为什么人工智能对水管工可能比对程序员更有利

今天在AI每日简报中，为什么AI对水管工的重要性可能超过对程序员。

Today on the AI Daily Brief, why AI could matter more for plumbers than for programmers.

AI每日简报是一档每日播客和视频节目，聚焦AI领域最重要新闻与讨论。

The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

好了，朋友们。

Alright, friends.

在开始之前，先做几个快速公告。

Quick announcements before we dive in.

首先，感谢今天的支持方：Rackspace Technologies、Robots and Pencils、Blitzy 和 Super Intelligent。

First of all, thank you to today's sponsors: Rackspace Technologies, Robots and Pencils, Blitzy and Super Intelligent.

要获取无广告版本的节目，请访问 patreon.com/aideallybrief，或在Apple播客上订阅。

To get an ad free version of the show, go to patreon.com/aideallybrief or you can subscribe on Apple Podcasts.

无广告版本每月仅需3美元。

Ad free is just $3 a month.

如需了解赞助节目事宜，请发送邮件至 sponsorsaidailybrief dot ai。

To learn about sponsoring the show, send us a note at sponsorsaidailybrief dot ai.

当然，aideiallybrief.ai 是你可以了解我们这个项目生态系统的其他所有信息的地方。

And of course, aideallybrief.ai is where you can find out everything else about this ecosystem of projects that we have as well.

今天我们要探讨的主题，我认为将在今年成为日益重要的议题。

Today we're exploring a theme which I think is going to be a growing topic throughout the year.

简而言之，就是人工智能将如何影响蓝领工人，不仅可能扩大他们的群体规模，还可能改变他们经营业务的方式。

In short, it's what sort of impact AI is going to have on blue collar workers, both in terms of swelling their ranks, as well as potentially changing the nature of how they run their businesses.

随着我们更深入地进入人工智能变革阶段，并开始更清晰地看到 AI 可能如何影响就业市场，尤其是短期内的影响，这一话题正日益受到关注。

This is a topic that is growing as a focus, particularly as we get farther into the AI change and we start to get better glimpses of how AI might actually impact the jobs market, especially in the short term.

需要明确的是，我依然完全不确定未来会是什么样子。当然，这是一期长篇深度思考的节目，而直接触发这一话题的，是《财富》杂志上大卫·海科克的一篇评论文章。

To be clear, I think we still have absolutely no idea what things are going to look like in the future, Now this is of course a long readbig think episode, and the specific catalyst for this was an op ed in Fortune magazine by David Haycock.

大卫是 Filterbuy 的首席执行官兼创始人，这是一家面向消费者的空气过滤产品公司。

David is the CEO and founder of Filterbuy, which is a direct to consumer air filtration company.

Filterbuy 年收入超过十亿美元，拥有七百万以上客户，并雇用了上千名员工。

Filterbuy generates over a billion dollars in revenue, has more than 7,000,000 customers, and employs over a thousand people.

这家公司也完全是自筹资金发展起来的。

The company was also fully bootstrapped.

大卫本人的经历非常有趣。

Now, David himself has an interesting path.

他职业生涯初期在高盛担任期权交易员，但2012年他离开华尔街，接手了家族的滤网制造业务。

He started his career as an options trader at Goldman Sachs, but in 2012 he left Wall Street to take over the family business which was this filter manufacturing business.

因此，这篇文章的标题是《我是一名将一家枯燥的空气过滤器企业打造成2.6亿美元公司的CEO》。

So the piece is titled I'm a CEO who grew a boring air filter business into a $260,000,000 company.

人工智能将帮助像我这样的普通蓝领工人。

And AI is going to help blue collar everyday people just like me.

这仅仅是我在这一主题上看到的最新案例，所以先让我们读一下这篇文章，它并不长，然后再深入探讨更广泛的背景。

Now this is just the latest in this theme that I've seen, so first let's read this piece it's not all that long and then we'll get into the broader context.

大卫写道：当我13岁的时候，我曾兼职为本地企业搭建网站。

David writes: When I was 13, I had a side hustle building websites for local businesses.

那是1990年代。

This was the 1990s.

搭建一个网站意味着要花几周时间通过拨号上网，逐行手写HTML代码，而且只要漏掉一个字符，布局就会崩溃。

Building a site meant weeks on a dial up connection, hand coding HTML line by line, and breaking layouts because you missed a single character.

如果我在夏天赚了2000美元，那是因为我几乎放弃了所有醒着的时间来做这件事。

If I made $2,000 in the summer, it was because I gave up nearly every waking hour to do it.

我的收入受限于我能工作的速度。

My income was capped by how fast I could work.

就在那段时间，我祖父给了我一些建议，我至今仍常常回想：专注于打造人们真正需要的东西。

Around that same time, my grandfather gave me advice that I still come back to: focus on building something people actually need.

他一生都在经营一家真正的企业，服务真正的客户，对那些无法解决明确问题的潮流毫无耐心。

He had spent his life running a real business, serving real customers, and he had little patience for trends that didn't solve a clear problem.

