영어 모의고사 (자동 편성)

Philosopher Harry Frankfurt devised a scenario ①to challenge a long-held assumption about moral responsibility: that a person can be blamed for an action only if they could genuinely have done otherwise. Imagine a man named Black who secretly implants a device in another man's brain, ②ready to force a particular decision if the second man shows any sign of choosing differently. The second man, however, decides entirely on his own to perform the very action Black wanted, and the device never ③activating at all. Black's hidden mechanism made it impossible for the man ④to have chosen otherwise, yet most people still consider him fully responsible for what he freely decided to do. Frankfurt used this scenario to argue that moral responsibility depends on the actual reasoning behind a choice, not on some abstract guarantee that an alternative path ⑤remained available the entire time.

Suppose a mysterious being with a near-perfect track record of ①predicting 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 ②placed 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 ③been made and cannot change. One line of reasoning says taking both boxes is strictly better, since whatever is already inside the boxes cannot ④be 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 ⑤guaranteeing an empty Box B.

Suppose you meet a quiet, gentle man ①who speaks softly, tends a small garden, and organizes his bookshelf with meticulous care. ②Ask whether he is more likely a florist or a truck driver, most people instinctively choose florist, since his personality matches the stereotype so neatly. This judgment, however, ③ignores 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. Relying on resemblance to a familiar category rather than on underlying numerical proportions, ④known among researchers as representativeness, leads people to overlook these base rates almost automatically. Even trained professionals, ⑤who should know better, often fall into the same trap when a vivid description feels more convincing than plain statistics.

Blockchain technology was originally promoted as a way to remove the need for trusted middlemen, allowing strangers to exchange value directly and verify transactions through a shared, ①tamper-resistant ledger rather than through a bank or government agency. In theory, this design distributes power away from any single institution and toward the network as a whole. In practice, however, a small number of large players have come to ②dominate many blockchain networks, controlling enough computing power or currency to influence outcomes that were supposed to be decided collectively. Critics note a further irony: when something goes wrong, such as a hacked exchange or a lost password, there is often ③ample institutional support to appeal to, since the entire system was designed precisely to eliminate that kind of central authority. Whether decentralization can ④survive this concentration of power remains one of the technology's most ⑤unresolved questions.

Many large companies now rely on artificial intelligence to screen job applications before a human ever sees them. These systems promise efficiency, scanning thousands of resumes in seconds and ranking candidates according to patterns drawn from previous hiring decisions. However, this reliance on historical data creates a troubling risk. If a company's past hiring favored a particular group, the algorithm may learn to treat that pattern as a marker of success and quietly reproduce it, even when no one intended discrimination. Unlike a human interviewer, the system offers no explanation for its choices, which means that _______________. Some researchers argue that fairness cannot be added afterward; it must be built into the system's design from the very beginning.

When consumers compare two products and assume that the one labeled "eco-friendly" is automatically the more sustainable choice, they often overlook the complexity involved in verifying such a claim. (A) Life cycle assessment, commonly abbreviated as LCA, is a systematic method developed to evaluate the environmental impact of a product across every stage of its existence. This method examines raw material extraction, manufacturing, transportation, use, and disposal, compiling data on energy consumption and emissions generated at each stage. (B) By tracing a product from its origin to its disposal, this approach reveals impacts that might otherwise remain hidden from consumers who see only the finished item on a shelf. For example, an electric vehicle may produce no emissions while being driven, yet the mining of metals for its battery can generate substantial environmental costs elsewhere. (C) Without accounting for these earlier stages, a superficial comparison could mistakenly present the vehicle as entirely emission-free. Therefore, researchers increasingly rely on life cycle assessment to make informed decisions rather than trusting labels alone.

Modern consumer culture often assumes that expanding the range of available options will automatically make people freer and happier, yet a growing body of research suggests the opposite may sometimes be true. (A) Having considered so many possibilities, a person naturally imagines the specific advantages that a different, unchosen option might have offered, and this imagined comparison quietly erodes contentment with what was actually selected. (B) When individuals select from an enormous set of alternatives, satisfaction with the final choice frequently declines rather than rises, even when the chosen item is objectively excellent. (C) This decline stems not from the difficulty of deciding but from what happens afterward, once a decision has already been made.

The practical consequence of this precision has been a dramatic acceleration in the pace of genetic research itself. Bacteria have been cutting up invading viral DNA for billions of years, long before any scientist thought to borrow the trick for use in a laboratory. ( ① ) The CRISPR-Cas9 system, as it is now known, relies on a short guide RNA that matches a specific DNA sequence, leading a scissor-like enzyme called Cas9 directly to that exact location in the genome. ( ② ) Once Cas9 arrives at the target site, it slices both strands of the DNA helix, and the cell's own repair machinery rushes in to mend the cut, often introducing a small change in the process. ( ③ ) By supplying the cell with a template during this repair step, scientists can direct that machinery to insert a specific new sequence. ( ④ ) This goes well beyond merely disabling the original gene. ( ⑤ ) What once required years of painstaking work to alter a single gene can now, with a properly designed guide RNA, be accomplished within days.

Until clearer rules emerge, artists, developers, and publishers remain locked in a legal gray zone that satisfies almost no one. Generative AI systems learn to write, draw, and compose by studying enormous collections of existing human work, much of which was created without the artists' knowledge or consent. ( ① ) Supporters of the technology argue that this process resembles how a human student learns by studying the masters. ( ② ) Critics respond that the comparison breaks down at scale, since a single AI model can absorb millions of works in days. ( ③ ) Courts around the world are now being asked to decide whether training an algorithm on copyrighted material counts as fair use or as infringement. ( ④ ) This is a question the law was never designed to answer. ( ⑤ )

주어진 문장: This apparent immunity to forgetting seemed to set flashbulb memories apart from every other category of recollection. When people recall precisely where they were and what they were doing at the moment they learned of some momentous public event, the resulting memory often feels extraordinarily vivid, as though it had been etched into the mind with photographic precision; researchers have termed such recollections flashbulb memories. ( ① ) Proponents of this concept once argued that the emotional intensity and surprise accompanying such events trigger a distinct neural mechanism that preserves details with unusual fidelity, effectively exempting them from the gradual decay that afflicts ordinary memories. ( ② ) Subsequent longitudinal studies, however, have complicated this picture considerably: when researchers compared accounts gathered within days of an event to accounts gathered years later, they discovered that details had frequently been altered, omitted, or even fabricated, ( ③ ) even though the individuals reporting them expressed unwavering confidence in their accuracy. ( ④ ) This persistent mismatch between subjective certainty and objective consistency implies that flashbulb memories, far from being flawless recordings, are reconstructed narratives shaped by rehearsal, media exposure, and the passage of time. ( ⑤ )