IELTS vocabulary: Automation and the Future of Work

Automation and the future of work is now common enough as its own Task 2 prompt — "will automation lead to widespread unemployment," "should governments intervene to protect jobs at risk of automation" — that treating it as a subset of general Work vocabulary leaves an essay under-equipped. General Work vocabulary ("job security," "career," "unemployment") describes the topic broadly but says nothing about the specific mechanism this prompt is actually asking about: why certain jobs, and not others, are vulnerable, and what happens to the people who held them. An essay that only ever says "automation will cause job losses" hasn't yet said anything a reader couldn't have guessed from the prompt itself. This article works through vocabulary for what's actually being automated, the effects on workers, the emergence of new kinds of work, and the policy responses under debate, along with the confusions that undercut otherwise informed answers.

Start with vocabulary for what is actually being automated, since an essay that treats all jobs as equally at risk is making a claim most economists would immediately dispute. "Routine tasks" are predictable, repeatable tasks that follow a consistent set of rules — these are generally considered most vulnerable to automation, whether manual (assembly-line work) or cognitive (basic data entry). "Non-routine tasks" require judgement, creativity, or interpersonal skill that varies case by case, and remain comparatively resistant to automation even as the technology improves — an essay that names this distinction explains why some jobs are at risk and others aren't, rather than treating automation as a uniform threat. "Task-based automation" is a genuinely useful, more precise phrase than "job automation": most current automation replaces specific tasks within a role rather than eliminating the role entirely, which changes what a job involves without necessarily eliminating it. "Algorithmic decision-making" refers to decisions made by software following programmed rules or learned patterns rather than direct human judgement, increasingly relevant to white-collar roles once considered automation-proof.

Vocabulary for the effects on workers moves an essay past the single word "unemployment," which flattens several genuinely distinct outcomes into one. "Job displacement" refers to a worker losing a specific job due to automation, without implying they become permanently unemployed — distinct from "structural unemployment," which describes unemployment caused by a persistent mismatch between workers' skills and available jobs, often lasting considerably longer than the disruption that caused it. "Labour market polarisation" is a precise term for a trend automation is frequently linked to: growth in both high-skill and low-skill jobs, with a shrinking number of middle-skill jobs in between, as routine middle-skill tasks are the ones most readily automated. "Wage stagnation" (wages failing to rise in line with productivity or cost of living) is a related economic effect worth naming separately from job loss itself, since a worker can keep a job while still experiencing this pressure. "Precarious employment" (work lacking stability, benefits, or predictable hours, common in gig-economy roles) is worth knowing as a potential outcome even for workers who find new employment after displacement, since not all replacement jobs offer comparable security.