ACADEMIC WRITING SAMPLE ANSWERS

Academic Writing Sample Answers Practice 6 Test 03

This original practice page includes Task 1 (Timeline Diagram) and Task 2 (Discuss Both Views and Give Your Opinion), with Band 9, Band 8, and Band 7 sample answers for IELTS preparation.
Academic Writing Task 1

Task 1 · Timeline Diagram

Task 1 Prompt

You should spend about 20 minutes on this task. Write at least 150 words.

The diagram below illustrates the evolution of public transport payment systems in a major city from 1980 to the present day, showing the key technologies introduced in each phase.

Summarise the information by selecting and reporting the main features, and make comparisons where relevant.

Academic Writing Task 1 Timeline Diagram practice image
BAND 9

Part 1 · Band 9 Sample Answer

The diagram traces five stages in the development of payment systems for public transport in a major city, from mechanically processed tickets in 1980 to the seamless biometric arrangements used today.

Overall, the system has progressed from cash-dependent, manually checked physical tickets to increasingly automated and less tangible payment methods. At the point of entry, manual inspection was followed by swiping, tapping and mobile scanning, before the introduction of facial identification linked to automatic payment.

In 1980, during the mechanical era, passengers used paper tickets or tokens. These could be obtained only with cash and had to be checked manually. The first electronic alternative appeared in 1995, when rechargeable magnetic-stripe cards were introduced. Rather than presenting a ticket to an employee, travellers swiped a card to enter the network, although contact with a reader was still required.

The contactless era began in 2005 with smart cards incorporating tap-and-go technology. This removed the need to swipe a magnetic strip. A further transition occurred in 2015, when payment moved onto mobile devices. QR codes and transport applications enabled app-based ticketing, so a separate travel card was no longer the only electronic option.

At present, the city has entered what the diagram calls the seamless era. The latest arrangement is both biometric and account-based: Face ID identifies the passenger, while the associated account handles payment automatically. Compared with the entirely manual process of 1980, the current system combines identification, entry and payment with minimal direct action from the traveller.

BAND 8

Part 1 · Band 8 Sample Answer

The diagram shows how payment for public transport in a major city has developed through five technological phases between 1980 and the present.

Overall, payment has changed from a manual system based on cash, paper tickets and tokens to an automated system using biometric identification and linked accounts. Passengers moved from showing a ticket to swiping or tapping a card, then using mobile technology, and finally making payments automatically through Face ID.

In 1980, the city was in the mechanical era. Travellers paid only in cash and received either paper tickets or tokens, which staff checked manually. The electronic era followed in 1995. Magnetic-stripe cards could be recharged and were swiped at the entrance, allowing the same card to be used repeatedly.

A decade later, in 2005, contactless smart cards were introduced. These used tap-and-go technology, eliminating the need to pass a magnetic strip through a reader. The digital era then began in 2015, when mobile QR codes and applications allowed tickets to be stored and used on a phone through an app-based system.

The most recent stage is described as the seamless era. Payment is now account-based and uses biometric technology. Instead of handling cash, presenting a ticket or scanning a card or QR code, a passenger can be recognised through Face ID and charged automatically. Thus, the main trend has been towards less reliance on physical payment items and progressively lower manual involvement.

BAND 7

Part 1 · Band 7 Sample Answer

The diagram illustrates the development of public transport payment in a large city from 1980 to the present. It divides this development into five eras, each based on a different type of technology.

Overall, the payment system became more digital and automatic over time. It started with cash payments and manually checked paper tickets or tokens. These were followed by different types of cards, mobile tickets and, finally, biometric identification with automatic payment.

In 1980, the city used a mechanical system. Passengers could pay only with cash and received paper tickets or tokens. These items had to be checked manually. In 1995, magnetic-stripe cards were introduced as part of the electronic era. The cards were rechargeable, and passengers swiped them to enter the transport system.

The next stage began in 2005. Contactless smart cards replaced the need to swipe, as travellers could use tap-and-go technology. In 2015, the system entered the digital era. Mobile QR codes and apps allowed passengers to use app-based tickets on their phones instead of relying only on travel cards.

At present, the system is in the seamless era. It uses biometric and account-based technology. Face ID can recognise a passenger, and the fare is paid automatically through the connected account. Compared with 1980, the modern process requires much less action from both passengers and transport workers, and cash and manual checking are no longer central to the payment procedure.

Academic Writing Task 2

Task 2 · Discuss Both Views and Give Your Opinion

Task 2 Prompt

You should spend about 40 minutes on this task. Write at least 250 words.

Write about the following topic:

Governments and companies are increasingly using artificial intelligence to analyse people’s online activity and information collected in public places. Some people believe that this can help identify social, economic and public health problems at an early stage and improve public safety. Others argue that such monitoring threatens personal privacy and may lead to unfair decisions because artificial intelligence systems can be biased.

Discuss both these views and give your own opinion.

Give reasons for your answer and include any relevant examples from your own knowledge or experience.

BAND 9

Part 2 · Band 9 Sample Answer

Artificial intelligence allows authorities and companies to find patterns in online behaviour, camera footage and other data from public spaces. Supporters see an early-warning system; critics see surveillance and automated discrimination. I believe narrowly limited analysis can serve public interests, but identifiable individuals should not be monitored continuously. Any use must be necessary, proportionate and independently supervised.

