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The humanities, not Big Tech, are uniquely positioned to lead the public in critically understanding, contextualizing, and ethically regulating so-called “AI” (large language models), thereby safeguarding critical thinking, authentic writing, and democratic discourse.

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“AI” / Large Language Models (LLMs): Refers to technologies like ChatGPT; They are the statistical model, not the true intelligence

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Humanities / Humanists: Encompasses fields like literature, composition, and critical thinking; positioned as "domain experts" who emphasize process, context, and ethics.

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Disruption: The type of "disruption" championed by tech giants (commercial, profit-driven) is contrasted with the critical, humanistic "disruption" that serves the public good.

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Surveillance Capitalism: The political-economic model underpinning "AI" development, reliant on data exploitation and monopolized resources.

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Today's “AI” is not intelligent but a resource-intensive statistical model, and its anthropomorphism is a result of marketing hype.

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LLMs like ChatGPT are fundamentally flawed, posing risks to reliable knowledge and democratic discourse.

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The push to integrate “AI” into education misunderstands and undermines the purpose of writing and learning.

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Humanists are the ideal “domain experts” to guide the public and regulate “AI” because they teach critical thinking, contextual analysis, and ethical communication.

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A toddler learns contextually with minimal data, while AI requires massive datasets and computing power.

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The term “AI” was rebranded from the more humble “machine learning” to attract investment.

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They “hallucinate” facts, perpetuate biases from training data, and produce simplistic, derivative text.

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Efforts to “detoxify” them create a “mouth on a leash” that avoids controversy but cannot grasp truth.

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Writing is a “frictional” process of thinking, research, and revision, not a transaction for a grade.

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Using AI for first drafts short-circuits a student’s own idea development.

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They are already acting: NYC schools banned ChatGPT, MLA/CCCC task forces are forming guidelines, faculty are sharing pedagogical strategies.

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They contextualize technology within history, power structures (e.g., racial bias, surveillance capitalism), and environmental costs.

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Public discourse is misled, creating false hopes and fears. This misrepresentation must be corrected.

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They are tools for “anti-thought” that could degrade public discourse and enable automated misinformation.

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Education must resist techno-solutionism that prioritizes efficiency over critical engagement.

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The humanities provide the essential critical framework to demand accountability, transparency, and regulation from tech companies.

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The article "Now the Humanities Can Disrupt 'AI'" by Lauren M. E. Goodlad and Samuel Baker presents a compelling argument that the humanities can play a leading role in regulating large language models, such as ChatGPT. The authors' central claim is that the humanities, with their deep expertise in critical thinking, writing, and ethical reasoning, are uniquely positioned to counter the marketing hype surrounding "AI" and guide the public in understanding its capabilities and perils.

The argument begins by deconstructing the very term "AI." The authors assert that what is marketed as artificial intelligence is merely a large-scale statistical model, a "stochastic parrot" that lacks any genuine understanding. They support this by contrasting the contextual, social learning of a human toddler with the massive, resource-intensive data processing of LLMs, concluding that the anthropomorphism of "AI" is primarily a product of marketing hype. This foundational claim is crucial because it reframes the public discourse, moving away from sci-fi fantasies and toward a sober assessment of the technology's true nature.

The article then describes the fundamental flaws of LLMs, such as their propensity for "hallucinating" facts, amplifying biases from their training data, and producing simplistic, derivative text. The authors argue that these are not mere bugs but inherent features of systems designed for prediction, not comprehension. The implication is severe: deploying such tools at scale risks further degrading public discourse and democratizing misinformation. This leads to their critique of integrating "AI" into education. They contend that using LLMs for writing undermines the very purpose of learning, which is a "frictional" process of developing one's own ideas through research, critical thinking, and revision. Positioning writing as a transactional task to be optimized fundamentally short-circuits intellectual growth.

In response, the authors position the humanities as the necessary corrective. They point to real-world actions, such as school bans and academic task forces, as evidence that humanists are already providing crucial leadership. The humanities offer the critical tools to contextualize AI within social power structures, like surveillance capitalism and racial bias, and to advocate for robust regulation. The ultimate conclusion is that the future of a healthy democracy and reliable knowledge depends not on adopting AI uncritically, but on strengthening the very humanistic skills—analysis, ethics, and contextual understanding—that this technology threatens to bypass.

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This assignment is highly complex, requiring extensive reading of literature and a deep understanding of its structure. Since my English isn't strong, I first translated the literature into Chinese to grasp its main content and structural framework. Then I carefully read each paragraph of the original text, identifying the main idea and key terms in each section. I systematically listed its arguments, explanations, and examples. It must be said that this article's structure is exceptionally cohesive, with every sentence interconnected. For instance, an argument is always followed by an explanation, using metaphors and examples to help readers grasp the author's position. Furthermore, paragraphs flow seamlessly, with each closing sentence naturally transitioning into the opening of the next. Take this passage: “But then no toddler will ever ‘train on’ and effectively memorize—or monetize—the entirety of the scrapable internet.” The key takeaway? Today’s machine “intelligence” bears little resemblance to the human thought processes to which it is incessantly compared, both by those who gush over “AI,” and by those who fear it." (page 1)Through this process, I gained deeper insight into the structure of accessible writing. Moving forward, I will adopt this approach to enhance the logic and focus of my own articles. Before writing, I will clearly define my main argument and supporting points, and carefully select examples to substantiate my claims. I will also create a logical flowchart before beginning the writing process.