标题： 人工智能革命的三个视角：风险、变革、连续性 显示英文标题

标题： Three Lenses on the AI Revolution: Risk, Transformation, Continuity

摘要： 人工智能（AI）既被视为历史技术革命的延续，也可能成为与之断裂的潜在因素。 本文认为，必须通过三个视角同时看待AI：\textit{风险}，其中它在不可逆和全球性外部效应方面类似于核技术；\textit{转换}，其中它与工业革命类似，作为一种通用技术推动生产力和劳动力重组；以及\textit{连续性}，其中它延续了从个人计算到互联网再到移动设备的五十年计算革命的历程。 借鉴历史类比，我们强调过去的任何过渡都没有构成严格的奇点：破坏性转变最终通过新的规范和制度变得可管理。 我们考察了各次革命中的重复模式——使用层的民主化、生产层的集中化、成本下降和个性化加深，并展示了这些动态在AI时代如何加剧。 行业分析说明了会计、法律、教育、翻译、广告和软件工程等领域正在被重塑，因为常规认知正在商品化，人类价值正转向判断、信任和伦理责任。 在前沿领域，设计道德AI代理人的挑战凸显了需要稳健的护栏、道德泛化的机制以及对新兴多代理动态的治理。 我们得出结论，AI既不是一次单一的断裂，也不仅仅是渐进的进步。 它是进化和革命的结合：其中期影响是可预测的，但带有奇点级别的尾部风险。 良好的结果并非自动产生；它们需要将促进创新的策略与安全治理相结合，确保公平获取，并将AI嵌入人类的责任秩序中。 显示英文摘要

摘要： Artificial Intelligence (AI) has emerged as both a continuation of historical technological revolutions and a potential rupture with them. This paper argues that AI must be viewed simultaneously through three lenses: \textit{risk}, where it resembles nuclear technology in its irreversible and global externalities; \textit{transformation}, where it parallels the Industrial Revolution as a general-purpose technology driving productivity and reorganization of labor; and \textit{continuity}, where it extends the fifty-year arc of computing revolutions from personal computing to the internet to mobile. Drawing on historical analogies, we emphasize that no past transition constituted a strict singularity: disruptive shifts eventually became governable through new norms and institutions. We examine recurring patterns across revolutions -- democratization at the usage layer, concentration at the production layer, falling costs, and deepening personalization -- and show how these dynamics are intensifying in the AI era. Sectoral analysis illustrates how accounting, law, education, translation, advertising, and software engineering are being reshaped as routine cognition is commoditized and human value shifts to judgment, trust, and ethical responsibility. At the frontier, the challenge of designing moral AI agents highlights the need for robust guardrails, mechanisms for moral generalization, and governance of emergent multi-agent dynamics. We conclude that AI is neither a singular break nor merely incremental progress. It is both evolutionary and revolutionary: predictable in its median effects yet carrying singularity-class tail risks. Good outcomes are not automatic; they require coupling pro-innovation strategies with safety governance, ensuring equitable access, and embedding AI within a human order of responsibility.