IELTS Academic Reading Practice Test 120

The first version of the device, built by Douglas Engelbart's team in 1964, was an awkward object: a block of wood the size of a cigarette packet, with one red button on top and two metal wheels protruding from the underside. A thick cable trailed from the back, and someone in the laboratory had already nicknamed it the mouse because the cable put them in mind of a tail. Engelbart was an engineer at the Stanford Research Institute in California, and for much of that decade he had led a group whose aim was to make computers useful to the human mind.

On 9 December 1968, before about a thousand computer specialists in San Francisco, Engelbart sat on stage in front of a large screen and put the device through its paces. He opened files, moved text, followed a link from one document to another and worked at the same time with a colleague many miles away, whose face and voice reached the hall by video link. By then the mouse had three buttons, and it was only one part of a demonstration later known as the Mother of All Demos, but it was the part visitors most wanted to try.

In the 1960s a computer was fed with punched cards or with typed commands, and its operator sat at a console rather than a screen. Engelbart's group, however, had built a display on which text and diagrams could be shown, and they needed a way of moving a mark around it quickly. They had tried a light pen, which had to be held against the glass, and a joystick, whose movements felt clumsy for fine work. The mouse combined precision with simplicity: its two wheels sat at right angles, one rolling when the device moved sideways and one when it moved forwards or backwards.

The arrangement was clever enough to be worth protecting. Engelbart filed a patent in 1967, and it was granted in 1970 under the title 'X-Y Position Indicator for a Display System'. The document describes the wheels, the button and the trailing cable with the care usually given to a far more complicated machine. The rights, however, belonged to the research institute that employed him rather than to the inventor, and the mouse earned Engelbart far less money than its later fame might suggest.

The person who did most to carry the idea forward was Bill English, the engineer who had built the first working model. He moved to Xerox's research centre in Palo Alto, California, in 1971, and the mouse reappeared there on the Alto, a small computer for individual use completed in 1973. English replaced the wheels with a single ball on the underside, which could roll in any direction and drove two internal rollers, and he gave the device three buttons. The Alto was never sold commercially; a few thousand were made for Xerox's own laboratories and a handful of universities.

The wider world caught up slowly. In December 1979 a group from Apple Computer visited the Palo Alto laboratories and saw the Alto in action; the visit has become one of the most argued-about episodes in the history of computing. What is clear is that Apple's Lisa, launched in 1983, was the first Apple machine sold with a mouse, and that the far cheaper Macintosh, which appeared in January 1984, made the device familiar to people who had never used a computer. The Macintosh mouse had a single button. Microsoft released its first mouse in 1983 as well.

For all its success, the mechanical mouse was a frail piece of equipment. The ball collected dust and fibres from the desk, which were transferred to the rollers inside; as the coating thickened, the cursor began to jump and stall, and the remedy was to open the casing and scrape the rollers clean. The ball also had to be pressed against a surface, so the mouse needed a mat on polished desks.

The first optical mice appeared in the 1980s, but they depended on a special mat printed with a fine grid of lines that the sensor could read. They were accurate and never clogged, yet the need for a proprietary pad kept them rare. The breakthrough came in 1999, when Agilent Technologies, a company spun out of Hewlett-Packard, produced a sensor that could track movement across an ordinary surface. An optical mouse shines light onto the desk, photographs the illuminated patch with a tiny camera thousands of times a second and calculates movement by comparing one image with the next.

Meanwhile the design of the mouse was changing in other ways. In 1996 Microsoft introduced a mouse with a small wheel between the buttons, which allowed users to scroll through long documents without moving the pointer to the edge of the screen; within a few years almost every manufacturer had copied the idea. Cables disappeared too. Early cordless versions communicated by infrared and needed a clear line of sight, but radio links and later Bluetooth made them dependable.

The mouse has been manufactured in enormous numbers and remains part of the standard office desk, but it is losing ground on portable machines to the touchpad built into the keyboard, and on phones to the fingertip. Engelbart died in 2013, having spent much of his later career insisting that his real subject had never been the mouse but the way people think and work together; his interests lay less in the device itself than in what it might allow a group to do.

