영어 모의고사 (자동 편성)

Eyewitness testimony ①has long carried weight in courtrooms, yet decades of research reveal that memories of witnessed events are more malleable than most people assume. When individuals who observe an event ②are later exposed to misleading information about what they saw, whether through a leading question or a conversation with another witness, their recollections frequently incorporate details that never occurred, a phenomenon known as the misinformation effect. In one classic paradigm, participants who watched a video of a traffic accident and ③were then asked how fast the cars were going when they smashed into each other reported higher speed estimates and were more likely to falsely recall broken glass than participants asked the identical question using the milder verb hit. Crucially, these distorted memories often feel genuine to the person experiencing them, since the original memory trace ④become blended with the newly introduced information rather than existing as a separate, contradictory record. Such findings ⑤have prompted legal systems to adopt cautious interviewing protocols designed to minimize suggestive questioning during investigations.

Facial recognition software has moved rapidly from airport security lines into shopping malls, schools, and even private apartment buildings, ①promising convenience 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 ②could manage. Independent studies, however, have repeatedly found that many commercial systems ③performs less 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 ④was detained based on a flawed match. Until these systems can prove equally reliable for everyone, deploying them at all represents a form of quiet discrimination ⑤dressed up as efficiency.

Among the many tools available to those who design choice environments, few are as quietly ①powerful as the default option, the alternative that takes effect automatically unless a person actively selects something else. Because changing a default requires ②deliberate effort, many individuals simply accept whatever arrangement has been preselected for them, regardless of whether that arrangement actually serves their interests best. Countries that automatically enroll citizens in organ donation programs, requiring an explicit request to opt out, consistently report far ③lower donor registration rates than countries that require citizens to actively opt in. Employers who automatically enroll new hires in retirement savings plans likewise see participation rates climb dramatically compared with employers who leave enrollment entirely voluntary. What makes default options so influential is not merely convenience; a default also functions as an implicit signal about what is considered ④normal or recommended, subtly shaping perceptions even among individuals who believe themselves to be deciding ⑤independently.

Factories that once employed hundreds of workers on an assembly line now run with a ①fraction of that staff, as robotic arms handle tasks that used to require human hands. Economists have long debated whether this shift destroys jobs or simply transforms them. Historical evidence offers some ②comfort: previous waves of automation eventually created new categories of work that no one had predicted. However, critics point out that earlier transitions unfolded over generations, giving workers ③ample time to retrain, whereas today's robots are being deployed at a pace that leaves little room for adjustment. A factory worker displaced this year cannot simply wait for a new industry to emerge decades from now. For this reason, many economists argue that the real ④challenge is not the robots themselves, but the ⑤sluggish speed at which society is expected to adapt to them.

Imagine two travelers preparing for the same trip: one refuses to fly after watching news coverage of a recent plane crash, while the other books a flight without hesitation. Statistically, air travel remains far safer than driving the same distance by car, yet vivid, emotionally charged images tend to dominate human judgment more powerfully than dry statistics ever could. This tendency, in which people estimate how likely an event is based on _______________, quietly shapes countless everyday decisions. News broadcasts that repeatedly feature rare disasters can leave viewers convinced that such events are common, even though official records clearly show the opposite. Advertisers and politicians alike exploit this pattern, knowing that a single striking anecdote often persuades audiences more effectively than pages of careful statistics ever manage to.

Many large companies now rely on artificial intelligence to screen job applications before a human ever sees them. (A) Unlike a human interviewer, the system offers no explanation for its choices, which makes the bias difficult to detect until an outside audit reveals it. (B) These systems promise efficiency, scanning thousands of resumes in seconds and ranking candidates according to patterns drawn from previous hiring decisions. (C) However, this reliance on historical data creates a troubling risk, because the algorithm may learn to treat a past discriminatory pattern as a marker of success.

Every time an antibiotic kills off a population of bacteria, a handful of cells carrying a random mutation that resists the drug are left behind to multiply without competition. (A) Repeated over decades, across hospitals, farms, and households worldwide, this simple process of natural selection has produced strains of bacteria that survive treatments once considered reliably effective. (B) The pharmaceutical industry, meanwhile, has slowed the pace at which new antibiotics reach the market, since a drug meant to be taken for only a week or two rarely earns back the enormous cost of developing it. (C) Researchers are therefore searching in unconventional places, screening soil microbes and even genetic databases for new molecules, and some have also revived an older approach using viruses that infect only bacteria to hunt down resistant strains.

Medieval philosophers told the story of a hungry donkey placed exactly midway between two identical, equally fragrant piles of hay, with no factor whatsoever tipping the balance toward either option. (A) Because the donkey is assumed to be a perfectly rational creature that always chooses the option supported by the strongest reason, it supposedly finds itself with no rational basis for choosing one pile rather than the other. (B) Paralyzed by this perfect symmetry, the donkey starves to death precisely because it can find no reason to move in either direction. (C) Critics of the story point out that real animals, and real humans, rarely face situations of such flawless symmetry, since even a tiny, arbitrary preference is usually enough to break the tie in practice.

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.

Suppose a traveler journeyed backward in time and, through some combination of accident and intention, prevented their own grandfather from ever meeting their grandmother. Time travel to the past has long fascinated physicists and philosophers alike, but it also generates a famously troubling contradiction. ( ① ) If the grandfather never had children, the traveler themselves would never have been born, which means the traveler could never have existed to make the trip in the first place. ( ② ) Yet if the traveler never made the trip, the grandfather would have survived to meet the grandmother after all, allowing the traveler to be born and eventually travel back in time. ( ③ ) The story therefore loops endlessly, undermining itself at every turn rather than settling into any stable outcome. ( ④ ) Some physicists resolve the paradox by arguing that any consistent timeline must forbid such self-defeating actions from ever succeeding. ( ⑤ ) Others propose that a traveler who alters the past simply branches off into a separate, parallel timeline instead.