The future of work in the age of Artificial Intelligence (AI) is one of the most pressing and significant topics today. The IELTS Reading passage “The Future of Work” (from Cambridge 16, Test 1, Passage 3) does more than just offer predictions; it delves into the debates surrounding how we should prepare for this shift. Let’s break down the passage in detail to decode the questions and equip you with the knowledge needed for your exam!
Reading Passage
The future of work
According to a leading business consultancy, 3-14% of the global workforce will need to switch to a different occupation within the next 10-15 years, and all workers will need to adapt as their occupations evolve alongside increasingly capable machines. Automation – or ’embodied artificial intelligence’ (AI)- is one aspect of the disruptive effects of technology on the labour market. ‘Disembodied AI’, like the algorithms running in our smartphones, is another.
Dr Stella Pachidi from Cambridge Judge Business School believes that some of the most fundamental changes are happening as a result of the ‘algorithmization’ of jobs that are dependent on data rather than on production- the so-called knowledge economy. Algorithms are capable of learning from data to undertake tasks that previously needed human judgement, such as reading legal contracts, analysing medical scans and gathering market intelligence.
‘In many cases, they can outperform humans,’ says Pachidi. ‘Organisations are attracted to using algorithms because they want to make choices based on what they consider is “perfect information”, as well as to reduce costs and enhance productivity.’
‘But these enhancements are not without consequences,’ says Pachidi. ‘If routine cognitive tasks are taken over by AI, how do professions develop their future experts?’ she asks. ‘One way of learning about a job is “legitimate peripheral participation”- a novice stands next to experts and learns by observation. If this isn’t happening, then you need to find new ways to learn.’
Another issue is the extent to which the technology influences or even controls the workforce. For over two years, Pachidi monitored a telecommunications company. ‘The way telecoms salespeople work is through personal and frequent contact with clients, using the benefit of experience to assess a situation and reach a decision. However, the company had started using a[n] … algorithm that defined when account managers should contact certain customers about which kinds of campaigns and what to offer them.’
The algorithm – usually built by external designers- often becomes the keeper of knowledge, she explains. In cases like this, Pachidi believes, a short-sighted view begins to creep into working practices whereby workers learn through the ‘algorithm’s eyes’ and become dependent on its instructions. Alternative explorations- where experimentation and human instinct lead to progress and new ideas- are effectively discouraged.
Pachidi and colleagues even observed people developing strategies to make the algorithm work to their own advantage. ‘We are seeing cases where workers feed the algorithm with false data to reach their targets,’ she reports.
It’s scenarios like these that many researchers are working to avoid. Their objective is to make AI technologies more trustworthy and transparent, so that organisations and individuals understand how AI decisions are made. In the meantime, says Pachidi, ‘We need to make sure we fully understand the dilemmas that this new world raises regarding expertise, occupational boundaries and control.’
Economist Professor Hamish Low believes that the future of work will involve major transitions across the whole life course for everyone: ‘The traditional trajectory of full-time education followed by full-time work followed by a pensioned retirement is a thing of the past,’ says Low. Instead, he envisages a multistage employment life: one where retraining happens across the life course, and where multiple jobs and no job happen by choice at different stages.
On the subject of job losses, Low believes the predictions are founded on a fallacy: ‘It assumes that the number of jobs is fixed. If in 30 years, half of 100 jobs are being carried out by robots, that doesn’t mean we are left with just 50 jobs for humans. The number of jobs will increase: we would expect there to be 150 jobs.’
Dr Ewan McGaughey, at Cambridge’s Centre for Business Research and King’s College London, agrees that ‘apocalyptic’ views about the future of work are misguided. ‘It’s the laws that restrict the supply of capital to the job market, not the advent of new technologies that causes unemployment.’
His recently published research answers the question of whether automation, AI and robotics will mean a ‘jobless future’ by looking at the causes of unemployment. ‘History is clear that change can mean redundancies. But social policies can tackle this through retraining and redeployment.’