几年后，当我探索不同的产品想法时，我会拿去给他看。

Years later, when I was exploring different product ideas, I ran them by him.

有些想法很花哨。

Some were flashy.

还有一个甚至是要做运动鞋。

One was even sneakers.

他礼貌地听着。

He listened politely.

然后我告诉他我正在考虑做空气净化器。

Then I told him I was thinking about air filters.

他凑近了过来。

He leaned in.

空气净化器很有道理。

Air filters made sense.

人们需要它们。

People need them.

它们不令人兴奋，但很重要。

They're not exciting, but they matter.

他的反应告诉我，我找到了一个对的方向。

That reaction told me I was onto something.

如今，我经营着FilterBuy，一家年产值2.6亿美元的国内制造公司，生产和配送全国范围的空气净化器。

Today I run FilterBuy, a $260,000,000 domestic manufacturing company that makes and ships air filters across the country.

回顾过去，那段早期经历教会了我一个大多数人至今仍忽视的道理：努力的回报是有限的，但杠杆效应会复利增长。

Looking back, that early experience taught me something most people still miss: Effort scales poorly, but leverage compounds.

这就是为什么我认为许多领导者误解了人工智能对经济的真实意义。

That's why I think many leaders are misreading what AI actually represents for the economy.

大多数高管关于人工智能的讨论都集中在风险、监管或成本削减上。

Most executive conversations about AI focus on risk, regulation, or cost reduction.

这些确实是合理的担忧，但它们忽略了更大的转变。

Those are valid concerns, but they miss the larger shift.

人工智能的主要目的并不是取代工人或削减人员编制。

AI isn't primarily about replacing workers or cutting headcount.

而是关于谁获得杠杆效应。

It's about changing who gets leverage.

在美国历史的大部分时间里，杠杆效应掌握在那些能雇佣大量团队、筹集资金或开发软件的人手中。

For most of American history, leverage belonged to people who could hire large teams, raise capital, or build software.

其他人则用时间换取金钱。

Everyone else traded time for money.

现在这种情况正在改变，而最大的受益者将不会是程序员。

That's now changing and the biggest beneficiaries won't be programmers.

他们将是那些经营实际非科技业务的人。

They'll be people running practical, non tech businesses.

想想今天一个小服务经营者是什么样子。

Consider what a small service operator looks like today.

水管工、暖通空调技术员或本地制造商花费了大量时间在与核心技能无关的工作上：安排工作、发送发票、跟进客户、预测需求。

A plumber, HVAC technician, or local manufacturer spends a surprising amount of time on work that has nothing to do with their core skill: scheduling jobs, sending invoices, following up with customers, forecasting demand.

这些任务并不难，但会制造摩擦。

Those tasks aren't hard but they create friction.

随着时间推移，这种摩擦限制了增长。

Over time, that friction caps growth.

AI并没有消除这些行业中对熟练劳动力的需求，而是消除了围绕它的拖累。

AI doesn't eliminate the need for skilled labor in those businesses it removes the drag around it.

使用AI处理派工、报价、客户沟通和跟进的水管工，不再受文书工作或漏接电话的限制。

A plumber who uses AI to handle dispatching, estimates, customer communication, and follow ups is no longer limited by paperwork or missed calls.

这位经营者可以用同样的团队服务更多客户，减轻压力，经营更顺畅的业务。

That operator can serve more customers with the same crew, reduce stress, and run a cleaner business.

工作本身没有变，但规模变了。

The work itself doesn't change the scale does.

这就是为什么我认为AI对水管工的重要性超过对程序员的重要性。

That's why I believe AI matters more to plumbers than programmers.

在科技领域，AI通常改进的是本来就容易扩展的东西。

In tech, AI often improves something that already scales well.

在实体业务中，它彻底改变了游戏规则。

In physical businesses, it changes the math entirely.

它让一位有能力的经营者能够管理过去需要多层员工或外部供应商才能处理的复杂事务。

It allows one capable operator to manage complexity that used to require layers of staff or outside vendors.

你不再需要随着收入增长而快速增加人员。

You're no longer growing by adding people as fast as revenue.

你是通过消除瓶颈来实现增长的。

You're growing by removing bottlenecks.

我们在FilterBuy公司已经亲眼见证了这一点。

We've seen this firsthand at FilterBuy.

我们并没有用技术来取代工厂车间的员工。

We didn't use technology to replace people on the factory floor.

我们用它来解决排程问题、改善预测、减少错误并加快决策速度。

We used it to clean up scheduling issues, improve forecasting, reduce errors, and speed up decision making.

价值并非仅仅来自自动化。

The value didn't come from automation alone.

而是来自为我们的团队提供更好的工具和更少的障碍。

It came from giving our team better tools and fewer obstacles.

我认为许多关于AI的讨论都错在这里。

That's where I think many AI discussions go wrong.

它们关注的是新颖性而非落地，关注的是愿景演示而非日常运营。

They focus on novelty instead of deployment, on vision decks instead of daily operations.

