资源简介

猜想6：思辨人机交互的伦理与边界
样题1：阅读理解：你的内心独白，会被机器“听见”吗？
本题是对2025课程标准课程理念修订变化中“增强现实、人机交互”的呼应。这样的设问在人工智能与人机融合加速发展的时代具有重要而现实的意义。题目考查考生在科技类文本中定位、分析与评价信息的能力，通过脑机接口（BCI）这一具体情境引导广大考生思考技术发展的双刃剑效应-如何在利用技术赋能的同时，守护人类的思维隐私与表达自主性，鼓励考生在语言表达中兼顾事实性论证与价值判断，实现了语言能力考查与价值引领的有机统一。
［2026届海南部分学校12月第三次月考］Now, devices called brain-computer interfaces （接口）,or BCIs, have got better than ever before at translating thoughts from people with speech difficulties.
In previous uses of BCIs, researchers asked patients who couldn't speak to try to physically form words. This generated so-called "attempted speech" signals in the brain-signals that were picked up by electrodes（电极）placed in the brain and interpreted by means of a computer algorithm（算法）. This process, however, could be tiring and uncomfortable for users, as Erin Kunz, an electrical engineer at Stanford University, says.
So Kunz and her team decided to investigate if implanted electrodes could pick up a patient's inner voice. If so, this could make device operation easier for users. But this research was also meant to investigate questions around privacy. Could these devices also pick up unintentional speech After all, our inner voices might articulate things we don't want others to know. To protect users' privacy, they chose a passphrase to activate the device. It was unlikely to come up in everyday speech: Chitty Chitty Bang Bang. The technology would start translating thoughts when it detected the phrase.
In the tests, researchers asked participants with speech difficulties to either try to say seven specific words or merely think them. Then they trained a computer system on signals from participants thinking words from a 125,000-word vocabulary. When participants thought sentences with these words, the technology produced words with an error rate of 26 to 54 percent, making it the most accurate inner speech translation to date.
“It's a fantastic advance,” says Christian Herff, a researcher at Maastricht University in the Netherlands, adding that the technology not only helps people who can't speak but also improves scientists' understanding of how language works. But the researchers say they're not done yet. They're working toward even better outcomes. "The results are an initial proof of concept more than anything," Kunz says. “We haven't hit the ceiling yet."
1.What was the purpose of using BCIs according to Paragraph 2
A. To check patients' inner speech ability.
B. To analyze attempted speech physically.
C. To detect and translate brain signals.
D. To train patients to form words correctly.
2.What does the underlined word "articulate" mean in Paragraph 3
A. Express. B. Hide.
C. Ignore. D. Compare.
3.What is the breakthrough in the new research on BCIs
A.BCIs' working without computer support.
B. An extensively expanded word database.
C. Improved inner speech interpretation.
D. The application of electrode technology.
4.What can we learn about the research from the last paragraph
A. Its focus has shifted to language theory.
B. The technology is still in its early stage.
C. The error rate remains the biggest barrier.
D. It is widely recognized by medical companies.
参考答案与解析：
【语篇导读】这是一篇科技发展类说明文，文章结构为：技术现状引入（Para.1）→传统方法的局限（Para.2）→新研究的目标与隐私考量（Para.3）→测试方法与突破性成果（Para.4）→研究意义与未来展望（Para.5）。本文主要介绍了Erin Kunz的研究团队在脑机接口（BCI）技术上的新进展，该技术通过检测“内心声音”信号，实现了迄今为止最准确的“内心声音”翻译。这不仅有益于言语障碍患者，也增进了科学家对语言工作机制的理解，但该研究仍处于概念验证的早期阶段。
1．设问方向对科学技术BCI的使用目的设问。
答案解析细节理解题。根据第二段中的“This generated... signals that were picked up by electrodes（电极）... and interpreted by means of a computer algorithm（算法）”可知，BCI的目的是检测并解读大脑产生的信号。故选C。
