영어 모의고사 (자동 편성)

Few ideas in policy debate ①provoke as much philosophical unease as the notion that a government might deliberately steer citizens toward better choices while leaving every option technically available. Defenders insist that freedom is preserved as long as no option is banned and no penalty is attached, ②arguing that a citizen who is merely steered, rather than coerced, remains free to choose otherwise. Critics counter that this defense rests on an impoverished notion of liberty, one that ③ignores how engineered defaults and calculated framing can shape decisions just as powerfully as an outright prohibition would. If a policy is designed because officials expect it to bypass conscious deliberation, these critics ask, can the resulting choice still ④call autonomous, even though no law was broken? The dispute ultimately turns on what freedom actually ⑤requires: the mere absence of coercion, or a decision-making process that remains transparent and undistorted.

Beyond restoring lost function, engineers are now exploring implants and prosthetics designed to give healthy people abilities beyond ordinary human limits, from night vision to reaction times faster than any athlete could achieve through training alone. Supporters frame this as simply the next step in a long history of human enhancement, ①no different in principle from eyeglasses or vaccines, only more direct. Critics counter that earlier enhancements were broadly available to anyone regardless of wealth, while cutting-edge neural and physical implants are likely to remain ②expensive for decades, potentially splitting society into those who can afford enhancement and those who cannot. If such a divide hardens, competitive advantages in school, sports, and the workplace could come to depend ③less on effort than on access to capital. What began as a medical tool for restoring what was lost, in other words, may end up ④preserving the baseline of what counts as an ordinary human being, keeping the definition of "normal" ⑤unchanged for future generations.

Social media platforms rarely show users a neutral stream of information. Instead, recommendation algorithms are ①optimized to maximize engagement, and content that provokes strong emotion, particularly outrage, tends to hold attention longer than balanced reporting ever could. Over time, users exposed to a steady diet of emotionally charged content may come to believe that extreme opinions are far more ②common than they actually are, simply because those opinions dominate their feed. Researchers describe this as a ③distorted mirror: the platform reflects not society as it truly is, but a version shaped by whatever keeps people scrolling. Some platforms have experimented with reducing the visibility of outrage-driven content, only to see user engagement ④drop, which reveals an uncomfortable truth about the underlying business model. This ⑤confirms that emotionally extreme content plays little role in keeping the platform profitable.

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

Traditional industrial systems have relied on a linear model of production, in which raw materials are extracted, transformed into goods, and eventually discarded as waste. This approach treats natural resources as if unlimited and disposal as if costless. A circular economy proposes an alternative framework in which _______________, thereby reducing the extraction of virgin resources. Central to this model is the notion that waste, rather than being an inevitable byproduct, can be redesigned as a resource for another process, much as fallen leaves nourish the trees that shed them. For example, manufacturers design products so that components can be disassembled and reused in new items once their original function ends. Some companies also lease equipment instead of selling it outright, retaining responsibility for refurbishment. Because such practices lessen dependence on finite raw materials, they reduce the environmental damage caused by mining. Consequently, the circular economy is increasingly regarded as a viable economic strategy that conserves resources for future generations.

Every time a smartphone connects to a network, it records a data point that can later map where its owner has been. The real danger emerges when location data from multiple sources is combined. Companies often argue that anonymized data cannot be traced back to individuals, yet researchers have repeatedly shown that _______________. As a result, privacy experts increasingly insist that location data deserves the same legal protection as medical records.

Imagine watching a fair coin land on heads five times in a row and feeling an increasingly strong intuition that the next flip is somehow due to produce tails. (A) This intuition, though psychologically compelling, rests on a basic misunderstanding of probability, since each flip of a fair coin remains entirely independent of every flip that came before it. (B) The coin possesses no memory of its previous outcomes, and its probability of landing on tails on the sixth flip stays fixed at fifty percent regardless of how many heads preceded it. (C) Casinos have long profited from this misconception, watching gamblers place larger bets after a losing streak simply because they mistakenly believe that a win has become statistically overdue.

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 )

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

Their actual forecasting accuracy, however, has repeatedly proven no better than that of far less experienced participants, and sometimes even worse. Overconfidence among financial professionals presents a puzzling contradiction. ( ① ) Fund managers and analysts typically possess years of specialized training, access to vast quantities of market data, and considerable professional experience. ( ② ) One might reasonably expect such expertise to translate into consistently superior predictions about future market movements. ( ③ ) Longitudinal studies tracking professional forecasts against actual outcomes reveal a persistent gap between confidence and accuracy. ( ④ ) This finding does not imply that expertise is worthless, but it does suggest that expertise can inflate confidence more readily than it improves genuine predictive accuracy. ( ⑤ ) Investors would therefore do well to treat confident predictions, however credentialed their source, with a healthy measure of skepticism.