普通人何时才能感受到 AI 的影响？

许多人工智能乐观主义者倾向于将当前的人工智能热潮与工业革命或其他快速技术进步并传播到社会的时期进行比较。这些比较在技术变化的规模上是成立的，但忽略了一个关键因素，即大多数人如何接触到这种变化。人工智能面临的问题是，大多数人并没有因为人工智能而获得非常具体的新产品，而社会在抵制变革方面比以往任何时代都更具惯性。

分享：https://www.interconnects.ai/p/when-will-average-people-feel-ais?utm_source=substack&utm_medium=email&utm_content=share&action=share

我写这篇文章时刚从新英格兰几周的婚礼休假回来。在这段时间里，完全不去想人工智能也是很容易的。今天普通人接触人工智能产品的触点仍然是边缘的、有限受益的，或者对他们来说完全令人困惑（例如，很多人听说过甚至提到了 OpenAI-HuggingFace 事件，但不知道该如何理解）。正面的人们将人工智能视为制作趣味图片、增强谷歌搜索等工具。这些好处都很小。负面的人则联想到让人上瘾的社交媒体算法、沉迷于人工智能聊天机器人的朋友的朋友，以及对数据中心的各种评论。

日常生活的核心方面——家庭、食物、交通和娱乐——目前几乎还没有直接影响。跳出泡沫去观察现状，你会惊讶地发现如今发生的事情其实毫无多大意义。对人工智能的痴迷是一种选择，目前只有极少数人选择了这种路线。例如，在这段时间里，我使用人工智能的唯一用途就是搜索和创意工作（为我的婚礼宾客制作漂亮的座位图，让他们能找到自己的座位）。

在过去的工业革命中，普通人获得了彻底改变生活的成果。第一次工业革命：https://en.wikipedia.org/wiki/Industrial_Revolution 发生在18世纪晚期，使人们能够获得更便宜的衣物、炊具、阅读材料，并转向新的生计方式。第二次工业革命：https://en.wikipedia.org/wiki/Second_Industrial_Revolution 发生在19世纪晚期，引入了家庭机器（例如缝纫机）、保藏食物、室内管道系统、摄影、更好的光源、自行车，以及制造品和电气化的进一步好处。这个清单非常显著——我们今天仍然经常使用其中的大多数——而且这些都是非常具体的福利。

即便是最乐观版本的人工智能也将带来新的科学发现、罕见疾病的先进治疗方法，甚至可能带来持续的经济丰裕，但这些好处有风险会过于间接。

如果一个普通公民去看家庭医生，医生告诉他们一个新的奇迹疗法，那么他们又如何会将自己的生命得救归功于OpenAI或Anthropic呢？

美国人中有多少人会关心OpenAI解决Navier-Stokes 千禧年奖问题：https://x.com/OpenAI/status/2097374640582668336 ?

50年后，平均的美国人的日常生活看起来很可能与今天非常相似。他们的家、家用电器、人际关系和交通工具都会很相似（当然，自动驾驶会继续普及，但这一直是在与大型语言模型创新完全独立的轨迹上发展）。在这段时间里，人工智能将获得大量认可。考虑到今天这个以人工智能为中心的狭窄领域中一切变化的速度，50年是一个非常长的时间。

人工智能革命早期最重要的部分，是建立基础设施和一个总体流程，这将随着几十年的发展而产生积累效应。今天的一项重大数学突破，相对于后续积累过程中取得的进展，看起来在范围上可能微不足道。很难预测，每种你日常使用的技术因人工智能而获得更快复合改进时会呈现出什么样的情况。

关于人工智能的叙述在很大程度上试图让人们关心它，至少作为一种潜意识动机，这是由于长期的进步现实。这需要很长很长时间才能做好，而人工智能的发展由于这种不平衡而面临着立即的政治问题。

今天的人工智能主要是服务于精英的工具。对于知识工作——大约占美国经济的一半——人工智能和电力一样基本（或者很快会成为基本工具，在未来18个月内，代理技术会迅速改进）。只有让社会的一半人受益而拥有如此变革性、高生产力的工具是高度不稳定的。许多人很容易注意到这一点——技术经济蓬勃发展，而生活在其他方面却停滞不前。

在撰写本文时，我了解到恩格斯间歇期：https://en.wikipedia.org/wiki/Engels%27_pause，这是“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变革中迅速增长的时期。” 如果我们——人工智能行业的领导者——认为这是人工智能未来的最接近的类比，那么那些没有受益的人有理由进行反击。

