普通人何时才能感受到 AI 的影响？

我们正处于一场可能持续一个世纪的复合革命不到 5 年的阶段，以及 AI 行业应如何管理这一进程。 We’re <5 years into a compounding revolution which could take a century, and how the AI industry should manage this.

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许多 AI 乐观主义者倾向于将当前 AI 热潮中发生的事情比作工业革命，或比作其他技术快速进步并扩散到社会的时期。这些比较在技术变革的规模上是贴切的，但忽略了大多数人如何接触这种变革的一个关键因素。AI 面临的问题是，大多数人并没有因为它而获得非常实在的新商品，而且社会比以往时代有更多的惯性来抵制变革。

Many AI optimists tend to compare what is happening in this AI boom to the industrial revolution, or to other periods of rapid technological advancement and diffusion into society. These comparisons fit on the scale of technological change, but miss a crucial factor in how most people are exposed to that change. The problem facing AI is that most people have no super tangible new goods thanks to it and society has more inertia resisting change than in previous eras.

我在新英格兰参加婚礼休假几周后，重新上线写下这些。在这段时间里，完全不考虑 AI 是非常容易的。如今普通人与 AI 产品的接触点是边缘性的、略有裨益的，甚至只是让他们非常困惑（例如，许多人听说过并提起 OpenAI-HuggingFace 事件，但不知道该如何理解它）。积极一方的人认为 AI 是一种制作有趣图像、增强 Google 搜索等方式。这些都是非常小的好处。消极一方则将其与令人上瘾的社交媒体算法、朋友的朋友沉迷于 AI 聊天机器人，以及关于数据中心的众多观点联系在一起。

I’m writing this coming back online from a few weeks off for my wedding in New England. In this time it would have been very easy to not think about AI at all. The touch-points that average people have to AI products today are fringe, marginally beneficial, or even just very confusing to them (e.g. many people have heard about and brought up the OpenAI-HuggingFace incident, but don’t know what to make of it). People on the positive side think of AI as a way to make fun images, enhanced Google Search, etc. These are very small benefits. On the negative side is an association with addictive social media algorithms, friends of friends addicted to AI chatbots, and a plethora of takes on data centers.

AI 在日常生活中仍是一个舍入误差 AI is still a rounding error in everyday life

日常生活的核心方面——家庭、食物、交通和娱乐——目前几乎没有受到直接影响。跳出泡沫，意识到正在发生的事情在 _今天_ 实际上多么无关紧要，这是一种令人耳目一新的体验。痴迷于 AI 是一种选择，目前只有极少数人选择了它。例如，在这段时间里，我使用 AI 的唯一用途是搜索和创意工作（为我的婚礼宾客制作漂亮的座位表，以便他们找到自己的桌子）。

Core aspects of everyday life — family, food, transportation, and entertainment — have few direct impacts yet. It’s a remarkable breath of fresh air to pop out of the bubble and realize how little what is happening really matters _today_. Being obsessed with AI is a choice that a very few people have yet opted into. For example, the only thing I used AI for in this time was search and creative work (making the pretty seating chart for my wedding guests to find their table).

在过去的工业革命中，普通人获得了彻底改变生活的成果。18 世纪末的第一次工业革命使人们能够获得更便宜的服装、炊具、阅读材料，并转向新的生计。19 世纪末的第二次工业革命引入了家用机器（如缝纫机）、保存食品、室内管道、摄影、更好的光源、自行车，以及制成品和电气化的进一步好处。这份清单令人瞩目——其中大部分我们今天仍在经常使用——而且非常物质化。

In industrial revolutions past, average people got absolutely life changing outcomes. The First Industrial Revolution in the late 18th century gave access to cheaper clothing, cooking ware, reading material, and a shift to new livelihoods. The Second Industrial Revolution in the late 19th century introduced household machines (e.g. sewing machines), preserved food, indoor plumbing, photography, better light sources, bicycles, and further benefits of manufactured goods and electrification. The list is remarkable — most of these we still use regularly today — and very physical.

尽管即使是最乐观的 AI 版本也将带来新的科学发现、罕见疾病的先进疗法，甚至可能带来持续的经济繁荣，但这些好处有可能过于间接。

While even the most optimistic versions of AI will usher in new scientific discoveries, advanced therapeutics for rare diseases, and potentially even sustained economic abundance, these benefits have the risk of being too indirect.

如果普通公民去看家庭医生，医生告诉他们一种新的神奇疗法，他们怎么会将拯救生命归功于 OpenAI 或 Anthropic？

How will a common citizen come to credit OpenAI or Anthropic for saving their life, if they went to their family doctor who told them about a new miracle cure?

有多少百分比的美国人会关心 OpenAI 解决了纳维-斯托克斯千年奖问题？

What percentage of Americans will care about OpenAI solving the Navier-Stokes Millennium Prize Problem?

