영어 모의고사 (자동 편성)

For most of last year, Junho ①refresh his social media feed constantly, terrified of missing a party, a trending meme, or gossip among his friends. This restless anxiety, ②often called FOMO, or the fear of missing out, left him exhausted and strangely unsatisfied even after hours of scrolling. One weekend, his phone battery died during a hiking trip, and, to his surprise, he actually ③enjoyed the quiet afternoon without notifications interrupting his thoughts. Curious about this unexpected calm, Junho began ④deleting social apps for a few hours each day, gradually extending the breaks as weeks passed. Instead of dreading what he might be missing, he started noticing small pleasures, such as finishing a book or ⑤having an uninterrupted conversation with his family.

When I told my parents I wanted to become a musician, I ①expected them to worry about money and stability. Instead, my father surprised me by ②ask what kind of music made me feel most alive. My mother, ③who had once dreamed of becoming a painter herself, admitted that she still wondered what her life might have looked like. Their honesty made me realize that parents' influence on career choices ④is not always about pressure or control. Their trust gave me the courage ⑤to keep pursuing music seriously.

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.

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.

When engineers design the software that controls a self-driving car, they face a question philosophers have debated for decades: should a crashing vehicle protect its own passenger, or minimize total harm even at the passenger's expense? Surveys reveal an uncomfortable 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 suggests that _______________. Manufacturers, regulators, and philosophers must instead agree on transparent rules before autonomous vehicles are allowed to make such decisions.

Facial recognition software has moved rapidly from airport security lines into shopping malls, schools, and even private apartment buildings. (A) Independent studies, however, have repeatedly found that many commercial systems perform less accurately on women and people with darker skin tones. (B) Proponents note that the technology can unlock doors, catch shoplifters, and speed up identity checks far faster than any human guard could manage. (C) Several cities have already reported cases in which an innocent person was detained based on a flawed match.

Blockchain technology was originally promoted as a way to remove the need for trusted middlemen, allowing strangers to exchange value directly through a shared, tamper-resistant ledger. (A) In practice, however, a small number of large players have come to dominate many blockchain networks, controlling enough power to influence outcomes that were supposed to be decided collectively. (B) In theory, this design distributes power away from any single institution and toward the network as a whole. (C) Critics note a further irony: when something goes wrong, there is often no institution left to appeal to, since the system was designed to eliminate central authority.

Millions of people now wear devices that continuously track their heart rate, sleep patterns, and daily activity, generating an intimate stream of health data. (A) In practice, however, the terms of service that few people read often grant the manufacturer broad rights to store, analyze, and even sell anonymized versions of that data. (B) Users generally assume this information belongs to them, since it is drawn directly from their own bodies. (C) This arrangement becomes especially troubling when health data influences decisions far beyond fitness, such as insurance premiums or employment screening.

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 )

The software company, in turn, may argue that no algorithm can be expected to be perfect. Hospitals are increasingly adopting artificial intelligence tools that can scan medical images and flag potential tumors faster than experienced radiologists. ( ① ) When an AI system misses a diagnosis that a human doctor would likely have caught, responsibility becomes difficult to assign. ( ② ) The doctor may argue that they simply trusted a tool the hospital required them to use. ( ③ ) The hospital, meanwhile, may argue that the software company guaranteed its accuracy. ( ④ ) Until legal systems clarify this chain of responsibility, patients harmed by an algorithmic error may find themselves with no clear party to hold accountable. ( ⑤ )