영어 모의고사 (자동 편성)

Fast fashion refers to cheap, trendy clothing ①produced quickly and replaced almost as fast as it is bought. Because these garments are ②designed to be worn only a few times, huge amounts of fabric end up in landfills every year, and the dyeing process pollutes rivers near factories. In contrast, a growing number of brands are turning toward the circular economy, an economic model in which materials are ③reused, repaired, or recycled instead of being thrown away after a single use. For example, some companies collect old clothes, break down the fibers, and weave them into new fabric, while others let customers ④to rent outfits for special occasions rather than buying garments they will barely wear. These approaches keep resources ⑤circulating within the system longer, reducing demand for raw materials. Therefore, shifting from a throwaway habit toward a circular one may be essential for making the fashion industry sustainable.

Generative AI systems learn to write, draw, and compose by studying enormous collections of existing human work, much of ①which was created without the artists' knowledge or consent. Supporters of the technology argue that this process ②resembles how a human student learns by studying the masters, absorbing style and technique rather than copying specific pieces. Critics respond that the comparison ③breaks down at scale: a single AI model can absorb millions of works in days and then generate outputs that directly compete with the very artists whose work ④trained it. Courts around the world are now ⑤ask to decide whether training an algorithm on copyrighted material counts as fair use or as infringement.

Consider a large heap containing ten thousand grains of sand. Nearly everyone agrees that removing a single grain from such a heap leaves another heap behind; surely one grain could never make the difference between a heap and a non-heap. Yet if this principle is applied repeatedly, grain by grain, the heap eventually ②grows to a single lonely grain, or even to no grains at all, and logic alone seems to force us to accept that this final result still counts as a heap. Something has clearly ①gone wrong along the way, since no reasonable person would call one grain of sand a heap, but pinpointing exactly which single removal transformed a heap into a non-heap seems ③impossible. The puzzle exposes a deep discomfort with vague terms like "heap," "tall," or "bald," concepts that seem to admit no sharp ④boundary yet are used confidently in everyday language. Some philosophers conclude that classical logic itself may need to be ⑤revised to accommodate the genuine vagueness built into ordinary human language.

Marketers have long recognized that perceived scarcity, the sense that a product or opportunity is available only in limited quantity or for a limited time, can dramatically increase its ①desirability, even when the item's intrinsic qualities remain entirely unchanged. This phenomenon, known as the scarcity effect, operates on a simple psychological principle: when something appears ②easy to obtain, people tend to infer that it must be valuable, since truly worthless items rarely generate genuine competition for possession. A retailer who labels a product as "limited edition" or displays a countdown timer beside a discounted offer exploits this inference, prompting customers to make ③hurried purchase decisions they might otherwise postpone or reconsider. Experimental studies confirm that identical products are rated as more desirable and often command ④higher prices when framed as scarce than when the same products are presented as widely and continuously available. Consumers who later reflect calmly on such purchases frequently discover that the item's actual usefulness fell well short of the ⑤urgency they experienced at the moment of decision.

The gig economy has grown ①rapidly over the past decade, as digital platforms connect customers directly with independent workers. This model offers clear advantages: workers can choose when and how much they work, providing valuable ②rigidity that traditional employment rarely allows. However, gig workers often ③lack benefits such as health insurance and paid leave, which full-time employees typically receive. Because their income can ④fluctuate sharply from month to month, many gig workers struggle to plan their finances confidently. Governments therefore face growing pressure to ⑤protect independent workers through new policies.

When engineers design the software that controls a self-driving car, they inevitably face a question that philosophers have debated for ①decades. If a crash becomes unavoidable, should the vehicle protect its own passenger at all costs, or should it be programmed to ②minimize total harm, even if that means steering toward the person inside? Surveys reveal an uncomfortable ③contradiction: most people say a car should be programmed to save the greater number of lives, yet the same people admit they would never buy a vehicle designed to sacrifice its own owner. This gap between the ideal and the personal choice suggests that ethical programming cannot be settled by public opinion alone. Manufacturers, regulators, and philosophers must instead agree on ④transparent rules before autonomous vehicles are ⑤forbidden to make such decisions on the road.

Facial recognition software has moved rapidly from airport security lines into shopping malls, schools, and even private apartment buildings, promising ①convenience in exchange for a quick scan of one's face. Proponents note that the technology can unlock doors, catch shoplifters, and speed up identity checks far faster than any human guard could manage. Independent studies, however, have repeatedly found that many commercial systems perform ②less accurately on women and people with darker skin tones, a gap that can lead to wrongful identification with serious real-world consequences. Several cities have already reported cases in which an innocent person was ③detained based on a flawed match. Until these systems can prove equally reliable for everyone, critics argue, deploying them at all represents a form of quiet ④discrimination dressed up as ⑤inefficiency.

As technology develops rapidly, many new jobs are ①appearing that did not exist a decade ago. Data analysts help companies make decisions based on huge amounts of information. Renewable energy technicians install and repair solar panels and wind turbines, meeting the ②shrinking demand for clean power. Healthcare is expanding beyond hospitals, creating roles for specialists who design digital health tools for elderly patients. These emerging jobs ③share one common feature: they combine technical skill with the ability to solve real-world problems. Experts predict that future workers will need to keep learning new skills ④throughout their careers. Staying curious and adaptable may matter ⑤more than choosing a single fixed career path.

Building a career portfolio is a great way to track your growth throughout high school. Start by choosing a format, such as a folder, a notebook, or a digital file. Next, include items like club activities, volunteer work, certificates, and sample projects, along with a short reflection for each one. Update your portfolio ___________, since memories of small experiences fade quickly. A well-organized portfolio not only helps you apply for programs or scholarships, but it also helps you understand your own growth over time.

Blockchain technology was originally promoted as a way to remove the need for trusted middlemen, allowing strangers to exchange value directly through a shared, tamper-resistant ledger. (A) In practice, however, a small number of large players have come to dominate many blockchain networks, controlling enough power to influence outcomes that were supposed to be decided collectively. (B) In theory, this design distributes power away from any single institution and toward the network as a whole. (C) Critics note a further irony: when something goes wrong, there is often no institution left to appeal to, since the system was designed to eliminate central authority.