很可能在 50 年后，普通美国人的日常生活看起来仍会非常相似。他们的住宅、家电、人际关系和交通工具都会差不多（当然，自动驾驶会继续普及，但它一直沿着一条与 LLM 创新非常独立的轨迹发展）。在这段时间里，AI 会获得很多赞誉。考虑到当今在这个以 AI 为中心的狭窄领域里一切变化得如此之快，50 年是一段相当长的时间。

It feels very likely that in 50 years the average American's day-to-day life will look very similar. Their home, appliances, relationships, and vehicles will be similar (of course, self-driving will continue to diffuse, but that has been developing on a very independent trajectory from the innovations of LLMs). In this time, AI will get a lot of credit. 50 years is a remarkable length of time given how fast everything is changing today in this AI-focused narrow slice of the world.

在 AI 革命早期所发生的事情中，最重要的部分是构建基础性基础设施和一套通用流程，它们将在几十年间产生复利效应。与复利旅程后期出现的进步相比，今天的一项重大数学突破在范围上会显得微不足道。很难预测，当你日常使用的每一项技术都因 AI 而获得更快的复利式改进时，那会是什么样子。

The most important part of what is happening early in the AI revolution is building foundational infrastructure, and a general process, which will compound over decades. A major mathematical breakthrough today will look astonishingly minor in scope relative to the advancements that come later in the compounding journey. It is hard to predict what it looks like for every technology you use daily to get faster compounding improvements due to AI.

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打破社会停滞 Breaking social stasis

围绕 AI 的许多叙事都在试图推动人们去关注，这至少是出于这种长期进步现实的潜意识动机。要处理好这一点需要很长很长时间，而 AI 的建设由于这种失衡正面临紧迫的政治问题。

Much of the narrative around AI is trying to push people to care, due to this long-term reality of progress, at least as a subconscious motive. This will take a long, long time to get right, and AI's buildout faces immediate political problems due to this imbalance.

当今的 AI 主要是服务精英的工具。对于知识工作——大约占美国经济的一半——AI 就像电力一样基础（或者随着未来 18 个月内智能体的快速改进，很快会如此）。拥有如此具有变革性、高生产率的工具却只带动社会的一半，这极具破坏稳定性。很多人不难察觉到这一点——科技经济繁荣，而生活却停滞不前。

Today's AI is primarily a tool to serve the elite. For knowledge work, which is roughly half of the U.S. economy, AI is as fundamental as electricity (or quickly will be so, with rapid improvements to agents in the next 18 months). It's highly destabilizing to have such a transformative, productive tool only bring half of society along. It's not hard for many people to pick up on this — the technology economy booms while life stays otherwise stagnant.

在撰写本文时，我了解到恩格斯停顿，即“1790 年至 1840 年期间，英国工人阶级工资停滞，而人均国内生产总值在技术剧变中迅速增长。”1 如果我们——AI 行业的领导者——认为这是与 AI 未来最接近的类比，那么未受益者进行反击是正确的。

In writing this, I learned of Engels' pause, which is "the period from 1790 to 1840, when British working-class wages stagnated and per-capita gross domestic product expanded rapidly during a technological upheaval."1 If we — the leaders of the AI industry — think this is the closest analogue to what comes next for AI, those not benefiting are right to push back.

AI 是有史以来扩展科技公司和创办新型在线原生小企业的最佳工具。我甚至不指望科技行业在巨大成功的时代增加员工人数并培养其工人——我同意 Doug O'Laughlin 的观点，即员工人数可能会缩减，而知识工作产出会爆炸式增长。这些部门已经是美国经济体系中最成功的，因此 AI 的品牌将因不是集体利益而受损。我担心这种本能反应会削弱 AI 的发展，使其走上一条更接近美国核电警示故事的道路。

AI is the greatest tool ever for scaling technology companies and starting new online-native small businesses. I don't even expect the tech industry to grow in headcount and nurture its workers through an era of massive success — I agree with Doug O'Laughlin that headcount would likely shrink while knowledge work output explodes. These sectors were already the most successful in the American economic system, so the brand of AI will be tarnished as not being a collective good. I worry that this instinctive reaction will kneecap AI's development, sending it down a path that looks closer to the cautionary tale of American nuclear power.

部分挑战在于社会期望的速度和无情。AI 行业有数百万双眼睛盯着，不会有太多耐心等待以后再带来创新。如果给它 100 年时间融入社会，其影响肯定会变得更加明显，就像几个世纪前的工业革命一样。

Part of the challenge is the speed and relentlessness of expectations in society. The AI industry has millions of eyes on it, and won't get much patience to wait and bring innovations later. If given 100 years to diffuse into society, its impacts will certainly become much more obvious, like the industrial revolutions of centuries past.