在非科技行业，机会不在于打造炫目的东西，而在于默默消除阻碍优秀企业发展的障碍。

In non tech industries the opportunity isn't to build something flashy it's to quietly remove the friction that holds good businesses back.

这对高管层有深远影响。

This has implications for the C suite.

错误的问题是：我们如何用人工智能降低成本？

The wrong question is How do we use AI to cut costs?

更好的问题是：我们如何用人工智能让我们的员工更高效？

The better question is How do we use AI to make our people more effective?

如果你有100名员工，目标不应该是减少到80人，而应该是让这100个人以更高的水平运作。

If you have 100 employees, the goal shouldn't be to get to 80 it should be to allow those 100 people to operate at a higher level.

持久的价值正是在这里创造的。

That's where durable value is created.

做得好的公司外表上看不会截然不同，它们只是比其他人执行得更好。

Companies that do this well won't look radically different from the outside they'll just execute better than everyone else.

我们正进入一个阶段，人工智能不再是一个话题，而开始成为基础设施。

We're entering a phase where AI stops being a topic and starts being infrastructure.

它不会单独存在于一份战略演示文稿中。

It won't sit in a separate strategy deck.

它会体现在实际工作是如何完成的。

It will show up in how work actually gets done.

排程将更紧凑，决策将更快，较少的事情会遗漏。

Scheduling will be tighter, decisions will be faster, fewer things will fall through the cracks.

我职业生涯一直专注于实体商品和所谓的传统行业，因为真正的经济价值正是在这些领域构建的。

I've spent my career leaning into physical goods and so called boring businesses because that's where real economic value is built.

AI是我所见过的第一个真正将杠杆作用转向那些在这些领域运营的人的工具。

AI is the first tool I've seen that meaningfully shifts leverage towards people who operate in that world.

互联网让我们获得了信息的访问权。

The internet gave us access to information.

AI正在为我们提供运营杠杆的访问权。

AI is giving us access to operational leverage.

对于那些愿意在实际发生工作的地方——而非仅在看起来令人印象深刻的地方——应用AI的领导者来说，回报是实实在在的。

For leaders willing to apply it where work actually happens, not where it looks impressive, the upside is real.

获胜的公司不会是最大声宣扬AI的那些。

The companies that win won't be the loudest about AI.

它们将是那些默默使用AI来运营更高效企业的公司。

They'll be the ones quietly using it to run better businesses.

好吧，我们回到NLW的话题。

All right, so back to NLW here.

当然要感谢大卫写了这篇文章。

Thanks of course to David for writing that.

其中实际上包含了几个不同的观点。

And there are actually a couple different ideas going on in there.

其中一个观点适用于所有人。

One of them is applicable to everyone.

这不仅仅关乎蓝领工作。

It's not just about blue collar.

而是关于任何领导者如何理解AI的问题。

It's about the idea of how to conceptualize AI for any leader.

大卫的观点是，从长远来看，把AI视为一种降低成本的技术是错误的，而将其视为一种创造机会的技术才是正确的。

David's argument is that the losing way in the long term of looking at AI is as a cost cutting technology and the winning way in the long term is looking at it as an opportunity creation technology.

我们总是从效率型AI和机会型AI的角度来讨论这个问题。

We always talk about this in the context of efficiency AI versus opportunity AI.

大卫将这一观点应用到企业领导者身上，他们需要为自身的AI计划设定目标。

David is applying that to the mindset of corporate leaders who need to set goals for what their AI initiatives are supposed to achieve.

他所应用的‘团队成员可以获得更多杠杆效应’这一理念，并不仅限于现实中的体力或蓝领行业。

The lessons that he's applying the idea that team members can have more leverage isn't just restricted to real world physical or blue collar businesses.

这一理念适用于任何人。

It's available for anyone.

所有这些都完全正确。

And all of that is 100% true.

但我想要探讨的是现实物理世界中的企业背景，尤其是那些比大卫在文中描述的还要小得多的企业。

But the part that I want to explore is the context of physical real world businesses and ones I think that are much smaller than even those being described by David in this piece.

AI之所以令人着迷，原因之一在于它打破了过去几百年来的趋势——以往新技术变革往往首先冲击蓝领工人，至少在负面影响方面是如此。

One of the things that makes AI so interesting is that it breaks the trend of the last couple hundred years where new technology changes tended to hit blue collar workers first at least the negative side.

而如今我们看到，最具实际影响的颠覆性变化实际上发生在白领岗位上。

Right now what we're seeing is that the places where the most realized disruption is happening is in fact in white collar roles.

人们对程序员自身角色的看法，正在发生变化。

The way that people think about programmers themselves, for example, is changing.

我认为，这一切最终会如何发展，目前还很难下定论。

Now I think the jury is very much still out on how that all shakes out.

我们正经历一个充满AI岗位替代担忧的时期，确实也出现了相当多的岗位流失，但这些流失显然不仅仅是由AI引起的，还有其他多种因素在起作用。

We're going through a period where there's a lot of AI job displacement concern and a fair bit of job displacement, but job displacement that clearly has a lot of other factors going on besides just AI.

