研究的工业化；论人工智能驱动的科学及其后果
The Industrialization of Research ; On AI-Driven Science and Its Consequences
- Inria（法国国家信息与自动化研究所）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
探讨人工智能驱动科学带来的研究工业化转变，如从技艺模式到流水线模式。分析了这种转变引发的七个问题，包括能力传承、理论透明度等，强调虽不反对其潜力，但要在这些条件下负责任地追求。
AI中文摘要：
人工智能正在改变科学研究——不仅是作为一种更强大的工具，更是作为研究周期中的自主参与者。这种转变在最精确的意义上构成了研究的工业化：从知识、方法和判断都嵌入在研究者身上的技艺模式，转变为这些步骤被分解、自动化和监督的流水线模式。美国能源部的创世纪任务是这种转变当前最雄心勃勃的实例，但它引发的基本问题远远超出任何单个项目。本文探讨了七个这样的问题：科学能力代际传承的侵蚀；人工智能生成理论的透明度不断提高；在大量机器生成的产出下同行评审的崩溃；人工智能在范式转变发现方面未经证实的能力；政治和工业行为者对科学议程的掌控；闭环流水线中系统错误的加剧；以及全球研究界在结构上分为不可通约的层级。这些担忧并不构成反对人工智能驱动科学的论据——其已证明的潜力是真实且巨大的。它们构成了负责任地追求这种潜力的条件。
英文摘要：
Artificial intelligence is transforming scientific research -- not merely as a more powerful instrument, but as an autonomous participant in the research cycle itself. This transition constitutes, in the most precise sense of the term, the industrialization of research: a shift from a craft model, in which knowledge, method, and judgment are embedded in the researcher, to a pipeline model, in which these steps are decomposed, automated, and supervised. The US Department of Energy's Genesis Mission is the most ambitious current instantiation of this shift, but the fundamental questions it raises extend far beyond any single program. This essay examines seven such questions: the erosion of the intergenerational transmission of scientific competence; the growing opacity of AI-generated theories; the collapse of peer evaluation under a flood of machine-generated output; the unproven capacity of AI for paradigm-shifting discovery; the capture of the scientific agenda by political and industrial actors; the compounding of systematic errors in closed-loop pipelines; and the structural bifurcation of the global research community into incommensurable tiers. These concerns do not constitute an argument against AI-driven science -- whose demonstrated potential is real and significant. They constitute the conditions under which that potential can be responsibly pursued.
