Breaking down the question
The instruction word is "critically assess", which demands a balanced weighing of positive and negative consequences rather than a one-sided account. The question pairs two related drivers — technological advancement and automation — and asks about their effect on two things: the nature of work and the level of employment.
"Nature of work" points toward qualitative change: skills, control, the labour process, and the experience of working. "Employment" points toward the quantitative question of jobs created and destroyed. A strong 10-mark answer keeps both dimensions in view rather than collapsing into a single worry about job loss.
The examiner expects theoretical anchoring — Braverman on deskilling, Marx on alienation — together with contemporary awareness of artificial intelligence and robotics.
How to approach it
Given the 10-mark limit, be economical. Open with a one-line framing that technology reshapes both the content and the quantity of work. Then move quickly into an evaluative structure that sets gains against costs.
On the nature of work, contrast the deskilling thesis with reskilling and the rise of knowledge work. On employment, contrast technological unemployment and displacement with the creation of new roles and sectors. Illustrate briefly with automation in manufacturing and the growth of the platform and IT economy. Our labour and society notes expand on these debates.
Close with a measured judgement stressing that outcomes depend on how technological change is socially and politically managed.
Model answer
Technological advancement and automation are among the most powerful forces reshaping contemporary work, altering not only how many people are employed but the very character of what they do. A critical assessment must therefore weigh clear benefits against equally clear costs, avoiding both technophobia and technological determinism.
Considering the nature of work first, automation transforms the labour process in contradictory ways. Harry Braverman's deskilling thesis argues that mechanisation and now digital systems strip skill and discretion from workers, fragmenting tasks and concentrating control in management and machines. The assembly line and, more recently, algorithmic monitoring in warehouses and delivery work illustrate this loss of autonomy, which deepens the alienation that Marx identified — the separation of the worker from the product, the process and their own creativity. Yet the opposite tendency also operates. Automation eliminates dangerous, repetitive and physically punishing tasks, and it generates demand for higher-order skills in design, data analysis, maintenance and coordination. The growth of knowledge work and the information technology sector shows that technology can upgrade as well as degrade, producing a polarised labour force in which some jobs are enriched while others are hollowed out.
On employment, the debate turns on technological unemployment. Automation and artificial intelligence displace labour in manufacturing, clerical work, banking and increasingly in services, raising fears of jobless growth as machines substitute for human effort. Routine, predictable roles are most exposed. Against this, the compensation argument holds that technology historically creates new occupations, sectors and forms of demand that offset the jobs it destroys — the digital economy, platform work and entire industries unknown a generation ago. The net effect is uncertain and uneven: it varies by country, skill level and the pace of change, and the transition itself imposes real hardship on displaced workers even if aggregate employment eventually recovers.
Critically, the outcomes of automation are not dictated by technology alone but by the social and political framework within which it is deployed — patterns of ownership, the strength of labour, education and reskilling policy, and the design of social protection. The same robot can be used to intensify work and shed labour, or to reduce drudgery and shorten hours. In conclusion, technological advancement carries genuine emancipatory potential alongside serious risks of deskilling, alienation and displacement. Whether it liberates or immiserates depends less on the machines and more on how their benefits and burdens are distributed across society.
Examiner's perspective
At 10 marks the examiner rewards focus and balance over breadth. The commonest error is a purely pessimistic answer that treats automation only as a cause of unemployment, ignoring the qualitative change in the nature of work and the countervailing creation of new roles.
A strong script separates the two dimensions the question names — nature of work and employment — invokes Braverman and Marx concisely, and ends with the critical point that outcomes are socially shaped rather than technologically determined. Precision and a genuinely two-sided assessment, delivered within the word limit, mark out the better answers.