영어 모의고사 (자동 편성)

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

Facial recognition software has moved rapidly from airport security lines into shopping malls, schools, and even private apartment buildings, ① promising 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 ② could manage. Independent studies, however, have repeatedly found that many commercial systems ③ performs 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 ④ was 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 ⑤ dressed up as efficiency.

Financial markets occasionally experience episodes in which asset prices rise far beyond any level that careful analysis of underlying fundamentals could justify, a phenomenon commonly ①attributed to herd psychology. During such episodes, individual investors, observing that prices have already risen substantially, often conclude that continuing to buy is reasonable simply because so many others ②are doing the same, rather than because any independent evaluation supports the purchase. This dynamic can become self-perpetuating: rising prices attract new buyers, whose purchases push prices higher still, thereby ③attracting yet another wave of buyers convinced that the upward trend itself constitutes reliable evidence of underlying value. Historical episodes of speculative excess display a strikingly similar pattern, suggesting that the underlying psychological mechanism ④remain constant even as the specific assets involved change considerably across centuries. Eventually, however, some triggering event, however minor, prompts a portion of investors to reconsider their assumptions, and the resulting wave of selling can ⑤trigger a collapse every bit as rapid and self-reinforcing as the original ascent.

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

Generative AI systems learn to write, draw, and compose by studying ① enormous collections of existing human work, much of which was created without the artists' knowledge or consent. Supporters of the technology argue that this process resembles how a human student learns by studying the masters, ② absorbing style and technique rather than copying specific pieces. Critics respond that the comparison ③ holds up perfectly at scale, since a single AI model can absorb millions of works in days. Courts around the world are now being asked to decide whether training an algorithm on copyrighted material counts as fair use or as ④ infringement. Until clearer rules emerge, artists, developers, and publishers remain locked in a legal ⑤ gray zone that satisfies almost no one.

As more schools shift toward digital textbooks and online assignments, a student without reliable internet access at home faces a disadvantage that has little to do with talent or effort. Some policymakers initially treated internet access as a convenience, comparable to cable television, rather than as infrastructure essential to modern life. That assumption is increasingly being reconsidered, particularly as _______________. Closing this divide will require more than simply distributing devices.

When individuals face uncertainty about how to behave, they frequently look to the actions of others for guidance, assuming that a behavior adopted by many people is more likely to be correct or appropriate than one adopted by few, a tendency known as social proof. Because conformity can substitute for independent judgment so seamlessly, individuals rarely notice when their own decisions have become ___________ rather than genuinely deliberated.

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.

The rejection of unfair offers in the ultimatum game raises an intriguing evolutionary question. (A) One explanation suggests that a willingness to punish unfairness, even at a personal cost, may have conferred long-term advantages within small communities where reputation and repeated interaction mattered greatly. (B) If punishing unfairness is costly in the short term, why would such a tendency have persisted across generations rather than being eliminated by more narrowly self-interested behavior? (C) An individual known to reject unfair offers discourages others from proposing unfair terms in future interactions, ultimately securing fairer treatment over the course of a lifetime.

There is also a quieter cultural cost that rarely appears in productivity reports. Sensors buried in the soil now report moisture levels in real time, drones survey entire fields for signs of disease within minutes, and automated systems adjust irrigation without a farmer ever walking the rows. ( ① ) For large operations with the capital to invest, these tools have measurably increased yields while reducing water waste. ( ② ) Smaller family farms, however, often cannot afford the upfront cost of this equipment. ( ③ ) Some worry that the gap between high-tech and traditional operations will only widen as the technology advances further. ( ④ ) Generations of farming knowledge, passed down through direct observation of soil, weather, and crops, risk being replaced by dashboards and automated alerts. ( ⑤ )