【避盲点】本题易误选B项。第二段描述了研究人员让患者尝试“物理构词（physically form words）”，这产生了“尝试性盲语”信号，但分析信号是手段，而非BCY使用的最终目的，BCI的目的是解读这些信号。
2．设问方向对文本关键词的词义推测设问。
答案解析词义猜测题。根据第三段画线词所在句＂our inner voices might articulate things we don't want others to know＂可知，“内心声音”可能会我们不想他人知道的事情。结合后文为保护隐私设置口令，可推断“articulate”意为“表达”。故选A。
3．设问方向对科学技术研究的新突破设问—BCI新研究的突破点是什么。
答案解析推理判断题。根据第四段中的“When participants thought sentences... the technology produced words... making it the most accurate inner speech translation to date＂可知，新研究的突破在于实现了对“内心声音（inner speech）”更准确的翻译解读。故选C。
干扰项分析
A项 第二段明确提到信号需“interpreted by means of a computer algorithm（算法）”，计算机支持是BCI工作的核心。该选项属于与原文事实相反的绝对化描述。
B项 原文第四段提到使用了“125,000-word vocabulary”进行训练，但词汇库是工具和基础，而“提升对内在声音的解释准确率”才是核心成果。该选项混淆了“工具”与“成果”。
D项 该选项利用了“新技术必然依赖新硬件”的思维定式。电极技术是BCI的基础，并非此项研究带来的新突破。第二段已说明：在BCIs的此前使用（previous uses of BCIs）中同样使用了植入电极来捕捉“尝试性言语”信号。本研究的突破在于信号类型的转换-从捕捉“尝试性言语”的脑信号，转向捕捉“内心声音”的脑信号，并成功解码。因此，该选项属于将旧有技术手段误判为新突破。
4．设问方向对科学研究的发展阶段与认知设问。
答案解析推理判断题。根据最后一段研究学者Kunz的话“The results are an initial proof of concept more than anything...”和“We haven't hit the ceiling yet”可知，该成果更多是初步的概念验证，且还有很大提升空间，说明技术仍处于早期阶段。故选B。
【避盲点】本题易误选C项。虽然第四段提到了26％至54％的错误率，但最后一段的重点是研究者对未来的展望和“未到天花板”的态度，这表明错误率是待改进的问题，但段落主旨并非强调其是“最大的障碍”。
样题2：阅读理解：对AI讲礼貌，数字互动中的人文价值
本题语境涉及人工智能技术的应用，是对2025课程标准中新增的“人机交互”的延伸。本题以“对AI讲礼貌”现象为切入点，结合心理学实验论证其培养人类积极品质的价值，通过现象分析、观点解读等题考查考生推理判断能力。题目引导考生辩证看待数字技术与人文品质的关系，彰显英语学科工具性与人文性的统一。
［2026届浙东北县域名校发展联盟11月诊断测试］ I often catch myself starting my questions to ChatGPT with a “please” and concluding with a “thank you”. Apparently, I am not alone. A survey published in 2024 by TechRadar found that approximately 67% of AI users are also polite and show gratitude toward AI search engines.
When asked whether there's a cost to all this politeness, OpenAI CEO Sam Altman responded, "Tens of millions of dollars well spent-you never know." In reality, of course, AI chatbots do not appreciate politeness; they lack consciousness, feelings or a need for social politeness. From a purely practical standpoint, all those pleases and thank-yous are just flushing money down the toilet.
Still, there may be value that isn't immediately measurable in showing gratitude toward AI. In his book The Psychology of Gratitude, psychologist Robert Emmons writes about a 10-week experiment. He divided participants into three groups, asking the first to list things they are grateful for, the second to list daily annoyances and the third to just keep a journal.
He found that the first group reported 25% higher happiness levels, showed stronger emotional resilience（适应力）and were physically healthier. Other studies have also linked gratitude to better sleep, less depression and anxiety, and greater relationship satisfaction.
What's true of gratitude is also true of kindness and generosity. Psychology professor Sonja Lyubomirsky from UC Riverside conducted experiments where participants performed “five small acts of kindness per week". She found that these small, frequent acts led to consistent and significant increases in happiness. These modern researchers are rediscovering an age-old wisdom: We should practice doing good regularly, not just for the sake of the people we benefit, but for our own.
So perhaps all of our pleases and thank-yous to AI have value, even if they cost OpenAI millions of dollars annually. Showing appreciation, even toward a machine, strengthens positive habits of politeness, patience and empathy. In our increasingly digital and automated world, preserving these human qualities may be more valuable than the substantial costs. Ultimately, the one who benefits from our politeness isn't the AI at all, but ourselves.
