영어 모의고사 (자동 편성)

Planning a multi-city trip once meant hours ① 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 compress much of that work into a short conversation, ② 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, including flight prices, seasonal weather patterns, and reviews ③ leaving by previous travelers, to suggest a route that avoids obvious scheduling conflicts. Many travelers appreciate ④ having a solid starting point rather than a blank page. Still, seasoned travelers warn that these itineraries can feel oddly generic, often ⑤ steering users toward the same popular landmarks.

Many companies today advertise their products as environmentally friendly, yet not all of these claims are accurate. This practice, ①knowing as greenwashing, involves exaggerating or fabricating a product's positive impact on the environment. Consumers, ②who are increasingly concerned about climate change, often trust such claims without questioning them closely. As a result, they may pay higher prices for products ③that are no more sustainable than ordinary alternatives. Genuine environmental efforts, which usually ④require significant investment and long-term planning, are far more costly than simply changing a label. Therefore, governments should establish clear standards ⑤that require companies to prove their environmental claims with verifiable data.

Opening most camera apps today reveals a row of filters that can smooth skin, brighten eyes, and reshape a jawline before a photo is even taken, all powered by AI models trained to recognize facial features in real time. What began as a playful novelty has become a ① default setting for many users, subtly adjusting nearly every selfie posted online. Psychologists have grown concerned about a specific consequence of this shift: people increasingly compare their unfiltered reflection in a mirror to a filtered version of themselves seen constantly on a screen, a comparison that earlier generations never had to ② face. Some social media platforms have responded by ③ labeling heavily edited photos or banning certain filters that alter body shape. Whether such small warnings can meaningfully ④ worsen the daily flood of filtered images, however, remains an ⑤ open question that researchers are only beginning to study.

A smart thermostat that learns a family's daily rhythm can lower the temperature automatically before everyone wakes up cold, while smart lights that follow a resident's schedule no longer need to be switched on and off by hand. These small ① conveniences rest on a shared foundation: sensors collect data about temperature, motion, and light throughout the home, and an algorithm gradually learns which settings match each household's actual habits rather than a factory default. Over months of use, the system becomes noticeably ② better at anticipating needs, often adjusting settings moments before a resident would have reached for a switch. Yet convenience comes with a trade-off that many households ③ overlook. Every one of these small adjustments depends on constant data collection, meaning that a detailed record of daily habits is quietly being ④ stored somewhere ⑤ beyond their immediate control, giving residents full and constant access to exactly how it is used.

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 compares that viewer's habits with patterns drawn from millions of other users, then ranks thousands of titles in order of predicted interest. The system is not without drawbacks, however. Because the algorithm favors titles similar to what a viewer already enjoys, it can quietly 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 _______________.

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. 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 experiencing it would have noticed anything unusual. Doctors caution, however, that these apps are designed to detect patterns, not to diagnose illness, and that _______________.

Many teenagers check their social media accounts dozens of times a day, worried that they might miss something important happening among their friends. This anxiety, known as FOMO, or the fear of missing out, arises when people believe that others are enjoying experiences from which they themselves are excluded. For example, a student scrolling through photos of a party she was not invited to may suddenly feel a wave of loneliness and regret, even though the event has already ended. Constantly refreshing feeds to avoid missing such updates, however, makes it difficult to concentrate on schoolwork or conversations happening in the present moment. Moreover, this endless comparison with curated highlights of other people's lives tends to deepen feelings of anxiety rather than relieve them. Therefore, students should learn to ___________.

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 )

Critics counter that this framing can understate the risk, since even a first draft ultimately shapes everything that follows it. Rather than replacing human creativity outright, many artists, writers, and filmmakers have begun treating AI tools as an unusual kind of collaborator, one that generates dozens of rough options in the time it would take a person to sketch just one. ( ① ) A novelist might ask an AI model for ten possible opening lines and then discard nine, keeping only the phrase that sparks an idea worth developing further. ( ② ) A film composer might use an AI system to generate a rough melody, then rework it entirely by hand until it fits the emotional tone of a specific scene. ( ③ ) What makes this collaboration work, according to many creators, is that the human remains firmly in charge of judgment and taste. ( ④ ) The AI's output, in this view, is treated as raw material rather than a finished product. ( ⑤ )

주어진 문장: Because people naturally trust those with specialized knowledge, this technique can be remarkably persuasive. Advertisements often rely on subtle psychological techniques that persuade viewers without their conscious awareness. ( ① ) One common method, known as social proof, shows images of many people using or enjoying a product, suggesting that its popularity guarantees quality. ( ② ) Another technique appeals to authority, featuring experts or professionals endorsing a product to make it seem more credible and trustworthy. ( ③ ) Emotional appeals are equally common, connecting products with feelings such as happiness, nostalgia, or belonging rather than focusing on practical features. ( ④ ) Repetition also plays a significant role, since seeing the same advertisement multiple times increases familiarity, which people often mistake for reliability. ( ⑤ ) Researchers studying consumer behavior have found that viewers who understand these techniques are less easily influenced by them.