영어 모의고사 (자동 편성)

Automation is transforming labor markets more quickly than economists predicted only a decade ago. Factories once staffed by hundreds of workers now rely on robotic arms ①that assemble products with remarkable precision. Warehouses use automated systems ②to sort and deliver packages within a few hours. This shift does not simply eliminate jobs; it also creates roles that ③never exists before. Technicians who maintain robotic equipment are now in high demand, and engineers who design efficient systems ④are highly valued. Policymakers argue that retraining programs ⑤are essential to help displaced workers move into emerging fields.

As governments and companies work to address climate change, a new category of employment ①known as green jobs has expanded rapidly. These positions include solar panel installers, wind turbine technicians, and specialists who design energy-efficient buildings. Countries that have invested heavily in renewable energy have seen employment in this sector ②grown far faster than in the economy overall. Young workers, in particular, are drawn to green careers because they ③offer a sense of purpose alongside financial stability. Critics point out that transitioning workers from fossil fuel industries to green jobs is not always simple, ④since the required skills can differ significantly. Governments are therefore introducing training programs designed ⑤to help such workers shift smoothly into renewable energy careers.

After a viewer finishes an episode, a streaming service rarely leaves the choice of what to watch next entirely up to chance. Instead, a recommendation algorithm ① compares that viewer's habits with patterns drawn from millions of other users who watched similar content, then ranks thousands of titles in order of predicted interest. This approach keeps viewers ② disengaged far longer than a simple list of new releases ever could, which is precisely why streaming companies invest so heavily in refining it. The system is not without drawbacks, however. Because the algorithm favors titles similar to what a viewer already enjoys, it can quietly ③ narrow someone's exposure to unfamiliar genres, directors, or cultures, creating a comfortable but repetitive bubble. Some platforms have begun inserting occasional wildcard suggestions, deliberately unrelated to past viewing habits, in an attempt to ④ counteract this narrowing effect and keep recommendations from becoming too ⑤ predictable.

Planning a multi-city trip once meant hours spent comparing flight schedules, reading hotel reviews, and mapping out which sights were close enough to visit in a single day. AI travel planners now ① compress much of that work into a short conversation, asking about a budget, a travel style, and a handful of preferences before generating a full day-by-day itinerary within minutes. The tool draws on enormous amounts of data to suggest a route that avoids obvious ② scheduling conflicts. Many travelers appreciate having a solid starting point rather than a ③ blank page. Still, seasoned travelers warn that these itineraries can feel oddly ④ unique, often steering users toward the same popular landmarks that every other AI-generated plan recommends, while ⑤ overlooking smaller, lesser-known places that a knowledgeable local guide might have suggested instead.

A growing number of health apps now track steps, sleep, and heart rate throughout the day, quietly building a detailed picture of a user's physical condition without requiring a single visit to a doctor's office. (A) Doctors caution, however, that these apps are designed to detect patterns, not to diagnose illness, and that a worried user should always confirm any alarming reading with a professional. (B) For people living far from specialists or unable to afford frequent checkups, this kind of constant monitoring can feel like a genuine safety net. (C) By comparing this stream of data against patterns drawn from millions of other users, the app's algorithm can flag early warning signs, such as an irregular heartbeat, long before the person notices anything unusual.

Only a decade ago, translation apps produced sentences so awkward that users often laughed at the results rather than trusting them. (A) Frequent travelers now point their phone cameras at street signs and receive an instant translation overlaid on the screen, thanks to this leap in accuracy. (B) Even so, the technology still struggles with humor, sarcasm, and cultural nuance, areas where a single wrong word can completely change the intended meaning. (C) Today, many of these apps rely on neural networks that analyze entire sentences at once, capturing context instead of translating word by word.

주어진 문장: This is a significant shift from earlier generations, who often stuck with a single trusted brand for years. Generation Z, typically defined as those born between the late 1990s and early 2010s, approaches shopping quite differently from previous generations. ( ① ) Having grown up with smartphones and social media, they research products extensively online before making even small purchases. ( ② ) Unlike older generations, who often valued brand loyalty above all else, many members of Generation Z prioritize a company's values, switching brands easily if one no longer matches their beliefs. ( ③ ) They also tend to favor secondhand and resale platforms, viewing sustainability as an important factor rather than an afterthought. ( ④ ) Peer recommendations shared through short videos frequently carry more weight than traditional celebrity endorsements. ( ⑤ ) Businesses that fail to adapt to these preferences risk losing an entire generation of potential customers.

주어진 문장: Still, the risk of falling behind outweighs the discomfort of constant adjustment, most experts say. As technology continues to reshape nearly every profession, the idea of finishing education after graduation has become outdated. ( ① ) Workers who once expected their initial training to last an entire career now find that skills can become obsolete within just a few years. ( ② ) Lifelong learning, therefore, has shifted from being an optional pursuit to a practical necessity for staying competitive in the job market. ( ③ ) Many professionals now take short online courses, attend workshops, or earn new certifications while continuing to work full-time. ( ④ ) Critics argue that constant learning can be exhausting and difficult to balance with personal responsibilities. ( ⑤ ) In a rapidly changing economy, the ability to learn continuously may matter more than any single degree.

Treating only one side of this equation, therefore, often leaves the other free to sustain the sleeplessness on its own. Insomnia is rarely caused by a single factor; it usually emerges from an interaction between psychological stress and physiological arousal that keeps the body from settling into sleep. ( ① ) A common trigger is what researchers call cognitive hyperarousal, in which the mind continues to race with worries about work, relationships, or even the inability to sleep itself, creating a frustrating cycle where anxiety about insomnia becomes a cause of insomnia. ( ② ) At the same time, the body's stress response system can become chronically activated, releasing hormones such as cortisol that keep heart rate and body temperature elevated at night, both of which interfere with the natural drop in arousal needed to fall asleep. ( ③ ) Poor sleep habits, including irregular bedtimes and excessive screen use before bed, can further weaken the body's internal signals for sleep onset. ( ④ ) Because these psychological and physiological factors reinforce one another, effective treatment for chronic insomnia addresses both the racing mind and the underlying pattern of physical tension, rather than relying on medication alone. ( ⑤ )

Shoppers use it to find where an item seen on the street can be purchased, while students use it to identify plants, insects, or historical artworks in seconds. Instead of typing keywords into a search bar, a growing number of people now simply upload a photo and let an algorithm figure out what it contains. ( ① ) This process, known as reverse image search, compares the visual patterns in a picture against a massive database, identifying everything from a landmark in the background to the exact model of a pair of sneakers. ( ② ) The system works by breaking an image down into countless small features, such as edges, colors, and shapes, then matching that pattern against millions of stored examples. ( ③ ) It is not flawless, however. ( ④ ) A blurry photo, an unusual camera angle, or an object partly hidden behind another can easily confuse the algorithm, leading to search results that have nothing to do with the original picture at all. ( ⑤ )