另一点是，尽管AI能够完成程序员过去所做的工作，但我最基本的判断仍然是，最终我们会看到编程岗位大幅增加，而不是简单地解雇所有现有的程序员。

The other thing is, of course, even though AI can do the work that programmers used to do, my base case is still that we end up with radically more programming jobs versus everyone just firing the programmers they have access to.

但要看到这一切如何发展，还需要时间。

But it will take time to see how that all shakes out.

好了，朋友们，我们短暂休息一下，来谈谈一个我经常被问到的问题：如何在不被基础设施决策压垮的情况下，真正从AI实验走向生产落地？

Alright friends, quick break to talk about a question I hear constantly: How do you actually move from AI experimentation to production without getting buried in infrastructure decisions?

这就是Rackspace AI Launchpad的用武之地。

That's where Rackspace AI Launchpad comes in.

它是一个全托管服务，旨在通过循序渐进的指导方式，帮助企业构建、测试和扩展AI工作负载。

It's a fully managed service designed to help enterprises build, test, and scale AI workloads through a guided, phased approach.

借助AI Launchpad，Rackspace负责管理基础设施、GPU和核心工具，让团队能够专注于验证应用场景，而不是从零开始搭建环境。

With AI Launchpad, Rackspace manages the infrastructure, GPUs, and core tooling so teams can focus on validating use cases instead of building environments from scratch.

你从一个概念验证开始，进入实际试点，然后在托管的企业级GPU基础设施上扩展至生产环境。

You start with a proof of concept, move into a real pilot, and then scale into production on managed, enterprise grade GPU infrastructure.

无论你是测试边缘推理、微调基础模型，还是搭建生产流水线，目标都是一样的：以更少的操作阻力实现更快的进展。

Whether you're testing inference at the edge, fine tuning foundation models, or standing up a production pipeline, the goal is the same: faster progress with less operational friction.

如果你已准备好超越演示，真正将AI投入应用，请了解一下Rackspace AI Launchpad，看看托管式生产路径如何加速成果落地。

If you're ready to move beyond demos and actually put AI to work, take a look at Rackspace AI Launchpad and see how a managed path to production can accelerate results.

访问 rackspace.com/ailaunchpad 了解更多信息。

Visit rackspace.com/ailaunchpad to learn more.

大多数公司并不缺乏创意。

Most companies don't struggle with ideas.

他们的问题在于如何将这些创意转化为真正创造价值的AI系统。

They struggle with turning them into real AI systems that deliver value.

Robots and Pencils 是一家致力于弥合这一差距的公司。

Robots and Pencils is a company built to close that gap.

他们设计并交付以生成式与代理式AI驱动的智能云原生系统，注重专注力、速度和明确的成果。

They design and deliver intelligent, cloud native systems powered by generative and agentic AI, with focus, speed, and clear outcomes.

Robots and Pencils 以小型、高影响力的团队开展工作。

Robots and Pencils works in small, high impact pods.

工程师、战略家、设计师和应用AI专家协同合作，从创意快速推进到生产，避免不必要的障碍。

Engineers, strategists, designers, and applied AI specialists working together to move from idea to production without unnecessary friction.

借助他们的Identic加速平台Roboworks，团队能够交付切实成果，根据项目范围，首次上线最快仅需四十五天。

Powered by Roboworks, their Identic Acceleration Platform, teams deliver meaningful results including initial launches in as little as forty five days depending on scope.

如果您的组织准备加快步伐、降低复杂性，将AI愿景转化为实际成果，Robots and Pencils 正是为此刻而打造的。

If your organization is ready to move faster, reduce complexity, and turn AI ambition into real results, Robots and Pencils is built for that moment.

请访问 robotsandpencils.com/aideallybrief 开始对话。

Start the conversation at robotsandpencils.com/aideallybrief.

网址是 robotsandpencils.com/aideallybrief。

That's robotsandpencils.com/aideallybrief.

Robots and Pencils 的 Impact at Velocity Weekends 专为氛围编程而设。

Robots and Pencils Impact at Velocity Weekends are for vibe coding.

将热情项目变为现实从未如此简单，去启动你最爱的氛围编程工具吧。

It has never been easier to bring a passion project to life, so go ahead and fire up your favorite vibe coding tool.

但周一就要来了，不知不觉中，你将面对一个由微服务组成的迷宫、一个来自1970年代的遗留COBOL系统，以及一条会延续到你退休派对之后的工程路线图。

But Monday is coming, and before you know it you'll be staring down a maze of microservices, a legacy COBAL system from the 1970s, and an engineering roadmap that will exist well past your retirement party.

这就是你需要Blitzy的原因——首个专为企业级代码库设计的自主软件开发平台。

That's why you need Blitzy, the first autonomous software development platform designed for enterprise scale codebases.

在每个冲刺周期的开端部署工作，让你的路线图推进速度提升500%。

Deploy the beginning of every sprint and tackle your roadmap 500% faster.

