영어 모의고사 (자동 편성)

City governments increasingly market dense networks of surveillance cameras as a straightforward safety upgrade, ①promising faster emergency response and lower crime rates. In many cases, the technology delivers exactly what it promises, ②helping investigators identify suspects within hours rather than weeks. Yet the same infrastructure that catches criminals also creates a permanent record of where ordinary, law-abiding citizens ③go about their daily lives. Once a camera network exists, its purpose can quietly expand, often without new public debate or explicit approval. Civil liberties groups argue that a city should decide how much surveillance it wants before the cameras go up, not years afterward when the infrastructure ④is already impossible removing. Convenience installed today, in other words, can quietly ⑤become control tomorrow.

When people estimate the value of an unfamiliar product, they rarely rely on objective calculation alone; instead, they anchor their judgment to whatever numerical reference happens to be presented first, however ①arbitrary that number may be. This phenomenon exerts a ②disproportionate influence on price perception precisely because initial figures function as a kind of cognitive gravity that subsequent estimates struggle to escape. A shopper who first sees a jacket listed at $300 before it is marked down to $150 will likely judge the discounted price as an excellent ③bargain, regardless of whether $150 actually reflects the jacket's true worth. Retailers, well aware of this bias, frequently display a ④deflated "original price" beside a discounted one, not because the higher figure is meaningful, but because it recalibrates customers' expectations. Even professionals are not immune: negotiators who open with an extreme initial offer often secure more ⑤favorable final terms than those who begin with a moderate one.

Individuals confronted with a set of options frequently default to whichever alternative requires no active decision at all. Decision-makers often treat the current arrangement as a reasonable ①baseline simply because it already exists, even when switching would plainly serve their interests better. When employees must actively opt into a retirement savings plan, participation rates remain stubbornly ②low; yet when the same plan is presented as automatic unless an employee opts out, participation rises ③dramatically, despite the fact that the underlying financial terms are identical in both cases. Two forces appear to drive this asymmetry: first, the cognitive effort required to evaluate alternatives and initiate change, and second, an aversion to the potential regret that might follow an active decision that turns out poorly. Because inaction carries no such vivid regret, the status quo comes to feel ④riskier than it objectively is, illustrating how mere inertia can ⑤masquerade as a deliberate preference.

When people look back on a multi-day journey, they ①rarely recall every hour with equal clarity; instead, memory tends to compress the entire experience into just a few representative moments. Psychologists have found that two points carry ②disproportionate weight in this process: the single moment when emotion, whether joy or discomfort, reached its highest intensity, and whatever happened right before the experience concluded. Consider two hikers who complete an identical five-day trek. The first finishes with a ③grueling, rain-soaked final climb, while the second enjoys a calm, scenic descent on the last afternoon despite having endured an equally difficult ascent earlier in the trip. Even though both hikers faced comparable hardship overall, the second is far ④less likely to remember the journey fondly, simply because the trip ended pleasantly. This pattern reveals that overall satisfaction is not calculated as an average of every experienced moment; rather, it is shaped disproportionately by whichever moments felt most ⑤intense and by however the experience happened to end.

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.

Facing a shortage of caregivers and a rapidly aging population, several countries have begun deploying robots designed to remind elderly residents to take medication and offer simple conversation. Early trials show that many residents report reduced loneliness, particularly when a robot's presence allows a human staff member to spend more time with each patient. Critics, however, worry that _______________, especially in facilities already struggling with tight budgets.

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.

Few of these later buyers, however, possess any independent basis for judging whether the asset's price still bears any relation to its underlying value. A speculative bubble typically begins with a genuine, defensible reason for optimism, such as a promising new technology or an unusually favorable economic environment. ( ① ) Early investors who recognize this genuine opportunity purchase the asset and, as expected, often see its price rise accordingly. ( ② ) As word of these early gains spreads, a second wave of investors enters the market, drawn less by independent analysis than by the simple observation that the price has already climbed. ( ③ ) They are, in effect, purchasing confidence rather than value, trusting that the crowd's continued enthusiasm will sustain or further elevate the price. ( ④ ) This reliance on collective momentum rather than fundamental analysis is precisely what transforms a reasonable initial rally into an unsustainable bubble. ( ⑤ ) When the momentum eventually falters, as it inevitably must, the absence of any solid fundamental foundation leaves the price with nothing to support it.

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 )

At that distant point in time, the future increase feels almost costless, since no immediate sacrifice is required. One practical application of hyperbolic discounting involves a savings program that gradually raises an employee's contribution rate over several years. ( ① ) Employees are first asked to commit, well in advance, to increasing their savings rate at a specific future date, often timed to coincide with an expected salary raise. ( ② ) Because the commitment applies only to a point far in the future, the vast majority of employees readily agree to the plan. ( ③ ) When the scheduled date finally arrives, the increase takes effect automatically unless the employee actively opts out, and remarkably few do. ( ④ ) The program succeeds precisely because it separates the decision from the discomfort, asking employees to commit when the cost feels abstract rather than immediate. ( ⑤ ) In this way, a well-timed program can help individuals overcome the very bias that would otherwise prevent them from saving adequately for the future.