For most of the twentieth century the electricity supply was designed as a one-way system. Large power stations, most of them burning coal or gas, fed current into a transmission network which carried it at high voltage to towns and factories, where it was stepped down and distributed to individual buildings. Nothing in this arrangement measured what happened at the far end of the wires: meters in homes simply accumulated a total that a reader visited once a quarter. The system worked because demand was predictable, rising gently during the day and falling at night, and because the output of the generators could be adjusted to match it.

Several changes have made that model harder to sustain. Wind and solar farms produce electricity only when the weather allows, so the supply side of the equation now varies as well as the demand side. Electric cars and heat pumps, both promoted as ways of cutting carbon emissions, add large new loads to networks built for smaller ones. Ageing cables and transformers need replacing, and extreme weather, from storms to heatwaves, puts equipment under strain. Nor can electricity yet be stored in large quantities at reasonable cost, so supply and demand must be matched instantaneously, second by second. The smart grid is the name given to a set of technologies intended to help networks cope with these conditions.

A smart grid is not a single machine but an approach: instruments and communications are added throughout the network so that it can be observed and controlled in near real time. The most visible parts are smart meters, which record consumption every half hour and send the readings back to the supplier automatically, and remote switches that allow a control room to isolate a faulty section of cable without sending an engineer. Because the operator can see what is happening as it happens, faults can be found and repaired more quickly, and supply can be restored to unaffected streets.

The most important measurement in any grid is frequency, the rate at which alternating current changes direction: 50 cycles a second in most of the world, 60 in North America. Frequency indicates whether supply and demand are in balance. If a power station fails, or demand rises unexpectedly, the generators slow down and frequency falls; if generation exceeds demand, it rises. Conventional power stations resist such changes because of the inertia of their heavy rotating machinery. Solar and wind farms feed the network through electronic inverters, which have no moving parts and, in their earliest form, provided no inertia at all.

Smart grids also make it possible to alter demand rather than supply. In a demand-response scheme, customers are rewarded for using less electricity at busy times. Some large industrial users are paid to shut down furnaces or pumps for an hour when the network is under strain. Households may be offered tariffs that are cheap at night and expensive in the early evening, and a control centre can switch off water heaters and air conditioners for a few minutes at a time, too briefly for anyone to notice.

Another change is that electricity now flows in both directions. A rooftop solar system sends power into the local network when it produces more than the household needs, and a battery can store the surplus and release it later. Groups of buildings with their own generators, batteries and control equipment can form a microgrid, a small network that is normally connected to the main grid but can disconnect and keep running on its own during a blackout. Hospitals and universities have built such systems for decades; cheaper electronics are now bringing them to ordinary streets.

The obstacles are less technical than institutional. Installing sensors, meters and communications equipment is expensive, and the benefits arrive slowly. Competing technical standards mean that devices from different manufacturers cannot always exchange information, so a utility that buys meters from one supplier may find they will not talk to the software of another. Meter data is also personal: a detailed record of electricity use reveals when a house is empty, how many people live there and when they sleep, which is why data-protection regulators have taken a close interest.

Security is the least visible concern. The computers that run power stations and substations were once kept deliberately isolated from the public internet, but remote monitoring requires connections, and every connection is a possible way in. Researchers have demonstrated attacks on the electronic controls of generating equipment, and the consequences of a successful attack on a national network would be severe. Because equipment may remain in service for forty years, security must be designed into devices that will still be running long after the software that protects them has been replaced.

Research is concentrated on the weak points. Forecasting is one: machine-learning systems trained on weather data and past consumption can predict the output of wind and solar farms, and the demand on the network, a day ahead. Another is the inverter. Engineers are developing grid-forming inverters, which imitate the steadying behaviour of a spinning generator by adjusting their output many times a second, so that a network dominated by renewable sources can remain stable. Electricity stored in the batteries of parked cars could also be drawn on at times of shortage, an idea known as vehicle-to-grid.