1.Why is the survey mentioned in Paragraph 1
A. To present a fact. B. To challenge a belief.
C. To support an argument. D. To illustrate a phenomenon.
2.How does Sam Altman seem to view the cost of politeness to AI
A. As an educational tool. B. As a necessary investment.
C. As a social requirement. D. As a technical breakdown.
3.What do the experiments find about being polite to AI
A. It helps people develop positive habits.
B. It improves the AI's response quality.
C. It brings lasting happiness to the AI.
D. It makes people more grateful to others.
4.What does the author mean in the last paragraph
A. Politeness to AI is meaningless but costly.
B. Digital interactions require new polite behavior.
C. Humans benefit more than AI from being polite.
D. AI will eventually develop emotional awareness.
参考答案与解析
【语篇导读】这是一篇科技与社会行为现象分析类议论文，文章结构为：从个人观察与数据引入话题（Para.1）→企业观点与成本分析（Para.2）→心理学理论与实验论证（Paras.3-5）→总结升华论点（Para.6）。文章探讨了人们在同AI交流时普遍使用礼貌用语的现象，并超越表面成本问题，从心理学实验和古老智慧的角度，深入论证了这种行为对培养人类良好习惯和积极品质的内在价值。
1．设问方向对文章论证逻辑设问-引用调查数据的作用。
答案解析推理判断题。第一段从作者的自我观察（“我”对ChatGPT说“请”和“谢谢”）切入，随即通过2024年一项调查的数据（约67％的AI用户也这样做），将个人行为拓展为普遍存在的群体表现。这种写法旨在生动地呈现一个社会现象，为后文探讨该现象背后的成本、相关研究及深层价值铺路。D项“为了说明一个现象”准确地概括了引用调查数据的意图。故选D。
【避盲点】本题需区分A选项“呈现事实”与D选项“说明现象”。虽然调查数据本身是客观事实，但作者的目的并非简单地陈列这一信息。作者的写作逻辑是：通过引用具有普遍性的数据，将个人观察提升为一种值得关注的社会现象，从而引出下文关于此现象成本、相关研究及深层价值的系列讨论。因此，“呈现事实”是手段，“说明／揭示现象”才是目的。
2．设问方向对文中人物观点态度设问-Sam Altman 如何看待为礼貌付出的成本。
答案解析推理判断题。根据第二段中的“When asked whether there's a cost to all this politeness, OpenAI CEO Sam Altman responded, 'Tens of millions of dollars well spent-you never know.”可以推断，尽管他承认这是一笔巨大开销，但他使用了积极评价“well spent”。这体现了一种长远、开放的视角，视其为一种有价值的、有潜力的投资，而不仅仅是浪费或技术故障。B项“作为一种必要的投资”准确捕捉了这种态度。
干扰项分析
A项 文中未提及Sam Altman从教育目的或社会教化角度看待此成本，其回应聚焦公司层面的价值判断与未来可能性。
C项 将成本归因于外部社会规范压力，但Sam Altman的回答是从公司运营者视角出发的价值评估，并未涉及社会期待或道德约束。
D项 该选项与原文“well spent”（花得值）的积极评价完全矛盾，属于反向干扰。
3．设问方向对实验研究发现与核心论点设问-研究发现对AI保持礼貌有何作用。
答案解析细节理解题。文章第三、四、五段引用了多项心理学研究来论证感恩、善意等行为对行为者自身的益处。最后一段直接点明核心发现：“Showing appreciation, even toward a machine, strengthens positive habits of politeness, patience and empathy”。A项“它能帮人培养积极的习惯”是对此句核心信息的同义转述。故选A。
【避盲点】本题易误选D项“它让人们更感激他人”。感恩实验只表明记录感恩之事能提升幸福感，文章并未明确推导出“对AI礼貌”会直接导致“对他人更感恩”。A项更直接、精准地对应了文章关于“强化习惯”的最终结论。
4．设问方向对文章主旨与作者写作意图设问。
答案解析推理判断题。最后一段中的“preserving these human qualities may be more valuable than the substantial costs. Ultimately, the one who benefits from our politeness isn't the AI at all, but ourselves”明确指出，在日益数字化的世界里，维系这些人类品质可能比巨额成本更有价值，并最终明确结论：从我们的礼貌中受益的完全不是AI，而是我们自己。C项“Humans benefit more than AI from being polite”（人类比AI从保持礼貌中受益更多）准确地概括了这一对比关系和最终落脚点-真正的受益主体是人类自身。故选C。
2

展开更多......

收起↑