IELTS Reading Full Test With Answers – Complete Free Practice Online

Paragraph A: The integration of Artificial Intelligence (AI) into global economic structures represents one of the most profound technological shifts of the twenty-first century. While AI-driven systems offer unprecedented gains in efficiency, data processing, and predictive analytics, their deployment has ignited widespread debate concerning the future of the human workforce. The prevailing concern, often termed ‘automation anxiety,’ centres on the potential for intelligent algorithms and robotic systems to render vast swathes of human labour redundant across multiple sectors. This anxiety is rooted in historical shifts, yet the scale and speed of AI adoption suggest a rate of change unparalleled in previous industrial revolutions.

Paragraph B: The impact of automation is not uniformly distributed across the labour market. Studies indicate that tasks characterized by high levels of repetition, predictability, and manual data handling are the most susceptible to immediate displacement. These include roles in manufacturing, logistics, and data entry. For example, assembly line robots have replaced human workers in factory settings since the late 20th century, a trend now accelerating with AI-powered visual inspection systems. Conversely, roles demanding complex interpersonal communication, emotional intelligence (EI), strategic creativity, and non-routine problem-solving—such as nursing, scientific research, and advanced management—show greater resilience. These jobs leverage uniquely human capabilities that are difficult for current AI models to replicate effectively.

Paragraph C: Paradoxically, the advent of AI is simultaneously a formidable job destroyer and a powerful job creator. New categories of employment are emerging rapidly, centred around the development, maintenance, and deployment of these sophisticated systems. These ‘AI-adjacent’ roles encompass fields like machine learning engineering, data architecture, and even emerging specialities such as ‘prompt engineering,’ which requires human expertise to optimize AI outputs. This shift mandates a fundamental transformation in educational and vocational training systems, emphasizing digital literacy and soft skills, rather than merely technical competence, to equip the populace for these future roles.

Paragraph D: Economists observe that this technological transition contributes to a phenomenon known as ‘job polarization.’ This describes a scenario where high-skill, high-wage jobs (which involve complex decision-making) and low-skill, low-wage service jobs (which require human physical presence, e.g., cleaning or caregiving) remain relatively stable or even grow, while the intermediate, middle-income, routine positions decline sharply. The consequence is a widening income disparity, as displaced workers from the middle ground struggle to transition into the highly skilled technical roles without significant reskilling, leading to increased competition for service-sector employment. Addressing the societal fallout of this polarization requires proactive policy interventions related to universal basic income and education reform.