영어 모의고사 (자동 편성)

Classical economic theory long assumed that decision makers ①gather all relevant information, calculate every possible outcome, and select the single option that maximizes their benefit. Herbert Simon, however, questioned this assumption, ②arguing that human beings operate under real constraints of time, knowledge, and mental capacity that make such exhaustive calculation practically impossible. Instead of searching endlessly for the theoretically perfect choice, people typically stop once they find an option that seems good enough to meet their immediate needs, a strategy Simon ③termed satisficing. A shopper comparing refrigerators, for example, rarely examines every model available; she instead sets a few practical criteria, such as price and size, and selects the first appliance that satisfies them adequately. This approach is not a failure of reasoning but rather a sensible adaptation to a world where information is costly and time is genuinely limited. Consequently, models assuming unlimited rationality often fail to predict actual behavior, while frameworks ④acknowledge these cognitive boundaries offer a far more realistic account of how ordinary decisions are ⑤made.

Factories that once employed hundreds of workers on an assembly line now run with a fraction of that staff, as robotic arms handle tasks ①that used to require human hands. Economists have long debated whether this shift destroys jobs or simply ②transforms them. Historical evidence offers some comfort: previous waves of automation eventually created new categories of work that no one ③had predicted. However, critics point out that earlier transitions unfolded over generations, ④given workers time to retrain, whereas today's robots are being deployed at a pace that leaves little room for adjustment. For this reason, many economists argue that the real challenge is not the robots themselves, but the speed at which society ⑤is expected to adapt to them.

Blockchain technology was originally promoted as a way ①to remove the need for trusted middlemen, allowing strangers to exchange value directly and verify transactions through a shared, tamper-resistant ledger rather than through a bank or government agency. In theory, this design ②distributes power away from any single institution and toward the network as a whole. In practice, however, a small number of large players have come to dominate many blockchain networks, ③controlled enough computing power or currency to influence outcomes that were supposed to be decided collectively. Critics note a further irony: when something goes wrong, there is often no institution left ④to appeal to, since the entire system was designed precisely to eliminate that kind of central authority. Whether decentralization can survive this concentration of power ⑤remains one of the technology's most unresolved questions.

When people face a difficult decision, they often weigh not only the expected outcome of each option but also how painful it would feel ①to discover later that a different choice had been better. This anticipation of future regret, rather than the size of the potential loss itself, frequently becomes the dominant factor ②shaping the final decision. Investors, for example, sometimes continue holding a declining stock rather than ③selling it, not because they expect the price to recover, but because selling would force them to confront the possibility ④of having made a clear mistake. Researchers have found that people feel sharper regret over losses that resulted from taking action than over identical losses that resulted from doing nothing, which ⑤help explain why so many individuals default to inaction whenever a decision feels uncertain.

Facing a shortage of caregivers and a rapidly aging population, several countries have begun ①deploying robots designed to remind elderly residents to take medication, monitor for falls, and even offer simple conversation throughout the day. Early trials show that many residents report ②reduced loneliness, particularly when a robot's presence allows an overworked human staff member to spend a few extra minutes with each patient rather than ③rushing between rooms. Critics, however, worry that this framing quietly shifts the goal of care: instead of asking how technology can support human connection, institutions may come to treat a robot's companionship as an acceptable substitute for it, especially in facilities already ④struggle with tight budgets. Advocates for the elderly argue that robots should be evaluated strictly as tools that free up human time for human contact, never as a lower-cost replacement for the contact itself, which ⑤remains irreplaceable.

City governments increasingly market dense networks of surveillance cameras as a straightforward safety upgrade, ①promising faster emergency response and lower crime rates. In many cases, the technology delivers exactly what it promises, ②helping investigators identify suspects within hours rather than weeks. Yet the same infrastructure that catches criminals also creates a permanent record of where ordinary, law-abiding citizens ③go about their daily lives. Once a camera network exists, its purpose can quietly expand, often without new public debate or explicit approval. Civil liberties groups argue that a city should decide how much surveillance it wants before the cameras go up, not years afterward when the infrastructure ④is already impossible removing. Convenience installed today, in other words, can quietly ⑤become control tomorrow.

Conventional economic wisdom holds that more options are always preferable to fewer, since a larger set of alternatives ①increases the likelihood that any individual will find one that precisely matches their preferences. When shoppers are presented with an extensive array of choices, they frequently experience heightened anxiety about making the wrong selection and, paradoxically, become ②less likely to make any purchase or decision at all. Furthermore, individuals who do eventually choose from an overwhelming array often report ③higher satisfaction with their selection than those who chose from a modest handful of options, since the sheer number of unexplored alternatives ④fosters lingering doubt about whether a better choice was overlooked. Businesses that recognize this dynamic have begun deliberately ⑤curating smaller, carefully selected assortments, betting that a narrower range of options can sometimes generate more sales and greater customer satisfaction than abundance.

Consider a student who ①genuinely intends to study for tomorrow's exam yet, when the evening actually arrives, chooses to watch another episode of a favorite show instead, promising herself she will surely study harder next week. This pattern, in which the pull of an immediate pleasure ②overwhelms the value of a distant benefit, appears again and again across ordinary life, from postponed exercise to delayed savings. People do not necessarily fail to understand that the future reward matters more; rather, whatever happens right now simply feels disproportionately more urgent and vivid than anything scheduled for later. Behavioral economists note that this preference ③weakens considerably once both options are pushed into the future, which is why planning a diet starting next month feels ④impossible compared with skipping dessert tonight. Such inconsistency helps explain why gym memberships go unused and retirement accounts remain ⑤underfunded, despite people's stated intentions.

German sociologist Georg Simmel argued that the psychological experience of city life differs fundamentally from life in small towns, primarily because urban residents are bombarded with a much greater volume of stimuli than the human nervous system evolved to process. (B) This detachment, while sometimes criticized as cold or impersonal, also grants urban residents a distinctive freedom, since so few people know or judge them personally. (A) To cope with this constant sensory overload, Simmel proposed, city dwellers develop what he called a blasé attitude, treating most encounters with calculated detachment rather than genuine engagement. (C) Simmel therefore viewed anonymity as a double-edged feature of modern life, one that isolates individuals from deep communal bonds while liberating them from constant surveillance.

Until clearer rules emerge, artists, developers, and publishers remain locked in a legal gray zone that satisfies almost no one. Generative AI systems learn to write, draw, and compose by studying enormous collections of existing human work, much of which was created without the artists' knowledge or consent. ( ① ) Supporters of the technology argue that this process resembles how a human student learns by studying the masters. ( ② ) Critics respond that the comparison breaks down at scale, since a single AI model can absorb millions of works in days. ( ③ ) Courts around the world are now being asked to decide whether training an algorithm on copyrighted material counts as fair use or as infringement. ( ④ ) This is a question the law was never designed to answer. ( ⑤ )