks to AI. The IBM Watson for Oncology programme was a piece of AI that was meant to help doctors treat cancer. Even though it was developed to deliver the best recommendations, human experts found it hard to trust the machine. As a result, the AI programme was abandoned in most hospitals where it was trialled.

Similar difficulties arose in the legal domain when algorithms were used in courts in the US to sentence criminals. An algorithm calculated risk assessment scores and advised judges on the sentencing. The system was found to amplify structural racial discrimination and was later abandoned.

There are some crucial lessons here for everyone aiming to boost investments in national AI programmes. These examples demonstrate that there is no AI solution for everything. Using AI simply for the sake of AI may not always be productive or useful, and not every issue is best addressed by applying machine intelligence to it. All solutions come with a cost and not everything that can be automated should be.