Blitzy的智能代理会读取你的整个代码库，规划任务，并实现超过80%的自主交付。

Blitzy's agents ingest your entire codebase, plan the work, and deliver over 80% autonomously.

以计算速度交付经过验证、端到端测试、高品质的代码。

Validated, end to end tested, premium quality code at the speed of compute.

数月的工程工作被压缩至数天之内。

Months of engineering compressed into days.

周末用 vibe coding 实现你的热情项目。

Vibe code your passion projects on the weekend.

周一把 Blitzy 带到工作中。

Bring Blitzy to work on Monday.

了解为什么《财富》500强企业信赖Blitzy来处理关键代码，访问blitzy.com。

See why Fortune 500s trust Blitzy for the code that matters at blitzy.com.

那就是blitzy.com。

That's blitzy.com.

本期节目由Superintelligent赞助。

Today's episode is brought to you by Superintelligent.

Superintelligent是一个平台，简单来说，它的目标是帮助您的公司更好地运用人工智能。

Superintelligent is a platform that very simply put is all about helping your company figure out how to use AI better.

我们部署语音代理，对公司内部人员进行访谈，结合其他公司成功实践的专有洞察，为您提供一系列关于应用场景和变革管理举措的建议，从而形成一份能帮助您从人工智能中获取价值的AI路线图。

We deploy voice agents to interview people across your company, combine that with proprietary intelligence about what's working for other companies, and give you a set of recommendations around use cases, change management initiatives that add up to an AI roadmap that can help you get value out of AI for your company.

但现在，我们希望为公司内部负责这一转型的团队提供一个更直接的平台。

But now we want to empower the inside your team who are responsible for that transformation with an even more direct platform.

我们即将推出的AI战略指南工具现已准备就绪，即将开始测试。

Our forthcoming AI Strategy Compass tool is ready to start to be tested.

这是任何负责公司内部AI采用或AI转型人员的强力工具。

This is a power tool for anyone who is responsible for AI adoption or AI transformation inside their companies.

它将让你以一种更自动化、自我管理的方式，完成我们在超级智能公司所做的许多事情，并且拥有完全不同的成本结构。

It will allow you to do a lot of the things we do at Super Intelligent, but in a much more automated, self managed way, and with a totally different cost structure.

如果你有兴趣试用，请访问 aidailybrief.aicompass，填写表格，我们会尽快与你联系。

If you are interested in checking it out, go to aidailybrief.aicompass, fill out the form, and we will be in touch soon.

我认为大卫说得对，AI 赋予了那些善于运用它的人更大的杠杆效应。

I think David is right to point out that AI gives the people who choose to wield it well way more leverage.

而这种杠杆效应，在蓝领企业手中可以变得极其强大。

And it's leverage that in the hands of blue collar businesses can be incredibly powerful.

目前，关于 AI 与蓝领工作之间关系的讨论实际上有很多不同的声音。

Now, there are actually a lot of different conversations happening right now when it comes to the relationship between AI and blue collar work.

首先，由于 AI 数据中心的建设，对蓝领工人的需求实际上增加了。

First of all, there is just simply put more demand for blue collar workers because of the AI data center build out.

去年九月，福特首席执行官吉姆·法利警告称，我们在建筑和维护等领域根本缺乏足够的熟练工人。

Last September, Ford CEO Jim Farley warned that we simply didn't have enough skilled workers in areas like construction and maintenance.

法利表示：‘意愿是有的，但没有人能填补这种雄心的空缺。’

Said Farley, I think the intent is there, but there's nothing to backfill the ambition.

如果我们没有足够的人手在那里工作，我们如何能将这些产业全部回流？

How can we reshor all this stuff if we don't have the people to work there?

这些评论发表之际，法利实际上在底特律主办了一场名为'加速基础经济'的峰会，该峰会完全致力于扩大这些技术型基础工人的输送渠道。

These comments came as Farley actually hosted a summit in Detroit called Accelerate the Essential Economy that was all about expanding the pipeline of these skilled essential workers.

在一篇博客文章中，法利估计美国...

In a blog post, Farley estimated that The U.

（此处应为'U.S.'的延续，但原文独立成句，故译为'美国'以保持结构对应）

S.

还需要60万名制造业工人、50万名建筑工人和40万名汽车技师。

Needed 600,000 more manufacturing workers, 500,000 more construction workers, and 400,000 more automotive technicians.

法利说，这看起来是人的问题，但实际上没那么简单。

Farley said, It looks like a people problem, but it's actually not that simple.

这是一个认知问题。

It's an awareness problem.

这是一个社会问题。

It's a societal problem.

如果我拿一个典型的美国家庭来问：你希望你的孩子当一名年薪17万美元的软件程序员，还是当一名年薪9.7万美元的暖通空调技术员，你会更倾向于哪一个？

If I were to take the typical American family and say, Would you rather your kid be a software programmer making $170,000 or be an HVAC specialist to make $97,000 which one would you prefer?

我会说，许多美国人都会更倾向于选择软件工程师。

I would say, Many, many Americans would prefer the software engineer.

