人工智能代理将以多快的速度席卷经济？

你想了解哪里出现了瓶颈。

You want to understand where the blockages are.

你知道，有一段时间的瓶颈在于代码合并，因为合并代码需要人类和其他系统来检查其正确性。

You know, one one blocker for a while was being able to merge in code because merging code requires humans and other systems to check it for correctness.

但现在如果你生成的代码量大幅增加，我们就必须大幅改进这个系统。

But now if you're producing way more code, we had to go and massively improve that system.

我对这个问题有一个普遍的经济理论，叫做‘O型环自动化’，其基本观点是自动化受限于链条中最慢的环节。

There's a general economic theory I like for this called O ring automation, which basically says automation is bounded by the slowest link in the chain.

此外，当你自动化公司的一部分时，人类会涌向最未被自动化的部分，提升其质量，并使其达到可以被自动化的程度，然后你再进入下一个循环。

And also, as you automate parts of a company, humans flood towards what is least automated and both improve the quality of that thing and get it to a point where it eventually can be automated, then you move to the next loop.

因此，我认为我们不断发现一些奇怪地缓慢的领域，但我们可以改进它们，为机器铺平道路，接着再找到下一个目标。

And so I think we're just continually finding areas where things are oddly slow, but we can improve to sort of make way for the machines to come behind us, and then you find the next thing.

所以Claude Code是一个相对较新的产品。

So Claude Code is a fairly new product.

Claude能够进行高级编码的时间跨度只有几个月，还是一年？

The amount of time at which Claude has been capable of doing high level coding is can be measured in months, a year?

也许一年。

Maybe a year.

是的。

Yeah.

Claude 本身是一个非常有价值的产品。

Claude itself is a very valuable product.

你已经将一种相当新的技术，相对宽松地应用于一个非常有价值的产品上。

So you've you've set a very new technology, somewhat loose on a very valuable product.

你可能正在生成更多的代码。

You're probably producing more code.

很多人告诉我，Claude Code 是有效的。

One thing many people say about Cloud Code to me is that it works.

它并不优雅，但有效。

It's not elegant, but it works.

对。

Yep.

但现在你对代码库的理解很可能不如以前了，因为你的工程师不再亲手编写代码。

But presumably now you now understand the code base less well than you did before because your engineers are not writing it by hand.

你是否担心，这样会制造大量的技术债务和网络安全风险，并且让你越来越远离对软件底层语言运行机制的直觉？

Are you worried that you're creating huge amounts of technical debt, cybersecurity risk, just an increasing distance from an intuition for what is happening inside the fundamental language of the software?

是的。

Yes.

这正是整个社会都将面临的问题。

And this is the issue that all of society is going to contend with.

世界上很大一部分领域，现在都将由系统来处理许多低层次的决策和具体工作，而我们需要理解这一切。

Just large chunks of of the world are going to now have many of the kind of low level decisions and bits of work being systems, and we're going to need to make sense of it.

要理解这一切，就需要开发许多你可能称之为监督技术的工具——就像大坝有装置来调节不同时间点的水流一样，我们将不得不建立起一种对所有系统完整性的概念，明确AI可以在哪些地方快速流动，在哪些地方应该放缓，以及哪些地方绝对需要人工监督。

And making sense of it is going to require building many technologies that you might think of as kind of oversight technologies or, you know, in the same way that a dam has things that regulate, like, how much water can go through it at different levels of, different points in time, we're going to end up developing some notion of integrity of all of our systems and where where AI can kind of flow quickly, where it should slow, where you definitely need human oversight.

在未来几年，这项任务不仅属于AI公司，也属于所有机构：我们需要弄清楚，在我们已经将大量繁琐工作交给代表我们行事的机器之后，这种治理机制应该是什么样子。

And that's gonna be the task of not just for AI companies, but institutions in general in the coming years is figuring out what does this this governance regime look like now that we've given a load of, basically schlep work over to machines that work on our behalf.

你们是怎么做的？

And how are you doing it?

你说这是每个人的问题，但你在应对这个问题上走在前列，而如果搞砸了，对你来说的后果是

You said it's everybody's problem, but you're ahead on facing this problem, and the consequences of getting it wrong for you are

非常严重。

pretty high.

