영어 모의고사 (자동 편성)

Building brand loyalty has traditionally been considered one of the most valuable goals in marketing, since loyal customers ①tend to spend more and recommend products to others. Companies invest significant resources in loyalty programs, ②offering points, discounts, and exclusive access to encourage repeat purchases. Genuine loyalty, critics contend, should be earned through consistent quality and honest treatment of customers, not through artificial incentives that merely ③delays a customer's departure. Furthermore, excessive focus on retaining existing customers can cause companies ④to neglect innovation, since they assume loyal buyers will continue purchasing regardless of improvements. Relying solely on loyalty programs without addressing underlying product quality may ultimately ⑤backfire.

When engineers design the software ①that controls a self-driving car, they inevitably face a question that philosophers have debated for decades. If a crash becomes unavoidable, should the vehicle protect its own passenger at all costs, or should it be programmed ②minimizing total harm, even if that means steering toward the person inside? Surveys reveal an uncomfortable contradiction: most people say a car should be programmed to save the greater number of lives, yet the same people admit ③they 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 ④be settled by public opinion alone. Manufacturers, regulators, and philosophers must instead agree on transparent rules before autonomous vehicles ⑤are allowed to make such decisions on the road.

Classical economic models typically assume that people discount future rewards at a constant rate, valuing a reward received later somewhat less than an identical reward received now, but doing so ①consistently across all time horizons. Empirical observation, however, reveals a different pattern: people apply a much ②steeper discount to the immediate future than to the distant future. When the reward or cost in question lies safely in the future, its emotional weight remains ③vivid, allowing rational long-term goals to dominate one's stated intentions. Once that same reward or cost draws near, however, its immediacy triggers a disproportionately strong emotional pull, frequently ④overriding the very plans made earlier with such apparent confidence. This dynamic helps explain chronic procrastination, since tasks that carry long-term benefits are perpetually ⑤deferred in favor of activities offering more immediate satisfaction.

Jiho had always assumed he would join a large corporation after graduation, just as his parents expected. During his final year of university, however, he joined a small student team building an app that connected local farmers directly with restaurants. What started as a class project gradually turned into something more ①serious, as several restaurants began placing regular orders through their prototype. Jiho and his teammates decided to ②abandon their idea and instead spend a year developing it further, despite warnings from relatives who considered the plan too risky. They worked from a cramped apartment, surviving on ③limited savings while learning skills ranging from coding to negotiating with suppliers. After nearly failing twice, the team secured a small investment that allowed them to hire their first ④employee. Looking back, Jiho believes that the uncertainty of startup life taught him far more about problem-solving than any traditional job could have ⑤offered.

The discovery of CRISPR gene-editing technology gave scientists a tool ①precise enough to correct a single mistaken letter in the human genome, raising hope for curing inherited diseases that have resisted treatment for generations. Yet the same precision that makes CRISPR so promising also makes it ②dangerous in the wrong hands. Editing a gene in a sperm, egg, or early embryo does not simply change one patient; it alters the genetic code passed down to every future generation, a decision no single person should be allowed to make ③alone. Scientific organizations around the world have therefore drawn a careful line, ⑤permitting gene editing to treat disease in existing patients while ④permitting any edit that would be inherited by their descendants. Critics worry, however, that as the technology becomes cheaper and more widely available, this line will become harder to enforce than it is to draw.

Suppose a mysterious being with a near-perfect track record of predicting human choices presents a player with two boxes. Box A always contains a visible thousand dollars, while Box B contains either a million dollars or nothing at all, depending on a prediction the being made before the game even began. If the being predicted the player would take only Box B, it placed a million dollars inside; if it predicted the player would take both boxes, it left Box B empty. The player may choose to take only Box B, or to take both boxes, and the prediction has already been made and cannot change. One line of reasoning says taking both boxes is strictly better, since whatever is already inside the boxes cannot be altered by the player's choice at this point. A second line of reasoning says taking only Box B is better, since the being's near-perfect accuracy means that choosing both boxes almost guarantees an empty Box B. _______________.

As technology develops rapidly, many new jobs are appearing that did not exist a decade ago. Data analysts, for example, help companies make decisions based on huge amounts of information. Renewable energy technicians install and repair solar panels and wind turbines. Healthcare is expanding beyond hospitals, creating roles for specialists who design digital health tools for elderly patients. These emerging jobs share one common feature: ___________. Experts predict that future workers will need to keep learning new skills throughout their careers.

Online reviews have transformed the way consumers evaluate products before buying them. (A) Unfortunately, some of these reviews are not genuine, having been written by paid promoters rather than actual customers. (B) Shoppers now trust the opinions of strangers online almost as much as recommendations from friends or family. (C) For this reason, several platforms have started using technology to detect and remove suspicious reviews automatically.

Online advertising has become increasingly personalized as algorithms analyze user behavior in real time. (A) Critics, however, warn that this precision can be used to exploit psychological weaknesses rather than genuinely help consumers. (B) Supporters claim that this precision benefits users by reducing the number of irrelevant advertisements they encounter. (C) Given these opposing views, many experts call for greater transparency about how such algorithms actually operate.

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 )