Vox Populi, Vox ChatGPT：大语言模型、教育与民主
Vox Populi, Vox ChatGPT: Large Language Models, Education and Democracy
AI总结：
本文探讨大语言模型（如ChatGPT）对民主的潜在威胁，提出替代、真实性和事实三个论证，并主张通过教育培养批判性思维以负责任地使用AI，增强而非替代人类能力。
摘要：
在生成式人工智能时代，特别是以ChatGPT为代表的大语言模型（LLMs）的出现，使得人工智能与人类推理的交汇成为全球关注的焦点。与传统搜索引擎不同，大语言模型超越了单纯的信息检索，进入了话语文化领域。其输出模拟了深思熟虑的独立观点或事实陈述，呈现出一种智慧的假象。本文探讨了大语言模型对民主社会可能产生的变革性影响，深入探讨了难以区分ChatGPT生成文本与人类输出这一担忧。讨论强调了作者身份的本质，根植于人类独有的推理能力——这一品质对于民主话语和自由社会中成功的协作不可或缺。为强调对民主的潜在威胁，本文提出了三个论点：替代论证、真实性论证和事实论证。这些论点凸显了过度依赖大语言模型所带来的潜在风险。核心论点认为，如果不能积极且恰当地理解和应对，大语言模型的广泛部署可能对民主结构产生不利影响。在提出解决方案时，我们主张强调教育作为降低风险的手段。我们建议培养儿童的思考技能，促进连贯思维的形成，并区分机器生成的输出与真正的（即人类的）推理。重点应放在负责任地开发和使用大语言模型上，目标是增强而非替代人类在思考、审议和决策方面的能力。
英文摘要：
In the era of generative AI and specifically large language models (LLMs), exemplified by ChatGPT, the intersection of artificial intelligence and human reasoning has become a focal point of global attention. Unlike conventional search engines, LLMs go beyond mere information retrieval, entering into the realm of discourse culture. Its outputs mimic well-considered, independent opinions or statements of facts, presenting a pretense of wisdom. This paper explores the potential transformative impact of LLMs on democratic societies. It delves into the concerns regarding the difficulty in distinguishing ChatGPT-generated texts from human output. The discussion emphasizes the essence of authorship, rooted in the unique human capacity for reason - a quality indispensable for democratic discourse and successful collaboration within free societies. Highlighting the potential threats to democracy, this paper presents three arguments: the Substitution argument, the Authenticity argument, and the Facts argument. These arguments highlight the potential risks that are associated with an overreliance on LLMs. The central thesis posits that widespread deployment of LLMs may adversely affect the fabric of a democracy if not comprehended and addressed proactively and properly. In proposing a solution, we advocate for an emphasis on education as a means to mitigate risks. We suggest cultivating thinking skills in children, fostering coherent thought formulation, and distinguishing between machine-generated output and genuine, i.e. human, reasoning. The focus should be on responsible development and usage of LLMs, with the goal of augmenting human capacities in thinking, deliberating and decision-making rather than substituting them.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