对吧？

Right?

如果因为你们把编码工作交给了Claude，结果Claude出问题了，那会让Anthropic看起来很糟糕。

If Claude blows up because you handed over your coding to Claude code, that's gonna make Anthropic look fairly bad.

如果Claude像RM、RF一样把整个文件系统删了，那对Anthropic来说就是个糟糕的日子。

It would be a bad day for Anthropic if if Claude, like, RM, RF'd for entire file system.

我不知道这是什么意思，但不错。

I have no idea what that means, but great.

如果Claude删除了代码，那就糟了。

If Claude deleted the code, would be bad.

是的。

Yeah.

看起来很糟糕。

Seems bad.

所以你在我们其他人之前就面临这个问题，别把责任推给社会。

So as you're facing this before the rest of us are, like, don't pass the the buck over to society here.

你到底在做什么？

What have you what are you doing?

公司内部以及我所管理的团队中，最重要的是建立监控系统，以监控所有这些工作现在发生的地方。

The biggest thing that that is happening across the company and on teams that I manage is basically building monitoring systems to monitor this all of the different places that the work is now happening.

我们最近发表了一项研究，探讨人们如何使用智能体，以及人们如何让智能体随着时间推移逐步提交越来越多的代码。

So we recently published research on studying how people use agents and how people let agents kind of push increasingly large amounts of code over time.

你对智能体越熟悉，就越倾向于将任务委托给它。

So the more familiar you get with an agent, the more you tend to delegate to it.

这让我们面临各种模式，需要建立相应的评估体系。

That queues us to all kinds of patterns that we need to build systems of evaluation for.

基本上就是说，好吧。

Basically saying, oh, okay.

在这个人与AI系统互动的阶段，他们很可能已经高度依赖它了。

At this person's point of working with the AI system, it's likely that they're massively delegating it.

因此，在这些时刻，我们需要加强对我们所做正确性检查的力度。

So anything that we're doing to check correctness needs to be kind of turned up in these moments.

但你所描述的这个世界，是一个AI代理编写代码、AI代理监督代码、AI代理监督元层面的系统吗？

But is this world you're talking about, a system where you have AI agents coding, AI agents overseeing the code, AI agents overseeing the meta, overseeing of it.

对吧？

Right?

也就是说，我们讨论的是否是层层都是模型的世界？

Like, are we just talking about models all the way down?

最终，是的。

Eventually, yes.

我认为我们现在花所有时间在做的事情，就是让这一切对我们变得可见。

And I think that the thing that we are now spending all of our time on is making that visible to us.

一两年前，我们构建了一个系统，能够以保护隐私的方式，查看人们与我们的AI系统进行的对话。

A year or two ago, we built a system that let us, in a privacy preserving way, look at the conversations that people were having with our AI system.

然后我们获得了这张地图，一张关于人们与Claude交谈的所有主题的庞大地图。

And then we gained this map, this giant map of all of the topics that people were talking to Claude about.

第一次，我们可以从整体上看到世界与我们的系统进行的对话。

And for the first time, we could see in aggregate the conversation the world was having with our system.

我们需要构建许多类似的新系统，以提供不同的观察方式。

We're gonna need to build many new systems like that which allow for different ways of seeing.

而我刚刚提到的这个系统，使我们能够创建名为‘Anthropic经济指数’的东西，因为我们现在可以定期发布关于人们与Claude交谈的不同主题及其与各类工作关联的数据，这首次为Anthropic之外的经济学家提供了了解这些系统及其对经济影响的切入点。

And that system that I just named allowed us to then build this thing called the Anthropic Economic Index because now we can release regular data about the different topics people are talking about with Claude and how that relates to different types of jobs, which for the first time gives economists outside Anthropic some hook into these systems and what they're doing to the economy.

公司的核心工作将越来越多地转向构建监控和监管运行于公司内部的AI系统的体系。

The work of the company is increasingly going to shift to building a monitoring and oversight system of the AI systems running the company.

最终，我们所采用的任何治理框架，可能都会要求对这些知识系统具备一定程度的透明度和访问权限。

And ultimately, any kind of governance framework we end up with will probably demand some level of transparency and some level of access into these systems of knowledge.

