IELTS Academic · Reading Skills
Five levels of difficulty. Read each passage carefully, then decide whether each statement is supported, contradicted, or simply not addressed in the text.
Passage A
The global average temperature has risen by approximately 1.1°C above pre-industrial levels, primarily as a result of human activities such as burning fossil fuels and deforestation.
Questions
1. Human activity is largely responsible for the rise in global average temperature.
2. Governments worldwide have introduced policies to reverse the temperature increase.
Passage B
Although caffeine can temporarily enhance alertness and concentration, excessive consumption has been linked to increased anxiety, disrupted sleep patterns, and elevated heart rate.
3. Caffeine has no effect on a person's ability to focus.
4. Drinking too much caffeine may interfere with sleep.
Passage
Remote work, once considered a privilege reserved for a small professional elite, expanded dramatically during the COVID-19 pandemic. Studies conducted in 2021 suggested that productivity among remote workers either remained stable or improved in many sectors, challenging the assumption that office presence is inherently necessary for performance. However, the same studies noted that employees in junior or entry-level positions often struggled more than their senior counterparts, as they had fewer opportunities for mentorship and informal learning. Companies that provided structured virtual onboarding programmes reported significantly better retention rates among new hires.
Questions
1. Remote work was widely practised across all professional levels before the pandemic.
2. Research indicated that working from home did not necessarily reduce output.
3. Senior employees preferred working from home to working in the office.
4. Entry-level employees found remote work more challenging partly because they had less access to guidance from experienced colleagues.
5. Organised virtual onboarding was associated with keeping new staff for longer.
Passage
The concept of neuroplasticity — the brain's ability to reorganise itself by forming new neural connections throughout life — has fundamentally reshaped our understanding of cognitive development and rehabilitation. Contrary to earlier scientific consensus, which held that the brain's architecture was essentially fixed after early childhood, contemporary neuroscience has demonstrated that significant structural change can occur well into adulthood and even old age, particularly in response to sustained learning and environmental stimulation. This malleability, however, is not uniform: regions associated with language acquisition appear most receptive during a so-called critical period in early childhood, whereas areas governing executive function remain comparatively plastic throughout the lifespan. Importantly, neuroplasticity also has a darker implication — the same mechanisms that enable adaptation and recovery can also encode maladaptive patterns, reinforcing behaviours associated with addiction or anxiety disorders if sufficiently repeated.
Questions
1. Earlier scientific views maintained that the brain could continue to form new connections throughout a person's entire life.
2. Structural brain changes in adulthood can be triggered by continuous exposure to learning experiences.
3. Not all areas of the brain demonstrate the same degree of plasticity across different life stages.
4. Pharmaceutical interventions have been developed to enhance neuroplasticity in stroke patients.
5. Neuroplasticity can contribute to harmful psychological patterns if certain behaviours are repeated frequently enough.
6. Executive function is known to decline more rapidly in old age than language-related abilities.
Passage
The debate surrounding universal basic income (UBI) — a policy in which all citizens receive a regular, unconditional cash payment from the government — has gained renewed momentum in the context of growing automation and economic inequality. Proponents argue that UBI would provide a financial floor that eliminates extreme poverty, reduces the stigma associated with means-tested welfare, and affords individuals the freedom to pursue education, entrepreneurship, or caregiving roles without the anxiety of immediate financial insecurity. A frequently cited pilot programme conducted in Finland between 2017 and 2018, in which two thousand unemployed individuals received monthly payments, found modest but statistically significant improvements in subjective wellbeing, without a measurable reduction in employment-seeking behaviour.
Critics of UBI, however, raise several substantive objections. Fiscal conservatives contend that the cost of providing meaningful payments to an entire population would either necessitate substantial tax increases or require the dismantling of existing targeted welfare programmes that, despite their inefficiencies, often provide more support to the most vulnerable than a flat-rate payment would. Others argue that UBI does not adequately address structural barriers to employment such as discrimination, lack of childcare, or geographic isolation from labour markets. A minority of critics, notably from labour movement traditions, warn that decoupling income from work may erode the social and psychological benefits that employment confers — a sense of purpose, community, and identity — though this view is contested by those who argue that paid work is merely one source of meaningful activity among many.
