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The writer is a global risk futurist at NYU and leads AI policy research at The Digital Economist think-tank
作者是纽约大学(NYU)的全球风险未来学家，并在智库数字经济学家(The Digital Economist)负责人工智能政策研究工作
Traditional foreign aid is losing steam. Budget constraints, donor fatigue and nationalist politics have eroded the once-dominant western development model. But as governments pull back, a new actor has stepped in. Artificial intelligence is being deployed with a speed and reach that traditional organisations struggle to match. Code — not cash — is the new foreign aid.
传统的对外援助正在失去动力。预算限制、捐助方疲劳以及民族主义政治正在削弱曾经占主导地位的西方发展模式。但随着各国政府逐步撤退，一位新参与者登场了。人工智能正以传统组织很难企及的速度和广度被部署。代码，而非现金，成为了新的对外援助。
Across the global south, AI is already doing some of the work that aid agencies once dominated. Ubenwa’s neonatal diagnostic app in Nigeria, Somanasi’s AI tutor in Kenya and Hello Tractor’s AI-enabled fleet management for small farmers are delivering essential services where public institutions are overstretched or absent.
在全球南方，人工智能已经开始承担一些曾由援助机构主导的工作。Ubenwa 在尼日利亚推出的新生儿诊断应用、Somanasi 在肯尼亚的人工智能辅导应用，以及 Hello Tractor 为小农户提供的 AI 车队管理服务，正在为公共机构人手紧张或缺位的地区提供基本服务。
Who is delivering this AI-powered development? It’s not the World Bank or USAID. Instead, tech companies like OpenAI, Google, Microsoft and Nvidia, alongside local civic-tech innovators, are stepping forward.
是谁在推动这种由人工智能驱动的发展？并不是世界银行(World Bank)或美国国际开发署(USAID)，而是OpenAI、谷歌(Google)、微软(Microsoft)和英伟达(Nvidia)等科技公司，以及本地的公民科技创新者正在挺身而出。
Consider what has already been rolled out. In the past year OpenAI has partnered with a primary care provider in Kenya to support local AI development in healthcare. In South Africa, billionaire Strive Masiyiwa worked with Nvidia to launch the continent’s first “AI factory” — a Johannesburg-based hub designed to train local talent and build regionally relevant models. In Kenya and Ghana, Google is investing in AI research centres. These projects are not labelled as foreign aid, but they’re delivering infrastructure, skills, and tools in exactly the areas where traditional donors have pulled back.
可以考虑已经推出的举措。在过去一年里，OpenAI与肯尼亚的一家初级医疗服务提供商合作，支持当地医疗领域的人工智能发展。在南非，亿万富翁斯特赖夫•马西伊瓦(Strive Masiyiwa)与英伟达合作，在约翰内斯堡建立了非洲大陆首个“AI工厂”——这是一个旨在培养本地人才并构建区域相关模型的中心。在肯尼亚和加纳，谷歌正在投资建设人工智能研究中心。这些项目并未被贴上对外援助的标签，但它们正为传统捐助方逐渐撤出的领域提供基础设施、技能和工具。
This work isn’t altruism, it’s strategy. The Trump administration’s recently released AI Action Plan makes the point explicit: AI is now a core pillar of foreign policy. The plan outlines a bold objective — exporting “the full AI stack” (from chips to models to standards) to build alliances, spread American values and counter Chinese influence in emerging markets.
这项工作并非出于利他主义，而是一种战略。特朗普(Trump)政府最近发布的《人工智能行动计划》(AI Action Plan)明确指出：人工智能如今已成为外交政策的核心支柱。该计划提出了一个大胆的目标——输出“完整的人工智能技术体系”（从芯片到模型再到标准），以建立联盟、传播美国价值观，并在新兴市场对抗中国影响力。
But those values are not always clear — or universally shared. Alongside the push to expand access to “responsible AI,” US policymakers are backing efforts to remove what some see as “woke” elements from AI models — curbing progressive language on race, gender and history.
但这些价值观并不总是明确的，也并非被普遍认同。在推动扩大“负责任的人工智能”使用的同时，美国政策制定者也在支持将一些人认为属于“觉醒”元素从人工智能模型中移除的举措——限制模型在种族、性别和历史等方面的进步性用语。
It is also worth distinguishing between tech companies that operate as agents of government strategy and those who act independently. While Chinese firms often align closely with state-backed development goals, many western AI companies follow commercial incentives — yet their actions can still serve national interests by entrenching influence, standards and dependencies abroad, whether intentionally or not.
同样值得区分的是，作为政府战略代理人运作的科技公司与那些独立行动的公司。中国公司通常与国家支持的发展目标紧密一致，而许多西方人工智能公司则以商业激励为导向——但无论有意还是无意，他们的行为仍可能通过在海外巩固影响力、标准和依赖关系，服务于国家利益。
This raises important questions. What norms and political assumptions are being embedded in the AI models that are exported? And will AI-as-aid replicate old dependencies in a more sophisticated form?
这引发了重要的问题：被出口的人工智能模型中嵌入了哪些规范和政治假设？人工智能援助(AI-as-aid)是否会以更复杂的形式复制以往的依赖关系？
AI development may be fast and scalable — but it is not immune to the problems that have plagued foreign aid for decades. Many of these tools depend on high energy use, commercial licences and recurring model updates — opening the door to problems with sustainability, affordability and lack of local control.
人工智能的发展可能迅速且具备可扩展性，但它并不能免于困扰对外援助数十年的问题。许多此类工具依赖高能耗、商业许可和持续的模型更新，这就带来了可持续性、可负担性以及缺乏本地控制等问题。
To avoid repeating past mistakes, we need a new global framework. Just as Bretton Woods reimagined aid for the postwar world, a blueprint for the AI century is required — one in which compute access, data infrastructure and open models are treated as public goods. That means supporting regional training data, funding inclusive language models and investing in local talent pipelines.
为了避免重蹈覆辙，我们需要一个新的全球框架。正如布雷顿森林(Bretton Woods)为战后世界重新构想了援助一样，人工智能世纪也需要一份蓝图——在这份蓝图中，算力获取、数据基础设施和开源模型都被视为公共产品。这意味着要支持区域性训练数据，资助包容性的语言模型，并投资于本地人才培养体系。
The global development sector, still reeling from post-pandemic cutbacks and crises, would do well to pay attention. Whether we are ready or not, the code diplomat has arrived.
全球发展领域在经历了疫情后的削减和危机后，仍在努力恢复元气。无论我们是否准备好，“代码外交官”已经到来，这一现象值得我们关注。