人工智能是有史以来最伟大的工具，用于扩大科技公司规模和创建新的在线原生小型企业。我甚至不指望科技行业在人员数量上增长并在巨大的成功时期培养其工人——我同意Doug OLaughlin的观点：https://open.substack.com/users/108855261-doug-olaughlin?utm_source=mentions，认为人员数量可能会减少，而知识工作输出会爆炸性增长：https://www.fabricatedknowledge.com/p/mythos-and-engels-pause。这些行业已经是美国经济体系中最成功的，因此人工智能的品牌将被视为非集体利益。我担心这种本能反应会扼杀人工智能的发展，使其走上更接近美国核能警示故事的道路。

挑战的一部分在于社会对速度和不懈期望的要求。人工智能行业有数百万双眼睛在关注着它，不会有太多耐心去等待并在以后引入创新。如果给它100年的时间来扩散到社会中，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。

总体而言，AI行业正面临一些简单的问题，我会称之为50年扩散过程的前半个十年。

AI在其演化初期的积极影响过于间接。

AI正面临与西方社会大型科技公司历史密切交织的政治反弹。之所以这只是一个AI故事，是因为时机的关系，如果AI的指数增长是在今天像谷歌和Meta这样的技术平台经历成长痛苦之后几十年发生的，那么数据中心问题似乎不太可能成为如此核心的政治议题。

解决其中任何一个问题都能缓解相当大的压力，并给AI行业更多时间去展示为什么人们应该接受现状变化（主要是经济方面）的正面案例。这两者都因AI自我标记为负面和/或不安全技术而变得更加困难，通过末日预言和大规模失业的宣告体现出来。主要的行业人物已经开始处理这一问题，但公众还需要更多的工作来完全接受整体发展轨迹。

从长期来看，我可以预见机器人技术和自动驾驶将在叙事中与当前的AI革命紧密关联。如果大规模生成语言模型引发的智能爆炸确实溢出，并加速了机器人在日常生活中的应用，人类将很快关注到AI的切实利益。这很讽刺，因为许多人一直试图说服别人，LLM正在发生的事情与过去十年或二十年的通用AI进展非常不同。如果同样的动态后来拯救（或大幅超越）LLM，那将会很有趣。

回顾我对这个时代历史的预期，它感觉很像人工智能的成长阵痛。社会需要摆脱旧习惯，并解决早于 ChatGPT 出现的问题——这会释放大量的能量和挫折感——以便抓住长期增长的机会。技术扩散的故事将比与之抗争的过程花费更长的时间。我们这一代跟踪这一故事的年轻人，将在有生之年看到强大的 AI 从实际上 0% 到 90% 以上被全面采用。这种深度整合在企业中、充当个人助理等的 AI 才刚开始变得可行。它的推广比像 ChatGPT 这样更易理解的应用要更漫长，而它才是 AI 进化的真正标志。

从这个角度来看，很明显持续推进技术是至关重要的——其带来的好处将是惊人的，但并非理所当然——而我们必须付出大量艰苦努力，确保这些好处能广泛分布。

Fabricated Knowledge 的 Doug 对此也有一篇不错的文章：

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.

Share ：https://www.interconnects.ai/p/when-will-average-people-feel-ais?utm_source=substack&utm_medium=email&utm_content=share&action=share

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.

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).

In industrial revolutions past, average people got absolutely life changing outcomes. The First Industrial Revolution：https://en.wikipedia.org/wiki/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：https://en.wikipedia.org/wiki/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.

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.

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?

What percentage of Americans will care about OpenAI solving the Navier-Stokes Millennium Prize Problem：https://x.com/OpenAI/status/2097374640582668336 ?

It feels very likely in 50 years that the average American’s day to day life looks 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 with how fast everything is changing today in this, AI-focused narrow slice of the world.

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.

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.

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.

In writing this, I learned of Engels’ pause：https://en.wikipedia.org/wiki/Engels%27_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：#footnote-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 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 OLaughlin：https://open.substack.com/users/108855261-doug-olaughlin?utm_source=mentions that headcount would likely shrink while knowledge work output explodes：https://www.fabricatedknowledge.com/p/mythos-and-engels-pause . 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.

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.

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

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

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.

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.

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.

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.

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.

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