因为如果我们认真对待这些AI公司（包括Anthropic）的目标——即打造有史以来最强大的技术，并最终将其部署到各个角落。

Because if we take as literal the goals of these AI companies, including Anthropic, it's to build the most capable technology ever, which eventually gets deployed everywhere.

这在我看来，意味着AI最终将与整个世界融为一体，届时，你不应只让AI公司掌握关于整个世界正在发生什么的全部信息。

Well, that sounds a lot to me like an eventually AI becomes indistinguishable from the world writ large, At which point, you don't want to only AI companies to have a sense of what's going on with the entire world.

所以会是政府、学术界和第三方机构。

So it's going to be governments, academia, third parties.

大量公司外部的利益相关者将希望了解正在发生的事情，并与社会讨论哪些是合适的，哪些让我们感到不安，以及我们需要哪些更多信息。

A huge set of stakeholders outside the companies are going to want to see what's going on and then have a conversation with society about what's appropriate and what what do we feel discomfort about, what do we need more information about.

等等。

Wait.

我想回到刚才那个话题。

I wanna go back on that.

你是在说Anthropic和SeeMyChats吗？

You're saying Anthropic and SeeMyChats?

我们无法查看，没有人会查看你的聊天内容。

We cannot see no human looks at your chats.

聊天记录会暂时存储，用于信任与安全目的，并运行分类器进行分析。

Chats are temporarily stored for trust and safety purposes, running running classifiers over them.

我们可以让Claude阅读、总结并删除这些内容。

And we can have Claude read it, summarize it, and toss it out.

所以我们从不查看，Claude 也不会记住它。

So we never see it, and Claude has no memory of it.

它只是尝试生成一个高度概括的摘要。

All it does is try to write a very high level summary.

比如说，你正在谈论园艺。

So say you were having a conversation about gardening.

Claude 会将这个对话概括为：这个人正在谈论园艺，并归入一个我们能看到的、名为‘园艺’的类别。

Claude would summarize that as this person's talking about gardening, and it leads to a cluster we can see that just says gardening.

但长远来看，这似乎会陷入许多社交媒体已经陷入的令人不快的境地——从人们与系统进行的非常私密的互动中收集大量元数据。

This feels though, like, over time, it could get into the quite unpleasant territory a lot of social media has gotten to, where the amount of metadata being gathered from a quite personal interaction people are having with a a system could be a lot.

是的。

Yes.

我的意思是，这里有几个方面。

I mean, a a couple of things here.

一年前，我们开始思考我们对消费者的立场，并采取了不投放广告的立场，因为我们认为，人们在这一领域显然存在焦虑。

A year ago, we started thinking about our our position on on consumer, and we adopted this position of not running ads because we think that's an area that people obviously have have anxieties about with regard to this kind of thing.

除此之外，我们还尝试向用户展示他们的数据，并在网站上提供一个按钮，允许您下载所有与Claude共享的数据，以便您至少能够查看它们。

In addition to that, we try and show people their data, and we have a button on the site that lets you download all the data that you shared with Claude so that you can at least see it.

总体而言，我们致力于在如何处理用户数据方面保持极高的透明度。

Generally, we're trying to be extremely transparent with people about how we handle their data.

最终，在我看来，人们会希望拥有大量可使用的控制选项，我认为我们和其他公司未来会逐步实现这些功能。

And ultimately, the way I see it is people are gonna want a load of controls that they can use, which I think we and others will build out over time.

当这些模型变得越来越复杂时，您有多大的信心认为我们能够进行这种监控和评估？如果我们真的进入一种情况，即Claude代码自主地以远超软件工程师阅读代码库速度的方式改进Claude，我们还能做到吗？

How confident are you that we can do this kind of monitoring and evaluation as these models become more complicated as if we do enter a situation where Claude code is autonomously improving Claude at a rate faster than software engineers could possibly keep up with reading that code base.

我们之前已经简要讨论过，您如何看待模型表现出某种程度的欺骗性，以及它们追求自身目标的现象。

We already talked briefly about how you see the models exhibit some levels of deception, some levels of pursuing their own goals.

