Artificial intelligence has already created trillions(数万亿) of dollars of market value and turned a handful of tech nerds into celebrities. The public is excited but also terrified. Many brainy(聪明的，有头脑的) people, from Bill Gates to Elon Musk, say that the technology is just getting started. Talk to academic economists, though, and most seem oddly uninterested in studying the impact of the potentially world-changing technology. The centre of gravity in ai economics is instead shifting away from universities—and a gang of “ai-pilled economists” is leading the charge(带头冲锋，引领潮流).
人工智能已经创造了数万亿美元的市场价值，并将少数科技极客变成了名人。公众既兴奋又恐惧。从比尔·盖茨到埃隆·马斯克，许多聪明人都表示这项技术才刚刚起步。然而，与学术经济学家交谈时，大多数人似乎出奇地对研究这项可能改变世界的技术的影响不感兴趣。人工智能经济学的重心正从大学转移——一群“AI上头”的经济学家正在引领潮流。
University researchers can move fast when they want to. After Lehman Brothers, an investment bank, collapsed in 2008 and sparked the global financial crisis, economists turned the study of bank runs and credit crunches from a niche pursuit(小众领域，冷门研究) into a mainstream interest. Two months into covid-19, in 2020, close to a third of working papers on economics published by America’s National Bureau of Economic Research (nber), a prestigious repository of economic thought, focused on the pandemic’s effects in some way. Some of this work burst into(突然进入，闯入) the mainstream, including that by Nicholas Bloom of Stanford University, an expert in working from home, and Emily Oster of Brown University, who studied school closures.
大学研究人员在需要时可以快速行动。2008年投资银行雷曼兄弟倒闭并引发全球金融危机后，经济学家将银行挤兑和信贷紧缩的研究从冷门领域变成了主流兴趣。2020年新冠疫情爆发两个月后，美国国家经济研究局（NBER）——一个享有盛誉的经济思想库——发表的经济学工作论文中近三分之一以某种方式关注了疫情的影响。其中一些研究成果进入了主流视野，包括斯坦福大学远程办公专家尼古拉斯·布鲁姆和布朗大学研究学校停课的艾米丽·奥斯特的研究。
Three and a half years after the launch of ChatGPT ushered in the ai age, by contrast, economic analysis of the technology remains comparatively scarce(稀缺的，不足的). The share of nber papers which focus on ai is rising, but not especially fast (see chart 1). Even in 2024, after the covid emergency was over and the ai era had truly begun, the number of covid-related papers exceeded(超过，超出) the number of AI-related ones. This year the nber is likely to host more conferences on health care than on ai.
相比之下，在ChatGPT推出开启AI时代三年半后，对这项技术的经济分析仍然相对稀缺。NBER论文中关注AI的比例在上升，但并非特别快（见图表1）。即使在2024年，新冠疫情紧急状态结束、AI时代真正开始之后，与疫情相关的论文数量仍超过了与AI相关的论文。今年NBER举办的医疗健康会议很可能多于AI会议。
Artificial scarcity
人为稀缺
Real-time intelligence
实时情报