Since 2020 millions of people who once worked in offices have done their jobs from kitchens and spare bedrooms, and a whole industry has grown up to watch them. Monitoring software can photograph a laptop screen at random intervals, count keystrokes, record which applications are open and how long the mouse has been still. Some programs take a picture through the webcam every few minutes. Others rank employees by the proportion of the day they are judged to be active, and field staff can be tracked by the location signals of the phone in their pocket. Employers buy these tools because they want to know that they are getting what they pay for.

The case for them is not frivolous. An employer that cannot see its staff has a legitimate interest in knowing whether the work is being done, and in some industries the law requires records of what employees say and write. Regulated financial firms must keep copies of communications, and a hospital or a delivery company has duties to protect patients and drivers that may justify knowing where its people are. Managers also point out that monitoring can protect employees: evidence of excessive hours is useful to anyone trying to show that a workload is unreasonable. Used narrowly and openly, surveillance can answer questions that would otherwise be settled by guesswork.

The suppliers go further. Their marketing emphasises fairness, arguing that a record of hours worked protects diligent employees from managers who reward only those they happen to notice. Time-tracking, in this account, is a service to the worker, and some staff who struggle to organise a day at home say that it helps. How many feel that way is unclear, since much of the published evidence comes from companies with an interest in the answer.

Beyond that narrow ground, however, the argument weakens quickly. Office work does not consist of keystrokes, and a person who produces three good paragraphs in a morning may be more valuable than one who sends a hundred messages. Monitoring systems cannot see the difference, because they are built to count what a computer can register rather than what a business actually needs. A warning attributed to the economist Charles Goodhart holds that when a measure becomes a target, it ceases to be a good measure, and there are few better illustrations than an employee whose activity score improves because the mouse is being moved while they think.

The result is what might be called productivity theatre: people performing activity because activity is what is measured. Employees under surveillance report moving the mouse at intervals while they read, keeping a second window open, or buying a small device that jiggles the cursor. Others answer messages at midnight to prove that they are available. A growing body of survey evidence links intensive monitoring with anxiety, with a sense of being distrusted and, in some studies, with a greater intention to leave.

European data-protection law sets limits. An employer must have a lawful basis for processing information about a member of staff, must tell people what is being collected, and must show that the intrusion goes no further than necessary for a stated purpose. Permanent screenshotting of a call-centre worker's screen is unlikely to pass that test; checking the security logs of a payment system probably would. The principle is proportionality, and it is easier to state than to apply.

The deeper problem is one of trust. Remote work rests on an agreement that people will manage their own time in return for being judged on results. Surveillance reverses that agreement: it assumes that the appearance of work is the best available evidence of it, and it invites employees to produce the appearance. A manager who installs monitoring software has usually given up on the conversation that would have established whether the work was being done well, and that conversation costs nothing.

Monitoring is not always resented. In call centres it has been routine for decades, and staff often accept it when the recordings are used for training and when everyone knows the rules. What distinguishes acceptable from unacceptable practice is not the technology but its purpose and its transparency. Software that warns a delivery driver they are speeding, or shows a manager that a team member has not taken a break, is helping. The same software becomes something else when it is used to build a case for dismissal.

Defenders of the industry reply that they merely supply what customers ask for, and that a responsible employer will use the data carefully. That is true as far as it goes, but it places the entire burden of judgement on the buyer. Software is not neutral: a dashboard that ranks staff by activity makes activity the thing that managers discuss, and a feature that appears on a menu will eventually be switched on. Design shapes behaviour quite as much as intention does.

My own view is that the burden of proof should lie with those who want to watch. Monitoring that is disclosed, time-limited, aimed at a specific risk and used to help rather than to punish seems to me defensible; blanket surveillance of remote staff does not. The best remote teams are those whose managers discuss the work itself, and who measure the result rather than the movement of a mouse. Employers who cannot manage without watching should ask whether the fault lies with their staff or with their management.