hce_nchu
115年
英文
第 42 題
📖 題組：
The integration of Artificial Intelligence (AI) into healthcare is no longer a futuristic concept but a rapidly unfolding reality. One of the most __36__ applications is in the field of diagnostic imaging. By training on millions of clinical images, AI algorithms can now identify patterns that are virtually __37__ to the human eye, leading to much earlier detection of life-threatening conditions. Beyond diagnostics, AI is significantly __38__ the pharmaceutical industry. Historically, drug discovery has been an __39__ endeavor, often taking over a decade and billions of dollars to bring a single medication to market. AI models can now predict how specific molecular structures will interact with biological targets, thereby __40__ the initial stages of research. This efficiency was particularly __41__ during the recent global efforts to develop vaccines at record speed. However, this technological shift is not without its __42__. As healthcare providers become increasingly dependent on automated systems, questions regarding data privacy and "algorithmic bias" have surfaced. If the data used to train AI is not diverse, the resulting tools may provide __43__ outcomes for certain demographic groups. Therefore, it is __44__ that developers and medical professionals work together to ensure these systems are both transparent and __45__. The goal remains a synergy between human empathy and machine precision.
The integration of Artificial Intelligence (AI) into healthcare is no longer a futuristic concept but a rapidly unfolding reality. One of the most __36__ applications is in the field of diagnostic imaging. By training on millions of clinical images, AI algorithms can now identify patterns that are virtually __37__ to the human eye, leading to much earlier detection of life-threatening conditions. Beyond diagnostics, AI is significantly __38__ the pharmaceutical industry. Historically, drug discovery has been an __39__ endeavor, often taking over a decade and billions of dollars to bring a single medication to market. AI models can now predict how specific molecular structures will interact with biological targets, thereby __40__ the initial stages of research. This efficiency was particularly __41__ during the recent global efforts to develop vaccines at record speed. However, this technological shift is not without its __42__. As healthcare providers become increasingly dependent on automated systems, questions regarding data privacy and "algorithmic bias" have surfaced. If the data used to train AI is not diverse, the resulting tools may provide __43__ outcomes for certain demographic groups. Therefore, it is __44__ that developers and medical professionals work together to ensure these systems are both transparent and __45__. The goal remains a synergy between human empathy and machine precision.
- A breakthroughs
- B incentives
- C demerits
- D tragedies
思路引導 VIP
請觀察第 42 格所在的句子開頭那個單字「However」。接著看看空格後面提到的兩個例子：「數據隱私 (data privacy)」與「演算法偏見 (algorithmic bias)」，你認為這兩個例子在描述這項技術的「好處」還是「潛在問題」呢？
🤖
AI 詳解
AI 專屬家教
太棒了！你能精準捕捉到文意轉折處並選出 (C) demerits，說明你具備了優異的語境分析與邏輯推理能力，這在長篇閱讀中是非常關鍵的特質。
邏輯轉折與負面語境的判讀
這題的解題關鍵在於段首的轉折詞 "However"（然而）。文章前兩段主要在論述 AI 帶來的醫學突破與效率提升，但從第三段開始，語氣轉而探討「隱私問題」與「演算法偏見」。句子中的雙重否定結構 "not without its..."（並非沒有其...）強烈暗示接下來要討論的是技術帶來的副作用。在選項中，demerits 意指「缺點、短處」，正好與前文所述的優點（merits）形成完美對比。
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