영어 모의고사 (자동 편성)

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

When engineers design the software ①that 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 ②minimizing 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 ③they 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 ④be settled by public opinion alone. Manufacturers, regulators, and philosophers must instead agree on transparent rules before autonomous vehicles ⑤are allowed to make such decisions on the road.

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

As private companies develop the technology to mine asteroids for rare metals and water, a legal question once confined to science fiction has suddenly become ①urgent: who, if anyone, owns the resources of outer space? Existing international treaties state that no nation may claim sovereignty over celestial bodies, but they say remarkably ②little about whether a private company may extract and sell what it finds there. Some governments have already passed domestic laws granting their own companies rights to material mined in space, a move that other nations view as a ③collective attempt to settle a question that should be decided collectively. Supporters of space mining argue that new resources could ④ease shortages on Earth and fund further exploration, while critics ⑤warn that treating space as an open frontier for extraction risks repeating the same mistakes that colonization caused on Earth.

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 ①unlimited and disposal as if costless. A circular economy proposes an alternative framework in which materials are kept in continuous use through reuse, repair, and recycling, thereby ②reducing 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 ③increase the environmental damage caused by mining. Consequently, the circular economy is increasingly regarded as a ④viable economic strategy that ⑤conserves resources for future generations.

Hospitals are increasingly adopting artificial intelligence tools that can scan medical images and flag potential tumors ①faster 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 have only begun to address. When an AI system misses a diagnosis that a human doctor would likely have caught, responsibility becomes ②easy to assign. The doctor may argue that they simply trusted a tool the hospital 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 be expected to be ③perfect. Until legal systems ④clarify this chain of responsibility, patients harmed by an algorithmic error may find themselves with no clear party to hold ⑤accountable.

Cognitive load theory begins from the premise that working memory, the mental workspace in which incoming information is temporarily held and manipulated, _______________, in stark contrast to the comparatively vast capacity of long-term memory. When instructional materials introduce more interacting elements than this narrow workspace can simultaneously process, learners experience what theorists call cognitive overload, a condition under which comprehension deteriorates and errors multiply regardless of how motivated the learner might be. Because much of this burden arises not from the intrinsic difficulty of the subject matter itself but from the manner in which information is presented, instructional designers can substantially reduce unnecessary strain by eliminating redundant explanations, aligning visual and verbal elements so that learners need not mentally integrate scattered sources, and gradually withdrawing guidance as competence develops. Ignoring these principles, by contrast, risks overwhelming novices with demands that exceed their processing capacity, however well-organized the underlying content may be.

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. This tendency, known as overconfidence bias, leads investors to trade more frequently than a more cautious assessment of their own skill would justify. Paradoxically, then, the very confidence that motivates investors to act decisively often undermines the outcomes they are trying to achieve, since ___________ frequently produces worse results than a more modest, diversified strategy.

Convenience installed today, in other words, can quietly become control tomorrow. City governments increasingly market dense networks of surveillance cameras as a straightforward safety upgrade, promising faster emergency response and lower crime rates. ( ① ) In many cases, the technology delivers exactly what it promises, helping investigators identify suspects within hours rather than weeks. ( ② ) Yet the same infrastructure that catches criminals also creates a permanent record of where ordinary, law-abiding citizens go about their daily lives. ( ③ ) Once a camera network exists, its purpose can quietly expand, often without new public debate or explicit approval. ( ④ ) 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 is already impossible to remove. ( ⑤ )

Until clearer rules emerge, artists, developers, and publishers remain locked in a legal gray zone that satisfies almost no one. Generative AI systems learn to write, draw, and compose by studying enormous collections of existing human work, much of which was created without the artists' knowledge or consent. ( ① ) Supporters of the technology argue that this process resembles how a human student learns by studying the masters. ( ② ) Critics respond that the comparison breaks down at scale, since a single AI model can absorb millions of works in days. ( ③ ) Courts around the world are now being asked to decide whether training an algorithm on copyrighted material counts as fair use or as infringement. ( ④ ) This is a question the law was never designed to answer. ( ⑤ )