The benefits can be substantial because AI can process signals too numerous for human teams to examine promptly. Aggregated search trends or public posts may reveal emerging unemployment, shortages or disease symptoms before conventional reports are available. Transport authorities can analyse crowd movements to identify dangerous congestion, while cameras may help locate a missing person or detect an abandoned object. Used as an alert rather than a final decision-maker, such systems can direct professionals towards problems requiring investigation and allow resources to be deployed earlier.

Nevertheless, this capacity creates serious privacy risks. People may reasonably expect to walk through a park, research a medical concern or express an unpopular opinion without these actions being assembled into a permanent profile. Even public information becomes intrusive when facial recognition links movements across time and place. Data may later be used for purposes never explained when they were obtained, or exposed through poor security. Awareness of constant observation can also discourage lawful speech and association.

Bias creates a further danger. AI learns from historical data, which may contain unequal policing, lending or hiring patterns. A system trained on such records can reproduce those patterns while presenting its output as neutral. Errors are especially damaging when an algorithm influences access to employment, insurance or public services. Individuals may not know why they were flagged and may struggle to challenge an opaque decision.

I therefore support only targeted applications with clear legal boundaries. Authorities should demonstrate necessity, minimise collection, delete information after defined periods and obtain independent approval for sensitive uses such as facial recognition. Models must be tested across relevant groups, and consequential decisions should remain reviewable by accountable humans. Wherever possible, public-health or economic analysis should use anonymous, aggregated data. Companies should face comparable duties and meaningful penalties for misuse.

In conclusion, AI monitoring can provide valuable early warnings and improve safety, but these benefits do not justify unrestricted surveillance. It should be permitted only where its public value is specific and where privacy, fairness and the right to appeal are built into the system.

BAND 8

Part 2 · Band 8 Sample Answer

Governments and businesses can use artificial intelligence to examine enormous amounts of information about online behaviour and activity in public areas. Supporters believe this allows problems and safety threats to be detected sooner, whereas opponents fear a loss of privacy and biased treatment. I believe monitoring can be beneficial, but only when it serves clear purposes and important decisions are reviewed by people.

One major advantage is speed. Public-health agencies could identify an unusual rise in searches or public messages about similar symptoms and investigate a possible outbreak earlier. Local authorities can study traffic and crowd patterns to find unsafe locations, while security systems may notice abandoned objects in stations. Economic information can also reveal sudden changes in demand or employment. AI does not need to prove that a problem exists; a reliable warning can help officials decide where human investigation and resources are needed.

However, connecting personal information can seriously reduce privacy. A single camera may appear harmless, but a facial-recognition network could follow someone across a city and create a detailed record of daily life. Online data can reveal health concerns, political interests and relationships that people never intended to share with employers or government departments. Information gathered for safety might also be used later for advertising, immigration enforcement or unrelated purposes.

The risk of unfair decisions is equally important. Algorithms learn from existing records, which may reflect previous discrimination or unequal attention from authorities. Consequently, some communities could be incorrectly identified as more dangerous. If an automated score affects a job application, loan or access to a service, the person concerned should be able to understand and challenge it. Human supervision is therefore essential, although reviewers must genuinely question the system rather than approve its recommendations automatically.

In my opinion, anonymous analysis of broad trends should generally be allowed because it can provide social value without identifying particular people. More intrusive uses should require strong justification, independent oversight and strict storage limits. Systems should be tested regularly for unequal error rates, and AI should provide evidence for human consideration rather than make final high-impact decisions.

In conclusion, intelligent monitoring can improve early detection and public safety, but it also creates genuine threats to privacy and equality. Its use is acceptable only within transparent rules that limit collection, prevent secondary use and give individuals an effective right to appeal.

BAND 7

Part 2 · Band 7 Sample Answer

Artificial intelligence is increasingly used to study online activity and information collected in public places. Some people think this can help organisations recognise problems early and protect the public, while others worry about privacy and unfair decisions. In my opinion, the technology is useful, but it should be used only for specific purposes and under human control.

AI can examine large amounts of information and find patterns quickly. For example, a sudden increase in online discussions about similar symptoms may warn health authorities about a possible disease outbreak. Cameras and sensors can also show where crowds are becoming dangerously large or where traffic accidents often occur. Officials could then investigate before the situation becomes more serious. Changes in purchases or job advertisements might also provide an early sign that an industry is experiencing difficulties.

On the other hand, people may lose control of their personal information. Someone may accept being recorded by one camera for security but not expect facial recognition to follow them across many locations. Online searches and posts can reveal private matters such as health, relationships and political opinions. If information is stored for a long time or shared with other organisations, it could be used in ways the individual never accepted.

AI systems can also be biased because they learn from past information, which may include unfair decisions. If earlier records focus more heavily on one neighbourhood, an AI system may continue to treat that area as a greater risk. Similar problems could affect recruitment, lending or insurance. A person rejected because of an automated recommendation may not understand the reason or know how to correct inaccurate data.

I believe monitoring should be permitted only when there is a clear public need. Organisations should collect as little personal data as possible, keep it for a limited period and explain its purpose. Independent experts should test systems for bias, and a person should review any decision that seriously affects someone. Anonymous information should be used whenever identities are unnecessary.

In conclusion, AI analysis can help detect problems and improve safety, but unrestricted monitoring would threaten privacy and could produce unfair results. Clear laws, regular checks and human review are required to keep its risks under control.

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