总体而言，AI 产业正面临几个简单的问题，而我将此称为 50 年扩散过程的第一个五年。

Together, the AI industry is facing a few simple issues, in what I would call the first half decade of a 50-year diffusion process.

1. AI 在其演进早期的积极影响过于间接。

1. AI's positive impacts early in its evolution are too indirect.

2. AI 正面临一场与西方社会大型科技公司历史深度交织的政治反弹。这仅仅因为时机而成为一个 AI 故事，如果 AI 的指数级增长发生在谷歌和 Meta 等当今技术平台经历成长阵痛数十年之后，那么数据中心问题似乎很可能永远不会上升到如此核心的政治地位。

2. AI is facing a political backlash deeply intertwined with the history of Big Tech in Western society. This is only an AI story due to timing, and if AI's exponential growth came decades after the growing pains of today's technology platforms like Google and Meta, it seems likely that the datacenter issue would've never risen to such a central political position.

解决其中任何一个问题都将缓解大量压力，并给 AI 产业更多时间来展示积极的案例，说明为什么人们应该接受现状的改变（主要是经济方面的）。而 AI 通过宣扬末日论和大规模失业，将自己标记为负面和/或不安全的技术，使得这两点都更具挑战性。领军人物已开始解决这个问题，但公众需要更多努力才能完全接受总体发展轨迹。

Solving either of these would alleviate a substantial amount of pressure, and give the AI industry a lot more time in showing the positive case for why people should be okay with changes to the status quo (primarily economic). These are both made more challenging by AI self-labeling itself as negative and/or unsafe technology, through proclamations of doom and mass unemployment. The leading figures have begun addressing this issue, but the public needs more work to fully buy into the overarching trajectory.

从长期来看，我可以预见机器人技术和自动驾驶在叙事中与当前的 AI 革命紧密相连。如果大规模生产大语言模型带来的智能爆炸确实外溢到加速日常生活中机器人的普及，人类将迅速抓住 AI 的切实好处。这很讽刺，因为许多人花费时间试图说服人们，大语言模型所发生的事情与过去一二十年的一般 AI 进展非常不同。如果同样的动态后来拯救了（或极大地掩盖了）大语言模型，那将很有趣。

When zooming out long-term, I could see robotics and self-driving becoming closely linked in storytelling to the current AI revolution. If the intelligence explosion from mass-producing large language models _does_ spill over into enabling the acceleration of robots in everyday life, humans will quickly latch onto the tangible benefits of AI. This is ironic, as many people have spent time trying to convince people that what is happening specifically with LLMs is very different than the previous decade or two of general AI progress. If the same dynamic later saved (or massively overshadowed) LLMs, it would be funny.

反思我预期这个时代的历史会是什么样子，感觉很像 AI 的成长阵痛。社会需要打破旧习惯，解决那些早于 ChatGPT 的问题——这会释放大量能量和挫败感——才能挖掘长期增长潜力。扩散的故事将比对抗它的斗争漫长得多。我们所有关注这个故事的年轻人，将在有生之年看到强大的 AI 从实际上 0% 的采用率发展到 90% 以上的全面采用。这种深度集成于企业、充当个人助理等的 AI 才刚刚开始变得可行。它获得采用所需的时间将远长于像 ChatGPT 这样易于理解的应用，而这才是 AI 演进的真正标志。

Reflecting on what I expect the history of this era to look like, it feels a lot like growing pains of AI. Society needed to break out of old habits and work through problems that predate ChatGPT — which releases a lot of energy and frustration — in order to tap into the longer term growth. The diffusion story will take a lot longer than the fight against it. All of us younger folk following the story today will get to see powerful AI go from effectively 0% to 90%+ full adoption in our lifetime. This sort of AI that is deeply integrated in businesses, acting as personal assistants, etc. is just starting to become viable. It’ll take far longer to gain adoption than easier to understand applications like ChatGPT, and is the true marker of AI’s evolution.

从这个视角看，显而易见的是，持续推进技术至关重要——其益处将令人惊叹，但这些益处并非理所当然——我们还有大量非常艰巨的工作要做，以确保它们被广泛分配。

Taking this perspective makes it clear that it is crucial to keep progressing the technology — the benefits will be astounding, but they are not a given — and we have a lot of very hard work to do in making sure they’re distributed widely.

Fabricated Knowledge 的 Doug 也有一篇好文章谈到这一点：

Doug at Fabricated Knowledge had a good piece on this too:

Fabricated Knowledge Engels 的停顿与永久下层阶级 阅读更多 5 个月前 · 214 个赞 · 5 条评论 · Doug O'Laughlin

Fabricated Knowledge Engels' Pause and the Permanent Underclass Read more 5 months ago · 214 likes · 5 comments · Doug O'Laughlin