然而，呼吁增加蓝领工人的人数，声音却一直在不断变大。

And yet, the steady drumbeat of people calling for more blue collar workers just continues to get louder and louder.

最近在世界经济论坛上，英伟达首席执行官黄仁勋认为，蓝领工作的价值将会提升。

Recently at the World Economic Forum, NVIDIA CEO Jensen Huang argued that the value of blue collar work would increase.

部分原因在于，他看到了许多新兴的蓝领岗位，这些岗位将体力劳动与数字和人工智能工具相结合。

Partially that's because he sees entire new categories of blue collar work in roles that mix physical work with digital and AI tools.

想想数据中心技术员、操作先进制造设备的工人，或者像法利提到的那些负责能源和基础设施建设的团队。

Think about data center technicians, workers who deal with advanced manufacturing equipment, or like Farley was talking about, the teams responsible for the energy and infrastructure build out.

有趣的是，Z世代似乎正在积极响应这一号召。

Now what's interesting is that Gen Z kind of seems to be taking up the call.

尽管法利关于家庭对孩子职业偏好的说法在某些地区可能是对的，但一种文化上的转变正在悄然发生。

And while Farley's comments about what families would prefer for their kids might be true in some areas, there is a bit of a cultural shift underway.

去年七月，HR Dive 发表了一篇题为《对人工智能的焦虑促使千禧一代转向蓝领工作》的文章。

Last July, HR Dive wrote a post called Anxiety about AI Drives Gen Z Career Pivot to Blue Collar Work.

这篇文章聚焦于职业网站Zeti最近发布的一项调查。

The article focused on a survey that had come out recently by career website Zeti.

这项调查针对1000名千禧一代工作者，结果清晰显示，他们正在重新评估什么是安全的职业。

It was a survey of 1,000 Gen Z workers, and it was very clear that they were in the midst of a re evaluation of what a safe career looked like.

近四分之三的受访者认为，未来五年内人工智能将减少初级企业岗位。

Almost three in four of those surveyed thought that AI would reduce entry level corporate jobs over the coming five years.

与此同时，许多受访者将技术工种和体力劳动，以及医疗、教育等以人为中心的职业，列为相对更不易被人工智能取代的工作。

Meanwhile, many of the respondents ranked skilled trades and labor, as well as people focused professions like healthcare and education, as among those jobs that were relatively more AI proof.

调查还发现，人们对大学学位的怀疑正在增加。

The survey also found a growing skepticism of college degrees.

在Zeti的这份报告中，65%的受访者认为大学学位无法保护他们免受人工智能导致的失业影响。

In that Zeti report, 65% of respondents thought that college degrees wouldn't protect them from AI related job loss.

这让人回想起Indeed在四月发布的一项报告，该报告发现约有一半的受访者认为新技术使他们的大学教育变得无关紧要。

That harkened back to an Indeed report from April that found about half of the respondents thought that new technology made their college education irrelevant.

由于这一切，开始出现向蓝领或技术型职业的转向。

Because of all this, there's the start of a reorientation towards blue collar or skilled trade jobs.

另一项调查来自Resume Builder，时间是2025年5月，发现42%的Z世代受访者目前从事或正在追求蓝领或技术型工作，尽管其中超过三分之一的人拥有学士学位。

Another survey, this time from Resume Builder back in May '25, found that 42% of its Gen Z respondents were either currently working in or pursuing a blue collar or skilled trade job, even though more than a third of them had bachelor's degrees.

但这并不意味着人们对这种转变普遍感到兴奋。

Which is not to say that there was universal excitement about this shift.

HR Dive总结道：尽管Z世代对蓝领工作的某些方面感到兴奋，比如更高的薪资、更多的就业机会和更大的灵活性，但他们也指出体力劳动强度大、职业晋升空间有限以及对技术行业缺乏了解仍是面临的挑战。

HR Dive summarized: While Gen Z said they were excited about certain elements of blue collar work such as higher pay, more job opportunities, and greater flexibility, they cited physical labor demands, concerns about upward mobility, and lack of awareness about trades as challenges that remain.

然而，尽管存在这些问题，这种趋势仍在持续增长。

And yet in spite of that, this narrative continues to grow.

今年9月，《福布斯》发表了一篇题为《当人工智能席卷白领世界，蓝领工作迎来复兴》的评论文章。

In September, Forbes published an op ed called As AI Sweeps the White Collar World, Blue Collar Works Sees a Renaissance.

这篇评论的触发点是Jobber公司不久前发布的报告《Z世代与蓝领革命》。

That essay had as its catalyst a then recent report from Jobber called Gen Z and the Blue Collar Revolution.

从这份报告中，最明确的一点是，即使技术型职业并非他们的答案，让职业免受人工智能冲击，依然是年轻一代最关注的议题。

If one thing is super clear from that report, it's that even when skilled trades are not their answer, AI proofing careers is very much at the top of minds for the younger generations.

