영어 모의고사 (자동 편성)

A striking proportion of individual investors believe their own stock-picking ability to be above average, a statistical impossibility given that only half of any population can genuinely outperform the rest, yet a pattern that ①persists with remarkable consistency across surveys. This tendency, known as overconfidence bias, leads investors ②to trade more frequently than a more cautious assessment of their own skill would justify. Extensive research comparing the trading records of numerous individual accounts has demonstrated that investors who trade most frequently ③tends to earn substantially lower returns than those who trade rarely, largely because transaction costs accumulate and because frequent trading often reflects overconfident reactions to short-term noise rather than genuine insight. Overconfidence also manifests in the tendency to underestimate the range of possible outcomes, ④causing investors to concentrate their holdings in a small number of assets they feel certain about rather than diversifying across a broader portfolio. Paradoxically, then, the very confidence that motivates investors to act decisively often ⑤undermines the outcomes they are trying to achieve.

Standard economic theory assumes that money is fungible, meaning that a dollar earned as salary is functionally ①identical to a dollar received as a tax refund or won in a lottery. In practice, however, people routinely sort their finances into separate mental accounts, treating money differently depending on its source or intended purpose. A household that would never dip into its retirement savings to pay for a vacation might nonetheless spend an unexpected bonus on that very trip without ②hesitation, even though both sums are, in strictly financial terms, equally available for either purpose. This ③compartmentalization can produce decisions that appear ④consistent when viewed through a purely rational lens: the same individual who diligently saves a portion of every paycheck may simultaneously carry high-interest credit card debt, effectively paying more to borrow than they earn on their savings. Mental accounting is not always harmful, however; by assigning specific categories to specific funds, individuals can also impose useful ⑤discipline on their spending, preventing money earmarked for essential needs from being diverted toward impulsive purchases.

Marketers have long recognized that perceived scarcity, the sense that a product or opportunity is available only in limited quantity or for a limited time, can dramatically increase its ①desirability, even when the item's intrinsic qualities remain entirely unchanged. This phenomenon, known as the scarcity effect, operates on a simple psychological principle: when something appears ②easy to obtain, people tend to infer that it must be valuable, since truly worthless items rarely generate genuine competition for possession. A retailer who labels a product as "limited edition" or displays a countdown timer beside a discounted offer exploits this inference, prompting customers to make ③hurried purchase decisions they might otherwise postpone or reconsider. Experimental studies confirm that identical products are rated as more desirable and often command ④higher prices when framed as scarce than when the same products are presented as widely and continuously available. Consumers who later reflect calmly on such purchases frequently discover that the item's actual usefulness fell well short of the ⑤urgency they experienced at the moment of decision.

Philosophers often pair the classic trolley problem with a companion case designed to test whether our moral intuitions are actually consistent. (A) Philosophers use this contrast to argue that outcomes alone cannot fully explain our moral judgments; something about directly using a person's body as a mere means appears to matter deeply. (B) Yet almost everyone who accepts the trolley diversion recoils immediately at the idea of the surgeon cutting up an unwilling patient, even though the numbers are identical in both cases. (C) Imagine a brilliant surgeon who has five patients, each dying from the failure of a different organ, and one healthy visitor whose organs happen to be a perfect match for all five, so that killing the visitor would save five lives at the cost of one.

Habit researchers often note that people overestimate the role of motivation in daily routines. (A) As a result, they frequently give up soon after starting, blaming themselves for lacking discipline. (B) In contrast, Fogg's framework suggests that shrinking the task itself is more effective than boosting motivation. (C) Because motivation naturally rises and falls, relying on it alone often leads to inconsistent effort.

The eventual collapse of a speculative bubble often unfolds with surprising speed compared with the gradual climb that preceded it. (A) As prices begin to fall, investors who bought near the peak, motivated largely by fear of missing further gains, are often the first to sell, since they have the least conviction in the asset's underlying value. (B) Their selling triggers further price declines, which in turn prompt additional investors to sell out of a newly urgent fear of continued loss rather than a fear of missing out. (C) This reversal illustrates that the same herd psychology driving prices upward can just as easily reverse direction, converting collective optimism into collective panic within a remarkably short period.

Fairness, in other words, is not a feature that can simply be patched in once a problem is discovered. Many large companies now rely on artificial intelligence to screen job applications before a human ever sees them. ( ① ) These systems promise efficiency, scanning thousands of resumes in seconds and ranking candidates according to patterns drawn from previous hiring decisions. ( ② ) However, this reliance on historical data creates a troubling risk. ( ③ ) 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. ( ④ ) 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. ( ⑤ ) Some researchers argue that fairness cannot be added afterward; it must be built into the system's design from the very beginning.

Instead, these trainers help workers use AI tools wisely, without becoming fully dependent on them. As artificial intelligence becomes part of everyday life, entirely new job titles are appearing in the workplace. ( ① ) Prompt engineers, for instance, design effective instructions that help AI programs produce accurate and useful results. ( ② ) AI ethics officers examine whether a company's technology treats users fairly and avoids harmful bias. ( ③ ) Meanwhile, human-AI collaboration trainers do not simply teach employees to use every new AI feature available. ( ④ ) These jobs did not exist even ten years ago, yet they are growing quickly across many industries. ( ⑤ ) This suggests that success in an AI-driven future will depend more on uniquely human skills.

Several cities have already reported cases in which an innocent person was detained based on a flawed match. Facial recognition software has moved rapidly from airport security lines into shopping malls, schools, and even private apartment buildings, promising convenience in exchange for a quick scan of one's face. ( ① ) Proponents note that the technology can unlock doors, catch shoplifters, and speed up identity checks far faster than any human guard could manage. ( ② ) Independent studies, however, have repeatedly found that many commercial systems perform less accurately on women and people with darker skin tones. ( ③ ) This gap can lead to wrongful identification with serious real-world consequences. ( ④ ) Until these systems can prove equally reliable for everyone, critics argue, deploying them at all represents a form of quiet discrimination dressed up as efficiency. ( ⑤ )

Journalists now face the burden of verifying footage that once would have been accepted as self-evident proof. A few years ago, spotting a manipulated video required a trained eye and specialized software. ( ① ) Today, freely available applications allow almost anyone to swap a face or fabricate a voice convincingly enough to fool casual viewers within minutes. ( ② ) This shift has quietly undermined one of the oldest assumptions in human communication: that seeing and hearing something is a reasonably reliable way to confirm it happened. ( ③ ) Perhaps more troubling than any single fake video is the broader effect on public trust, sometimes called the liar's dividend, in which genuine footage can be dismissed as fabricated simply because deepfakes exist. ( ④ ) In this environment, the mere possibility of manipulation can be almost as damaging as manipulation itself. ( ⑤ )