He adds: ‘If there is going to be change to jobs as a result of AI and robotics then I’d like to see governments seizing the opportunity to improve policy to enforce good job security. We can “reprogramme” the law to prepare for a fairer future of work and leisure.’ McGaughey’s findings are a call to arms to leaders of organisations, governments and banks to pre-empt the coming changes with bold new policies that guarantee full employment, fair incomes and a thriving economic democracy.
‘The promises of these new technologies are astounding. They deliver humankind the capacity to live in a way that nobody could have once imagined,’ he adds. ‘Just as the industrial revolution brought people past subsistence agriculture, and the corporate revolution enabled mass production, a third revolution has been pronounced. But it will not only be one of technology. The next revolution will be social.’
Questions 27 – 30
Choose the correct letter, A, B, C or D.
Write the correct letter in boxes 27 – 30 on your answer sheet.
- The first paragraph tells us about
- According to the second paragraph, what is Stella Pachidi’s view of the ‘knowledge economy’?
- What did Pachidi observe at the telecommunications company?
- In his recently published research, Ewan McGaughey
Questions 31 – 34
Complete the summary using the list of words, A – G, below.
Write the correct letter, A – G, in boxes 31 – 34 on your answer sheet.
A pressure
B satisfaction
C intuition
D promotion
E reliance
F confidence
G information
The ‘algorithmication’ of jobs
Stella Pachidi of Cambridge Judge Business School has been focusing on the ‘algorithmication’ of jobs which rely not on production but on 31.
While monitoring a telecommunications company, Pachidi observed a growing 32. on the recommendations made by Al, as workers begin to learn through the ‘algorithm’s eyes’. Meanwhile, staff are deterred from experimenting and using their own 33. , and are therefore prevented from achieving innovation.
To avoid the kind of situations which Pachidi observed, researchers are trying to make Al’s decision-making process easier to comprehend, and to increase users 34. with regard to the technology.
Questions 35 – 40
Look at the following statements (Questions 35 – 40) and the list of people below.
Match each statement with the correct person, A, B or C.
Write the correct letter, A, B or C, in boxes 35 – 40 on your answer sheet.
NB You may use any letter more than once.
List of people
A Stella Pachidi
B Hamish Low
C Ewan McGaughey
Summary of “The Future of Work”
This passage presents a multi-dimensional view of the future of work under the influence of AI and automation, through the perspectives of three experts.
- Stella Pachidi focuses on the “algorithmization” of knowledge-based jobs. She warns of negative consequences, such as disrupting the process of expert development, causing employees to become overly dependent on machine instructions, and stifling human creativity and instinct.
- Hamish Low offers a more optimistic view. He argues that the traditional career trajectory (education -> work -> retirement) is obsolete and that people will lead multi-stage working lives involving frequent retraining. He also dismisses fears of mass unemployment, suggesting that technology will create more jobs than it destroys.
- Ewan McGaughey agrees that “apocalyptic” views on job loss are misguided. He argues that unemployment is a result of laws and social policies, not technology. He calls on governments and organizations to proactively update legislation to ensure job security and a fairer future for all.
Key Vocabulary
- disruptive (adj): causing radical change to existing systems.
- algorithmization (n): the process of converting tasks into processes based on algorithms.
- outperform (v): to perform better than someone or something else.
- legitimate peripheral participation (n.p): a concept describing learning by observing experts in a workplace setting.
- short-sighted (adj): lacking foresight; narrow-minded.
- trajectory (n): the path or progression of development.
- fallacy (n): a mistaken belief or unsound argument.
- apocalyptic (adj): predicting or describing catastrophic destruction.
- redeployment (n): the act of moving employees to different tasks or locations.
- pre-empt (v): to take action in advance to prevent something from happening.
Answer Key & Detailed Explanations
- 27. B – the extent to which AI will alter the nature of the work that people do.