63%的Z世代父母表示，人工智能使年轻人更难进入职场，77%的Z世代认为选择一份难以被自动化的职业对他们来说很重要。

Sixty three percent of Gen Z parents said that AI was making it harder for young people to break into the workforce, and 77% of Gen Z said it was important to them to choose a career that was difficult to automate.

如今，只有16%的Z世代父母认为大学学位能保证长期的工作保障。

Only 16% of Gen Z parents now believe a college degree guarantees long term job security.

对于人生中最大的开销之一来说，这个比例已经低得微不足道。

That is a vanishingly small number for one of the biggest expenses of people's lives.

近72%的父母表示，他们会与孩子讨论自动化可能对他们的职业产生的影响，56.7%的父母认为人工智能将在未来十年显著改变可用的工作类型。

Nearly 72% of parents said that they'd talk to their children about how automation might impact their careers, and 56.7% of parents said that they believed that AI would significantly change the types of jobs available over the next ten years.

近三分之一（29.6%）的父母认为，蓝领或动手类工作比办公室工作更不容易受到人工智能的影响，近40%的父母表示，如果能增强抵御人工智能的能力，他们会积极鼓励孩子选择职业培训路径。

Nearly a third as well 29.6% said that they believed that blue collar or hands on jobs were safer from AI than office jobs, and nearly 40% said that they would actively encourage a vocational path if it meant AI resilience.

对我来说，这里发生了巨大的转变：如今只有16%的Z世代父母认为大学学位能保护孩子免受人工智能引发的就业冲击。

Here's the dramatic shift to me: only 16% of Gen Z parents now think a college degree protects kids from AI related job disruption.

与此同时，73%的人认为，技术型创业者比大型科技公司的员工拥有更强的长期保障。

Meanwhile, 73% say they believe a trade entrepreneur has more long term security than a tech employee at a major company.

我认为，技术型创业这一理念非常重要。

And I think that idea of trade entrepreneurship is really important.

越来越明显的是，年轻一代及其父母都意识到，创业不仅仅意味着风险，也意味着韧性。

Increasingly, it's clear that the younger generations and their parents understand that entrepreneurship isn't just about risk it's also about resilience.

62%的Z世代父母表示，技术工作可以提供创业机会，62.1%的人表示，如果他们的孩子成为技术工人，他们会感到自豪。

Sixty two percent of Gen Z parents said that trade jobs can offer entrepreneurial opportunities, and 62.1% said that they would be proud if their child became a tradesperson.

好吧，让我们来把这些数据加总一下。

Okay, so let's start to add this up.

首先，AI带来的变化正在改变人们对白领工作稳定性和安全性看法，这使得人们更倾向于蓝领和技能型职业，而人们也逐渐认识到，这些职业本身就是创业和自主命运的途径。

We've got first the shifting sands that AI represents changing people's perceptions of the durability and safety of white collar jobs, which is making people more favorably inclined towards blue collar and skilled trade jobs, which then people are also recognizing are vehicles for entrepreneurship and self destiny.

这就引出了蓝领与AI对话的第二部分：不仅在于AI为何推动人们转向技术行业，更在于技术从业者如何利用AI来提升自身成果。

And that gets us to the second part of this blue collar AI conversation, which is not just why AI is driving people to the trades, but how people in the trades can use AI to increase their outcomes.

或者像我们之前听到的戴维所说的，他们如何利用AI来增强自己的影响力。

Or, as David put it in that first piece that we heard, how they can use it to increase their leverage.

目前，AI在蓝领工作中的渗透仍处于初期阶段。

Now at this stage, AI's penetration into blue collar work is still fairly nascent.

一项在芬兰进行的调查显示，仅有约四分之一的蓝领工会成员表示他们在工作中使用过AI。

One survey in Finland found that only around a quarter of union members in blue collar occupations said that they had used AI at work.

尽管有60%的人表示他们在工作之外使用过人工智能。

That was even though 60% said that they had used AI outside of the workplace.

不过，有三分之一的人认为他们在工作中有更大的应用人工智能的空间。

A third, though, said that they felt there was greater scope for using AI in their work.

那么，人工智能可能会如何进入技工行业呢？

So how might AI make it into trades professions?

我认为有几种途径。

I think there are a couple paths.

首先，我们现在生活在一个开放爪的世界里。

First of all, we are now living in an open claw world.

尽管有人可能会因为怀疑这一尚处于早期极客采用阶段的技术——比如为自己的小代理设置Mac Mini所伴随的技术负担——而认为它不太可能对白领或蓝领职业的大多数人产生影响，但这种状况不会持续太久。

And while one would be forgiven for rightly being skeptical that this very nascent hacker early adoption phase is likely to impact many people at all in white collar professions or blue collar professions given the technological burden that comes along with setting up your Mac Mini for your little agent, this state of affairs is not going to last long.

开放爪并不是一个孤立的现象。

Open Claw is not an isolated phenomenon.

相反，它是向代理型经济过渡过程中的一个里程碑。

It is instead the waypoint in our transition to an agentic economy.

