영어 모의고사 (자동 편성)

Last spring, I ①joined a one-day job experience program at a local hospital. I had always been curious about becoming a nurse, so I signed up without hesitation. A kind nurse ②named Ms. Park showed me around the ward, ③explaining how nurses check patients' conditions. At first, I was nervous about talking to real patients. However, after ④help an elderly patient find her room, I felt proud and relaxed. I realized that teamwork ⑤matters as much as medical knowledge.

Hospitals are increasingly adopting artificial intelligence tools that can scan medical images and flag potential tumors faster and, in some trials, more accurately than experienced radiologists. Patients understandably welcome any technology that catches disease earlier, yet the growing reliance on these tools raises an uncomfortable legal question that hospitals ① have only begun to address. When an AI system misses a diagnosis that a human doctor would likely ② have caught, responsibility becomes difficult to assign. The doctor may argue that they simply trusted a tool the hospital ③ required them to use, the hospital may argue that the software company guaranteed its accuracy, and the software company may argue that no algorithm can ④ expect to be perfect. Until legal systems clarify this chain of responsibility, patients harmed by an algorithmic error may find themselves with no clear party ⑤ to hold accountable.

When engineers design the software ① that controls a self-driving car, they inevitably face a question that philosophers have debated for decades. If a crash becomes unavoidable, should the vehicle protect its own passenger at all costs, or should it be programmed ② minimizing total harm, even if that means steering toward the person inside? 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 ③ 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 ④ be settled by public opinion alone. Manufacturers, regulators, and philosophers must instead agree on transparent rules before autonomous vehicles ⑤ are allowed 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.

The gig economy has grown ①rapidly over the past decade, as digital platforms connect customers directly with independent workers. This model offers clear advantages: workers can choose when and how much they work, providing valuable ②rigidity that traditional employment rarely allows. However, gig workers often ③lack benefits such as health insurance and paid leave, which full-time employees typically receive. Because their income can ④fluctuate sharply from month to month, many gig workers struggle to plan their finances confidently. Governments therefore face growing pressure to ⑤protect independent workers through new policies.

Few ideas in policy debate provoke 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. Critics counter that this defense rests on an impoverished notion of liberty, one that ignores how _______________. The dispute ultimately turns on what freedom actually requires: the mere absence of coercion, or a decision-making process that remains transparent and undistorted.

The discovery of CRISPR gene-editing technology gave scientists a tool precise enough to correct a single mistaken letter in the human genome. Yet editing a gene in a sperm, egg, or early embryo does not simply change one patient; it alters the genetic code passed down to every future generation. Scientific organizations around the world have therefore drawn a careful line, permitting gene editing to treat disease in existing patients while banning any edit that would be inherited by their descendants. Critics worry, however, that _______________.

City governments increasingly market dense networks of surveillance cameras as a straightforward safety upgrade, promising faster emergency response and lower crime rates. (A) Yet the same infrastructure that catches criminals also creates a permanent record of where ordinary, law-abiding citizens go about their daily lives. (B) In many cases, the technology delivers exactly what it promises, helping investigators identify suspects within hours rather than weeks. (C) Once a camera network exists, its purpose can quietly expand, from tracking traffic accidents to monitoring political protests, often without new public debate.

주어진 문장: Because the number of likes a post will receive is never guaranteed, every notification carries a small element of suspense. Psychologists have long studied a mechanism called the variable reward schedule, in which rewards arrive unpredictably rather than after every single action. ( ① ) Slot machines famously exploit this principle, and social media notifications operate on strikingly similar logic. ( ② ) When someone posts a photo, they cannot predict exactly when likes will appear, nor how many they will eventually receive. ( ③ ) This uncertainty triggers a small burst of dopamine each time the phone is checked, regardless of whether the result is disappointing or thrilling. ( ④ ) Consequently, users often refresh their feeds compulsively, hoping the next check will finally bring a satisfying reward. ( ⑤ ) What makes this troubling is that technology companies deliberately designed notification systems using insights borrowed from gambling research, rather than stumbling upon them by accident. Such practices raise serious ethical questions about manipulating users' brains for profit. Therefore, people must consciously recognize this hidden mechanism and set firm limits on their checking habits.

This small difference in preparation determines whether an item can be reused or simply thrown away as waste. Sorting your trash correctly is one of the simplest habits that protect our environment. ① When you separate paper, plastic, glass, and cans, recycling centers can process each material more efficiently. ② For example, plastic bottles should be rinsed and have their caps removed before being thrown away. Paper soaked with food or oil, however, cannot be recycled and must go into general waste. ③ Sorting garbage is similar to organizing a closet, where each type of clothing has its own shelf. If items are mixed together carelessly, finding what you need later becomes difficult. ④ Likewise, mixing recyclables with ordinary trash makes the whole recycling process complicated. Many students believe that sorting trash takes too much time, but it actually requires only a few extra seconds. ⑤ Therefore, learning these basic rules now helps you build a habit that benefits your entire community.