hce_cmu
115年
英文
第 37 題
📖 題組：
In contemporary higher education, the discourse surrounding generative artificial intelligence (AI) has largely coalesced around a set of comforting metaphors. University policies and academic handbooks frequently characterize AI as a “tool,” a “tutor,” or a “helpful assistant.” While these descriptors aim to provide pragmatic clarity, they are far from neutral. Instead, these metaphors exert a profound, often invisible, influence on how educators and students conceptualize the technology’s role in the cultivation of critical thinking. The cognitive power of metaphors is well-documented. A landmark study by Stanford psychologists Paul Thibodeau and Lera Boroditsky demonstrated that framing crime as either a “beast” or a “plague” significantly altered the solutions participants proposed—steering them toward either punitive measures or social reform, respectively. Crucially, participants remained largely unaware of the metaphor’s influence, instead attributing their decisions to raw statistics. Similarly, viewing AI as a “tool” implies a degree of moral neutrality and human agency; much like a hammer, the responsibility for its effects is placed squarely on the user. This perspective, however, obscures the ways in which AI systems actively shape interpretations and manipulate judgment, potentially undermining the intellectual habits academics seek to foster. The “assistant” metaphor further complicates the pedagogical landscape by suggesting a clear hierarchy where the human remains in control. This narrative masks the emergence of a “second hidden curriculum,” wherein AI does not merely assist but actively directs learning by structuring explanations and modeling specific cognitive pathways. When AI is anthropomorphized—attributed human qualities like “going rogue” or being “racist”—it further dilutes accountability. Such language allows users to look away from the institutional and corporate biases embedded within the algorithms, leading to a drift in moral responsibility. To counteract these cognitive distortions, some scholars suggest a transition from convenient metaphors to disciplined, technical vocabulary. Rather than “brainstorming with AI,” users should recognize the process as “engaging in probabilistic text generation” under specific algorithmic constraints. Shifting from the concept of “hallucinations” to “predictive text failure” transforms verification from an optional task into a fundamental academic practice. Ultimately, by stripping away misleading metaphors and insisting on technical precision, the academic community can better maintain moral responsibility and pedagogical integrity, ensuring that the development of thought remains a distinctly human endeavor.
In contemporary higher education, the discourse surrounding generative artificial intelligence (AI) has largely coalesced around a set of comforting metaphors. University policies and academic handbooks frequently characterize AI as a “tool,” a “tutor,” or a “helpful assistant.” While these descriptors aim to provide pragmatic clarity, they are far from neutral. Instead, these metaphors exert a profound, often invisible, influence on how educators and students conceptualize the technology’s role in the cultivation of critical thinking. The cognitive power of metaphors is well-documented. A landmark study by Stanford psychologists Paul Thibodeau and Lera Boroditsky demonstrated that framing crime as either a “beast” or a “plague” significantly altered the solutions participants proposed—steering them toward either punitive measures or social reform, respectively. Crucially, participants remained largely unaware of the metaphor’s influence, instead attributing their decisions to raw statistics. Similarly, viewing AI as a “tool” implies a degree of moral neutrality and human agency; much like a hammer, the responsibility for its effects is placed squarely on the user. This perspective, however, obscures the ways in which AI systems actively shape interpretations and manipulate judgment, potentially undermining the intellectual habits academics seek to foster. The “assistant” metaphor further complicates the pedagogical landscape by suggesting a clear hierarchy where the human remains in control. This narrative masks the emergence of a “second hidden curriculum,” wherein AI does not merely assist but actively directs learning by structuring explanations and modeling specific cognitive pathways. When AI is anthropomorphized—attributed human qualities like “going rogue” or being “racist”—it further dilutes accountability. Such language allows users to look away from the institutional and corporate biases embedded within the algorithms, leading to a drift in moral responsibility. To counteract these cognitive distortions, some scholars suggest a transition from convenient metaphors to disciplined, technical vocabulary. Rather than “brainstorming with AI,” users should recognize the process as “engaging in probabilistic text generation” under specific algorithmic constraints. Shifting from the concept of “hallucinations” to “predictive text failure” transforms verification from an optional task into a fundamental academic practice. Ultimately, by stripping away misleading metaphors and insisting on technical precision, the academic community can better maintain moral responsibility and pedagogical integrity, ensuring that the development of thought remains a distinctly human endeavor.
Why does the author mention the study by Paul Thibodeau and Lera Boroditsky?
- A To indicate that metaphors can manipulate human problem-solving and decision-making.
- B To argue that crime in cities is subjected to either punishment or reform.
- C To show that psychologists are more qualified than computer scientists to discuss AI.
- D To illustrate that the use of “beast” metaphor is better than the “plague” metaphor.
思路引導 VIP
如果一位作家在討論「科技標籤」的嚴肅文章中，突然插入一個關於「犯罪心理實驗」的故事，你認為這個故事的主要目的是在介紹犯罪知識，還是為了向讀者證明「特定措辭」對人類思考模式的影響力呢？
🤖
AI 詳解
AI 專屬家教
恭喜你精準地掌握了文章的邏輯架構！這題考查的是讀者能否區分「論點」與「證據」之間的關聯。你選對了 (A)，代表你成功看穿了作者引用這項心理學研究的真實用意。
隱喻的力量：從犯罪研究到人工智慧
在文章第二段，作者提到史丹佛大學的研究，指出將犯罪形容為「野獸」或「瘟疫」會影響人們提出的對策。作者並非真的要討論犯罪問題，而是藉由這個具體的實驗數據，來驗證（Verify）隱喻如何在你我察覺不到的情況下，悄悄地操控（Manipulate）我們的決策與判斷。這為後文鋪路：如果隱喻能改變我們對犯罪的態度，那麼稱 AI 為「工具」或「助手」自然也會形塑我們對科技責任的看法。
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