영어 모의고사 (자동 편성)

Last month, I ①attended a three-day career camp during summer vacation. The camp offered workshops in fields such as broadcasting, cooking, and environmental science. On the first day, I chose the broadcasting workshop, ②where students practiced writing short news scripts. It was harder than I expected, since staying calm while a camera ③recorded my every move felt strange at first. The instructors, who all had real broadcasting experience, gave detailed feedback rather than simple praise, ④that helped us improve quickly. On the final day, each team ⑤presented a short news segment to the entire camp.

As companies collect enormous amounts of personal data to improve their products and target advertisements, serious ethical questions have emerged about how that information should be handled. Employees who work with big data now face responsibilities that previous generations rarely encountered, since a single careless decision can expose millions of people's private information. Regardless of which approach prevails, most experts agree that ___________. Universities have begun adding data ethics courses to computer science programs, recognizing that future employees will need to balance innovation with responsibility.

When Mina graduated from college five years ago, she had never even heard the term "data scientist." Everything changed when a small tech startup, which was building an app to predict traffic patterns, hired her to analyze massive amounts of data. Mina quickly discovered that she loved turning raw numbers into insights that helped real people make better decisions. Within two years, ___________, as companies in every industry realized how valuable data could be. Today, Mina leads a team of ten analysts, mentoring young graduates who are drawn to a field that barely existed when she began her own career.

Suppose you meet a quiet, gentle man who speaks softly, tends a small garden, and organizes his bookshelf with meticulous care. (A) This judgment, however, ignores a crucial fact: truck drivers vastly outnumber florists in almost every country, which means that, statistically, he is far more likely to belong to the larger group regardless of how well he fits the flower-shop image. (B) Relying on resemblance to a familiar category rather than on underlying numerical proportions, known among researchers as representativeness, leads people to overlook these base rates almost automatically. Even trained professionals, who should know better, often fall into the same trap when a vivid description feels more convincing than plain statistics. Consequently, teaching people to pause and ask how common something actually is, instead of merely how typical it appears, can meaningfully improve the accuracy of everyday predictions and reduce costly errors in judgment. (C) Asked whether he is more likely a florist or a truck driver, most people instinctively choose florist, since his personality matches the stereotype so neatly.

주어진 문장: This selective compression of memory is not random, however; it follows a strikingly predictable psychological pattern. When people look back on a multi-day journey, they rarely recall every hour with equal clarity; instead, memory tends to compress the entire experience into just a few representative moments. ( ① ) Psychologists have found that two points carry disproportionate weight in this process: the single moment when emotion, whether joy or discomfort, reached its highest intensity, and whatever happened right before the experience concluded. ( ② ) Consider two hikers who complete an identical five-day trek. ( ③ ) The first finishes with a grueling, rain-soaked final climb, while the second enjoys a calm, scenic descent on the last afternoon despite having endured an equally difficult ascent earlier in the trip. ( ④ ) Even though both hikers faced comparable hardship overall, the second is far more likely to remember the journey fondly, simply because the trip ended pleasantly. ( ⑤ ) This pattern reveals that overall satisfaction is not calculated as an average of every experienced moment; rather, it is shaped disproportionately by whichever moments felt most intense and by however the experience happened to end.

For example, children and elderly people are especially vulnerable because their bodies cool down less efficiently. Every summer, doctors warn about the danger of heatstroke during long heatwaves, and this condition does not affect everyone equally. ( ① ) Heatstroke happens when the body's temperature rises too high and cannot cool itself down. ( ② ) This condition can be life-threatening if it is not treated quickly. ( ③ ) To prevent heatstroke, drink plenty of water and avoid outdoor activities during the hottest hours of the day. ( ④ ) Wearing light clothing also helps your body stay cool. ( ⑤ ) If symptoms appear, move to a shaded or air-conditioned place immediately.

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

Instead, these trainers help workers use AI tools wisely, without becoming fully dependent on them. As artificial intelligence becomes part of everyday life, entirely new job titles are appearing in the workplace. ( ① ) Prompt engineers, for instance, design effective instructions that help AI programs produce accurate and useful results. ( ② ) AI ethics officers examine whether a company's technology treats users fairly and avoids harmful bias. ( ③ ) Meanwhile, human-AI collaboration trainers do not simply teach employees to use every new AI feature available. ( ④ ) These jobs did not exist even ten years ago, yet they are growing quickly across many industries. ( ⑤ ) This suggests that success in an AI-driven future will depend more on uniquely human skills.

The software company, in turn, may argue that no algorithm can be expected to be perfect. Hospitals are increasingly adopting artificial intelligence tools that can scan medical images and flag potential tumors faster than experienced radiologists. ( ① ) When an AI system misses a diagnosis that a human doctor would likely have caught, responsibility becomes difficult to assign. ( ② ) The doctor may argue that they simply trusted a tool the hospital required them to use. ( ③ ) The hospital, meanwhile, may argue that the software company guaranteed its accuracy. ( ④ ) Until legal systems clarify this chain of responsibility, patients harmed by an algorithmic error may find themselves with no clear party to hold accountable. ( ⑤ )

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