我的意思是，Anthropic公司由Chris Olah等人开展的可解释性研究已经取得了惊人的成果，但这些工作仍然处于初级阶段。

I mean, there's been amazing interpretability work at Anthropic under Chris Ola and others, but it's rudimentary.

因此，您正在使用自己并不完全理解的AI系统来监控另一些您也不完全理解的AI系统，而这些系统正以加速的速度相互增强——如果事情如您所预期的那样发展的话。

So you're using AI systems you don't totally understand to monitor AI systems you don't totally understand, And the systems are making each other stronger at an accelerating rate if things go the way you think they're gonna go.

您有多大的信心认为我们最终能够理解这一切？

How confident are you that we're gonna understand that?

这正是多年来人们所警告的一种情况：将任务委托给具有些许不可解释和不可预测特性的系统。

This is one of the situations which people warned about for years, some form of delegation to systems that have slightly inscrutable and unpredictable aspects.

而这种情况正在发生。

And so this is happening.

我们对此高度重视。

We take this really, really seriously.

我认为，完全有可能构建一个系统，能够完成这里所需工作的绝大部分。

I think it's absolutely possible that you can build a system that does the the vast majority of what needs to be done here.

这个问题具有分形的特性。

This has the property of being a fractal problem.

你知道，如果我想衡量伊兹拉，我可以构建几乎无限多的测量方式来描述你。

You know, if I wanted to measure Ezra, I could build an almost infinite number of measurements to characterize you.

但问题是，我需要在多高的精度水平上衡量你？

But the question is, at what level of fidelity do I need to be measuring you?

我认为我们会达到足以应对安全问题和社会问题的精度水平，但这需要企业投入巨大的资源。

I think we'll get to the level of fidelity to deal with the safety issues and societal issues, but it's going to take a huge amount of investment by the companies.

我们必须说出一些让我们感到不适的话，包括在那些我们对自己系统的认知能力存在局限的领域。

And we're going to have to say things that are uncomfortable for us to say, including in areas where we may be deficient in what we can or can't know about our systems.

Anthropic 在研究这些问题的过程中，长期以来一直就这些议题进行讨论和预警。

And Anthropic has a long history of talking about and warning about some of these issues while working on it.

我们的总体原则是，通过公开讨论这些问题，使我们自己承担责任。

Our general principle is we talk about things to also make ourselves culpable.

这是一个我们必须说得更多的领域。

This is an area where we're going to have to say more.

我是贾德森·琼斯。

I'm Judson Jones.

我是《纽约时报》的记者兼气象学家。

I'm a reporter and meteorologist at The New York Times.

近二十年来，我一直在报道极端天气，而由于气候变化，极端天气正变得越来越严重，及时准确的天气信息也变得愈发重要。

For about two decades, I've been covering extreme weather, which is getting worse because of climate change, and it's becoming more important to get timely and accurate weather information.

因此，我们发送这些定制化的简报，提前最多三天告知您可能影响您或您关心的地区的极端天气。

That's why we send these customized newsletters letting you know up to three days in advance about extreme weather that could impact you or a place you care about.

在《纽约时报》，您可以相信，我们发布的所有内容都基于我们所能获得的最准确的科学信息，因为我们希望您能够实时做出关于如何安排生活的决策。

At The Times, you can be confident that everything we publish is based off the most accurate scientific embedded information available to us because we want you to be able to make real time decisions about how to go about your life.

这种工作使得订阅《纽约时报》如此有价值，也是您支持基于事实的独立新闻的方式。

This is the kind of work that makes subscribing to The New York Times so valuable, and it's how you can support fact based independent journalism.

如果您想订阅，请前往 nytimes.com/subscribe。

So if you'd like to subscribe, go to nytimes.com/subscribe.

我已经读过足够多关于人工智能超级智能和爆发的恐惧性观点，知道在几乎每一个这样的故事中，关键的假设都是人工智能系统会进行递归式自我改进。

I have read enough of the frightened ideas about AI superintelligence and takeoff to know that in almost every single one of them, the key move in the story is that the AI systems become recursively self improving.

是的。

Mhmm.

它们在编写自己的代码。

They're writing their own code.