Evidence: “…3-14% of the global workforce will need to switch to a different occupation… and all workers will need to adapt as their occupations evolve…”
Explanation: The paragraph doesn’t just discuss changing jobs; it emphasizes that all workers will need to adapt. This indicates a broad shift in the nature of work, not just which specific jobs are affected.
28. D – It is a key factor driving current developments in the workplace.
Evidence: “…some of the most fundamental changes are happening as a result of the ‘algorithmization’ of jobs that are dependent on data… – the so-called knowledge economy.”
Explanation: Pachidi believes that the most “fundamental changes” are occurring due to the algorithmization of jobs in the knowledge economy. This identifies it as a key factor driving current developments.
- 29. C – staff making sure that AI produces the results that they want.
Evidence: “We are seeing cases where workers feed the algorithm with false data to reach their targets.”
Explanation: Employees entering false data to hit targets is an act of manipulating the algorithm to produce desired results.
- 30. D – illustrates how changes in the job market can be successfully handled.
Evidence: “History is clear that change can mean redundancies. But social policies can tackle this through retraining and redeployment.”
Explanation: McGaughey points out that while change can lead to job losses, social policies like “retraining and redeployment” can successfully tackle these issues.
- 31. G – information
Evidence: “…jobs that are dependent on data rather than on production…”
Explanation: “Data” is synonymous with “information” in this context.
- 32. E – reliance
Evidence: “…workers learn through the ‘algorithm’s eyes’ and become dependent on its instructions.”
Explanation: “Become dependent on” is synonymous with “a growing reliance.”
- 33. C – intuition
Evidence: “Alternative explorations- where experimentation and human instinct lead to progress and new ideas- are effectively discouraged.”
Explanation: “Human instinct” is synonymous with “intuition.”
- 34. F – confidence
Evidence: “Their objective is to make AI technologies more trustworthy and transparent…”
Explanation: To make technology more “trustworthy,” the goal is to increase user “confidence” in it.
- 35. B / C
Hamish Low (B): “…that doesn’t mean we are left with just 50 jobs… we would expect there to be 150 jobs.”
Ewan McGaughey (C): “…‘apocalyptic’ views about the future of work are misguided.”
Explanation: Both experts believe that automation will not lead to a net decrease in jobs.
- 36. A – Stella Pachidi
Evidence: “Organisations are attracted to using algorithms because they want to make choices based on… ‘perfect information’, as well as to reduce costs and enhance productivity.”
Explanation: Pachidi lists the reasons why businesses are attracted to AI.
- 37. C – Ewan McGaughey
Evidence: “Just as the industrial revolution brought people past subsistence agriculture, and the corporate revolution enabled mass production, a third revolution has been pronounced.”
Explanation: McGaughey compares the current technological revolution to major historical shifts like the Industrial Revolution.
- 38. A – Stella Pachidi
Evidence: “We need to make sure we fully understand the dilemmas that this new world raises regarding expertise, occupational boundaries and control.”
Explanation: Pachidi emphasizes the need to fully understand the “dilemmas” or problems caused by AI.
- 39. B – Hamish Low
Evidence: “The traditional trajectory of full-time education followed by full-time work followed by a pensioned retirement is a thing of the past.”
Explanation: Low argues that the traditional career path is over, and people will follow a “multistage” path, which is “less conventional.”
- 40. C – Ewan McGaughey
Evidence: “…then I’d like to see governments seizing the opportunity to improve policy to enforce good job security… pre-empt the coming changes with bold new policies that guarantee full employment, fair incomes…”
Explanation: McGaughey calls on authorities to take measures to ensure job security and fair income for everyone.
Conclusion
“The Future of Work” does not provide a single definitive answer; instead, it opens a multi-dimensional dialogue. It shows that the future is not a pre-determined scenario where robots replace humans, but one that depends heavily on our choices regarding policy, law, and how we integrate technology into society. For IELTS learners, this is an excellent passage for practicing the analysis of complex and opposing viewpoints—a core skill for achieving a high band score.
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