现在你已经可以看到许多公司正在竞相简化OpenClaw在非技术人员中的实施。

Already you can find so many companies that are racing to simplify implementation of OpenCLaw for less technical folks.

这将极大地加速能够为人们做真正有用事情的智能代理的产品化进程。

That is going to radically hasten the productization of agents that can actually do useful things for people.

尽管我们仍在探索适用于不同场景、人群、工作和角色以及公司类型的精确用例，但即使从我自己的实验来看，我也很清楚这绝非空谈。

And while we are still figuring out the exact use cases that work for different contexts and settings and people and jobs and roles and types of companies, it's pretty clear to me even from my own experiments that this is not a nothingburger.

更重要的是，我认为许多OpenClaw用户目前正在尝试的通用助手类用例，恰恰可能对贸易创业者极为有用。

And what's more, I think a lot of the general assistant type of use cases that many OpenClaw users are experimenting with right now might be exactly the type that are incredibly useful for trade entrepreneurs.

邮件管理、日程管理、移动中的问题排查——这些正是这一代智能代理真正擅长的事情。

Email management, calendar management, on the go problem triage These are all things that this new generation of agents actually does quite well.

而这正是那些在时间上受制于大量现实物理约束的人们所需要的。

And it's exactly the type of things that could be useful for folks who have a lot of real world physical constraints on their time.

但这一领域还有另一个层面。

But there's another dimension of this as well.

AI时代带来的另一个影响是，开发软件的成本正在急剧下降。

One of the other impacts of the AI era is that the cost of building software is coming down dramatically.

但这并不意味着我会预期大量贸易创业者会为自己开发应用程序，尽管确实会有一些人这么做。

Now that does not mean that I expect to trade entrepreneurs en masse to build applications for themselves, although certainly some will.

相反，我认为这意味着，那些过去被认为对软件开发者来说太小而缺乏吸引力的市场，突然间变得非常有吸引力。

Instead, what I think it means is that markets that would have previously been seen as too small for people who build software to be interested in all of a sudden start to look really interesting.

为某个特定贸易类别开发专用软件？

Dedicated software for a niche trades category?

如果你不需要数百万美元的风险投资来构建它，它突然间看起来可能是一个非常有前景的机会。

If you don't need millions of dollars from a venture capitalist to build it, all of a sudden looks like it could be a really interesting opportunity.

我预计会看到大量专为解决特定类别贸易工作者具体问题而设计的、高度聚焦的应用程序蓬勃发展和复兴，而这得益于使用AI构建成本的降低。

I would expect to see an absolute flourishing and renaissance in dedicated, highly focused applications that are designed to solve the specific problems of specific categories of trades workers enabled by the reduced cost profile of building with AI.

而且同样地，由于这些公司是由没有风险投资人所要求的成果约束的小型创业团队所建立的，这也改变了他们所采用的商业模式。

And once again, because those companies are built by small entrepreneurial teams who don't have the constraints of the types of outcomes that a venture capitalist needs to see, that also changes the nature of the business model that they put into practice.

我认为这可能会降低这些贸易工作者和贸易创业者所面临的服务成本。

Which I think probably brings down the cost profile for those tradespeople and trades entrepreneurs.

但这并不意味着AI对蓝领工作没有威胁。

Now none of this is to say that there aren't threats from AI for blue collar work as well.

我们正处于具身人工智能时代的初期，有许多大型风险投资支持的公司正在努力开发功能强大的人形机器人，以完成如今蓝领工人所做的工作。

We are at the very beginning of the era of embodied AI and there are plenty of companies big venture backed companies that are trying to build highly capable humanoid robots that can do things that blue collar workers do now.

完全忽视这种风险是天真的。

It would be Pollyanna's to write off that risk entirely.

但我觉得，与软件AI带来的颠覆如今已经发生不同，我们在真正理解具身AI的经济模式之前，还有很长的路要走。

But I think whereas much of the disruption from software AI is here right now, we have a long way to go before we know exactly how the economics of embodied AI really work out.

例如，人们往往认为机器人相比人类的成本更低是唯一重要的因素。

For example, people tend to think that the reduced cost of a robot compared to a human is the only factor that matters.

但我认为，人类更倾向于让其他人来帮助自己完成所需事务，这种偏好将成为比人们预期高得多的障碍。

But I think human preference to have other humans helping them with the things that they need is going to be a dramatically higher barrier than people are anticipating.

无论如何，重点并不是我们要对这一切掉以轻心，而是正发生着一个非常令人兴奋的新机遇。

Anyways, the point isn't that we should be blithe about all of this, but that there is this really exciting new opportunity happening.

一个我认为我们讨论得还不够多的机遇。

And one that I think we don't talk about enough.

总之，告诉我你的想法吧。

Anyway, let me know what you think.

我很期待能继续进行这场对话。

I'm excited to have this conversation more.

目前，这就是今天的AI每日简报的全部内容。

For now, that's going do it for the AI Daily Brief.

一如既往，感谢您的收听或观看。

Appreciate you listening or watching, as always.

下次再见，保重！

And until next time, peace!