它们在部署自己的代码。

They're deploying their own code.

它变得越来越快。

It's getting faster.

他们写得更快了。

They're writing it faster.

他们部署得更快了。

They're deploying it faster.

现在你会看到迭代周期越来越快。

Now you're going to have faster and faster iteration cycles.

你对此感到担忧吗？

Are you worried about it?

你对此感到兴奋吗？

Are you excited about it?

我回来了。

I came back

我休完陪产假回来，我为西耶拉负责的两个主要项目是：公开发布关于人工智能与经济的更准确信息，以及内部建立更完善的机制，以了解我们在多大程度上自动化了人工智能开发的各个部分。

from paternity leave, and my two big projects for Sierra are better information about AI and the economy that we will release publicly and generating much better information and systems of knowing information internally about the extent to which we are automating aspects of AI development.

我认为现在这一切还只是以非常边缘的方式发生。

I think right now, it's happening in a very peripheral way.

研究人员的节奏被加快了。

Researchers are being sped up.

AI系统正在运行不同的实验。

Different experiments are being run by the AI system.

弄清楚你是否完全闭合了这个循环，将极其重要。

It would be extremely important to know if you're fully closing that loop.

我认为我们实际上还有一些技术工作要做，那就是构建方法来监控我们内部的开发环境，以便观察趋势的变化。

And I think that we actually have some technical work to do to build ways of instrumenting our internal development environment so that we can see trends over time.

我担心吗？

Am I worried?

我读过你读过的那些内容，当事情开始出错时，这正是故事的关键转折点。

I have read the same things that you have read, and this is the pivotal point in the story when things begin to go awry, if things do.

当我们对此有更完善的数据时，我们会指出这一趋势。

We will call out this trend as we have better data on it.

我认为这是一个需要格外谨慎对待的领域，因为很容易出现将太多事情交由系统处理的情况，一旦系统出错，错误会迅速累积并失控。

And I think that this is an area to tread with, like, extraordinary caution because it's very easy to see how you delegate so many things to the system that if the system goes wrong, the wrongness compounds very quickly and gets away from you.

但让我一直感到担忧的是，每个人都心知肚明。

But the thing that always strikes me and has always struck me as being dangerous about this is everybody knows.

如果我问任何一家公司的员工是否希望在这里保持谨慎，他们都会告诉我他们确实希望如此。

And if I ask a member of any of the companies whether or not they wanna be cautious here, they will tell me they they do.

但另一方面，这几乎是他们彼此之间唯一的竞争优势。

On the other hand, it is their almost only advantage over each other.

你们刚刚撤销了OpenAI使用Cloud Code的权限，因为据我所知，你们认为它确实能提升你们的效率，而你们不希望它也提升他们的效率。

And you all just revoked OpenAI's ability to use Cloud Code because, as best I can tell, you think it is genuinely speeding you up, and you don't want it to speed them up.

在这里，各种力量的权重和影响力之间存在某种微妙的平衡，我相信你们都清楚自己正在玩弄什么，同时又面临着极其强烈的抢先动机。

There is something here between the weight of the forces, the power of the forces that I think you all know you're playing with, and the very, very, very strong incentives to be first.

我完全可以想象自己身处Anthropic内部时会想：与其让OpenAI领先，不如让我们领先？

And I I can I can really imagine being inside Anthropic and thinking, well, better us in OpenAI?

让我们领先，而不是让Alphabet、谷歌领先。

Better us than Alphabet, Google.

让我们领先，而不是让中国领先。

Better us than China.

而这正是一个非常充分的理由，不能放慢脚步。

And that being a very strong reason to not slow down.

我甚至不确定这个问题你是否能回答，但你是如何平衡这一点的呢？

I don't even know that this is a question I believe you can answer, but how do you balance that?

嗯，也许我这里有个答案。

Well, maybe I have something of an answer here.

今天，我们的系统以及其他公司的系统都会接受第三方的测试，包括政府机构对国家安全特性、生物武器、网络攻击等方面进行评估。

Today, our systems and the other systems from other companies are tested by third parties, including parts of government for national security properties, biological weapons, cyber offense, other things.