Questions
1. Supporters of UBI claim that it would remove the shame sometimes felt by people receiving government assistance.
2. The Finnish pilot study demonstrated that receiving UBI payments caused participants to stop looking for work.
3. The Finnish pilot programme was subsequently extended beyond 2018 due to its positive outcomes.
4. Some opponents argue that existing welfare systems, despite their flaws, may offer greater assistance to those most in need compared with a universal flat payment.
5. All critics of UBI agree that paid employment is the primary source of meaning in people's lives.
6. Countries with high levels of automation have been more likely to implement UBI as a formal national policy.
7. Some critics point out that UBI does not resolve certain non-financial obstacles that prevent people from finding employment.
Passage
The proliferation of large language models (LLMs) has prompted a reappraisal of longstanding assumptions within philosophy of mind, particularly regarding the relationship between syntactic processing and semantic understanding. The seminal thought experiment proposed by John Searle in 1980, commonly referred to as the Chinese Room Argument, posited that a system manipulating symbols according to formal rules could produce outputs indistinguishable from those of a native speaker without possessing any genuine comprehension of meaning. Searle's argument was directed primarily at what he termed Strong Artificial Intelligence — the thesis that an appropriately programmed computer not only simulates but actually instantiates mental states, including understanding. Contemporary defenders of functionalism, however, dispute this framing, contending that if a system's functional organisation is sufficiently isomorphic to that of a human mind, the question of substrate — biological versus silicon — becomes philosophically irrelevant.
The empirical capabilities of recent LLMs have complicated this debate in ways that neither camp fully anticipated. These models demonstrate not merely pattern-matching within their training distribution but apparent generalisation to novel contexts, analogical reasoning, and, in some studies, rudimentary theory of mind — the capacity to attribute mental states to others. Critics are quick to note, however, that such behaviours may constitute sophisticated statistical mimicry rather than evidence of inner experience, and that the absence of embodiment, temporal continuity, and phenomenal consciousness renders comparisons to human cognition fundamentally misleading. The disagreement, therefore, may ultimately rest not on empirical questions about what these systems can do, but on prior metaphysical commitments about what understanding, consciousness, and mind essentially are.
A further dimension of the debate concerns the social and epistemological implications of deploying systems that appear cognitively competent without their underlying mechanisms being transparent, even to their creators. There is a growing body of literature examining what researchers have termed the "alignment problem" — the challenge of ensuring that the objectives an AI system effectively pursues correspond to the intentions of its designers and the values of the broader society it serves. Unlike earlier conceptions of AI risk, which focused on science-fiction scenarios of explicit hostility, contemporary alignment research is largely concerned with subtler forms of misspecification: systems that optimise for measurable proxies of human values rather than those values themselves, potentially with divergent and unforeseeable consequences.
What unites these threads — philosophical, empirical, and sociotechnical — is a recognition that the development of increasingly capable AI systems is not merely a technical enterprise but one that engages fundamental questions about the nature of mind, the architecture of knowledge, and the governance of powerful technologies. Whether the philosophical issues are ultimately resolvable, or whether they represent irreducibly contested terrain, may matter less in practice than the institutional, regulatory, and cultural frameworks through which societies choose to deploy and constrain these systems.
Questions
1. Searle's Chinese Room Argument was originally aimed at a specific version of AI theory that claimed machines could genuinely possess mental states.
2. Functionalists maintain that the biological composition of a mind is the key factor in determining whether genuine understanding is present.
3. Searle later revised his Chinese Room Argument in response to advances in neural network research.
4. Some researchers have found evidence suggesting that certain LLMs can reason about the mental states of others.
5. Contemporary alignment research is primarily focused on the risk of AI systems becoming openly hostile to human beings.
6. The authors of alignment research literature are predominantly based in academic philosophy departments rather than technology companies.
7. A key concern with alignment is that AI systems may pursue measurable stand-ins for human values rather than those values in their full complexity.
8. The passage concludes that resolving the philosophical questions about AI and mind is more important than developing governance frameworks for these technologies.