哈佛大学经济学家杰森·弗曼告诉Axios，如果他今天重返白宫经济顾问委员会主席的旧职，他将在该委员会大部分日常分析工作中依赖AI工具，而非幕僚经济学家。
Harvard economist Jason Furman told Axios that if he were to return to his old job as chairman of the White House Council of Economic Advisers today, he would rely on AI tools over staff economists for much of the council's day-to-day analytical work.
大局观：毫不意外，这在网络讨论中激起波澜，尤其是在那个松散的、前称“Econ”的经济学家圈子里。许多在经济政策一线摸爬滚打的老将看到，未来的决策者过度依赖AI存在真实风险——至少认为弗曼低估了人类经济学家在为国家领导人提供建议方面的重要性。
The big picture: Unsurprisingly, this made some waves in the online discourse, particularly the loose-knit community formerly known as Econ • Many veterans of the economic policy trenches see real risks in future policymakers becoming overly reliant on AI — or at a minimum think that Furman is underestimating the importance of human economists in advising the nation's leaders.
各方观点：拜登政府时期的经济顾问委员会主席贾里德·伯恩斯坦在Substack上写道：“就我的经验而言，经济顾问委员会的工作高度定制化，因为你要向极其忙碌、不想只看到现成分析的人解释数据流向（以及更多内容）。”
What they're saying: "CEA work, at least in my experience, is highly bespoke as you're explaining the data flow (and much else) to very busy people who don't want only market-shop analysis," Jared Bernstein, the CEA chair under President Biden, wrote on Substack
- “是的，他们想要并需要那种分析——市场会如何解读这份CPI、就业、GDP等报告——但更重要的是，他们想知道这份报告如何融入我们的叙事、我们的议程、总统今天去爱荷华州访问的行程中。”
• "Yes, they want and need that — what will the markets make of this CPI, jobs, GDP, etc. report — but more so they want to know how this report fits into our narrative, our agenda, the president's trip today to Iowa."
- 他补充说，在白宫内部，“观察言行察言观色（读懂现场氛围）的人类技能至关重要。我远非AI专家，但我感觉AI在这方面很糟糕，而且可能永远都会很糟糕，这个结论在不小程度上源于听取其创造者的看法！”
• He adds that within a White House, "the human skill of reading-the-room is paramount. I'm far from an AI expert, but my sense is it sucks at that and probably always will, a conclusion that derives in no small part from listening to its creators!"
深度聚焦：前美联储经济学家克劳迪娅·萨姆提出了一个我们常从咨询、投资银行等领域的资深人士那里听到的问题：如果取消初级职位，未来的高层领导者从哪里来？
Zoom in: Claudia Sahm, a former Federal Reserve economist, raised an issue that we've often heard from senior people in fields like consulting and investment banking: If you get rid of junior positions, where will future senior leaders come from?
- 她在X上写道：“弗曼的幕僚‘后来创立了耶鲁预算实验室，掌管财政部经济政策和一个美联储研究所，在后来的政府中任职，并发表了关于贸易、环境和税收的研究。这就是‘20名幕僚’会变成的样子。没有任何模型能做到这一点。’”
• Furman's staff "went on to found the Yale Budget Lab, run Treasury economic policy and a Fed institute, serve in later [administrations], and publish research on trade, environment, and taxes. That's what '20 staff' become," she wrote on X. "No model does that."
- 彭博社首席美国经济学家安娜·黄（Anna Wong）认为，“作为资深人士，现在能够不依赖任何人，这非常、非常有赋能感。如今，仅凭一个想法，资深人士就能走得很远。”
• Bloomberg chief U.S. economist Anna Wong argues that the "ability to now not depend on anyone, as a senior person, is very, very empowering. Now, with just the idea, a senior person can go far."
“进入科幻推测领域，”黄在 X 上写道，“由于年轻人类专家储备不足，我们人类无法替代老龄化的专家，AI 本身通过多年的训练，成为了产生创意的那一个。”
"Entering into sci fi speculation," Wong wrote on "as humans [we're] not about to replace the aging experts due to low pipeline of young human experts, AI themselves, through the training over the years, became the one spawning the ideas."
- “这看起来像是一场等待发生的灾难，当前的社会政策需要加以应对。”
• "That seems like a disaster waiting to happen that current social policy needs to address."
但也有不同观点：凯西·穆利根（Casey Mulligan）曾在特朗普首任期内担任白宫经济顾问委员会（CEA）成员，现任卫生与公众服务部首席经济学家，他表示，AI 对政策制定中人力劳动的影响并不那么显而易见。
Yes, but: Casey Mulligan, who served in President Trump's first-term CEA and now as chief economist at the Department of Health and Human Services, said that the implications of AI for human labor in policymaking are not so obvious.
- “我在两个联邦办公室构建过 AI 工具，”穆利根在 X 上写道。“由于能更好、更快地开展经济研究，我们对所做工作的需求增加，因此需要更多经济学家，而不是更少。这种模式在小企业领域也显而易见。”
• "I built AI tools at two federal offices," Mulligan wrote on X. "Able to do economic research better and more quickly, we needed more economists rather than fewer due to the added demand for what we do. This pattern is also evident in the small business sector."
- 这一概念——即节省劳动力的工具反而可能增加对劳动力的需求——被称为杰文斯悖论。
• This concept — that labor-saving tools can actually increase demand for labor — is known as Jevons Paradox.
核心观点：“要成为你希望在世界上看到的那种增强劳动力的技术变革，”斯坦福大学经济学家尼尔·马霍尼（Neale Mahoney）写道。
The bottom line: "Be the labor-augmenting technological change you want to see in the world," wrote Stanford economist Neale Mahoney.
- “我们这些老一辈有责任建立人与 AI 相互补充的组织，并为年轻一代做好准备，迎接一个 AI 越来越强大的世界，”他补充道。
• "It's on us olders to build organizations where people and AI complement each other, and to prepare the youngers for a world with better and better AI," he adds.