这显然是一个世界需要了解是否正在发生的问题领域。

It's clearly a problem area where the world needs to know if this is happening.

我认为，如果你随机调查街头任何一个人，向他们解释什么是递归自我改进后，问他们是否认为人工智能公司应该被允许这样做，

And you almost certainly, I think if you polled any person on the streets and said, do you think AI companies should be allowed to do, like, recursive self improvement after explaining what that was?

他们几乎肯定会说：不。

Without checking with anyone, they would say, no.

这听起来风险很大。

That sounds sounds pretty risky.

我是希望有一些形式的监管的。

Like, I would like there to be some form of regulation.

但他们可能根本不会实施，或者即使实施也不会那么严格。

But they're probably either won't be or it won't be that strong.

我的意思是，当我跟你们这些AI公司的高层交谈时，这有时让我很沮丧——你们竟然会冒出一种极其天真的‘机械降神’式监管幻想，而实际上你们都清楚监管环境是什么样子。

I mean, this actually sometimes frustrates me when I talk to all of you at the top of the AI companies, which is the emergence of, like, a very naive deus ex machina of regulation, where you all know what the regulatory landscape looks like.

目前，大讨论在于我们是否要完全 preempt 各州的AI监管，而你们也知道事情进展有多慢。

Right now, the big debate is whether or not we're gonna completely preempt any state AI regulation, and you know how slowly things move.

国会到目前为止对此根本没有通过任何重大法案，是的。

There has been nothing major passed by congress on this at all Yep.

我会这么说。

I would say.

建立一个所有不同实验室都认可的独立测试与评估体系，会很难。

And setting up some kind of independent testing and evaluation system that all the different labs buy into, it would be hard.

这会很复杂。

It would be complicated.

考虑到人们推进的速度以及系统已经表现出的种种异常行为，即使你能以极快的速度制定出正确的政策，关于测试能否在快速自我改进的系统中发现所有你希望发现的问题，仍然是一个悬而未决的问题。

And it is given how fast people are moving and how strange the behaviors the systems are already exhibiting are, even if you could get the policy right at a high speed, the question of whether or not the testing would be capable of finding everything you want on a rapidly self improving system is a very open question.

我于2021年与英国的合著者杰斯·惠特尔斯顿共同撰写了一篇研究报告，题为《政府为何及如何监控人工智能的发展》。

I wrote a research paper in 2021 called how and why governments should monitor AI development with, my co author Jess Whittleston in England.

我认为这里并不在强调因果关系，但就在那篇论文发表后的两年内，美国和英国都成立了人工智能安全研究所，开始对实验室的成果进行测试和大致监控。

And I think I'm not attributing a causal factor here, but within two years of that paper, we had the AI safety institutes in The US and UK testing things from the labs, roughly monitoring some of these things.

所以，我们确实能做成这件困难的事。

So we we can do this hard thing.

这件事已经在某个领域发生了。

It has already happened in one domain.

我并不是在依赖某种看不见的、神秘的外部力量。

And I'm not relying on some, like, invisible big other force here.

我更想说的是，公司们已经开始在自己的系统中对这些问题进行测试和监控。

I'm more saying that companies are starting to test for this and monitor for this in their own systems.

仅仅拥有一个非监管性质的外部测试，来验证你是否真正进行了相关检测，就已极具帮助。

Just having a nonregulatory external test of whether you truly are testing for that is is extremely helpful.

你觉得我们在测试方面足够好吗？

And do you think we're good enough at the testing?

我的意思是，我持怀疑态度的原因并不是我认为我们无法建立一个声称是测试的系统。

I mean, I think one reason I am skeptical is not that I don't think we can set up something that claims to be a test.

正如你所说，我们已经做到了。

As you say, we have done that already.

问题是，投入到测试中的资源与投入到加速这些系统中的资源相比，差距太大了；而且，我已经读到Anthropic的报告，说Claude可能知道自己正在被测试，并据此调整行为。

It is that the resources going into that compared to the resources going into speeding these systems and already, I am reading anthropic reports that Claude maybe knows when it's being tested and alters its behavior accordingly.

所以，在一个越来越多代码由Claude编写、而越来越少被人理解的世界里。

So a world where more of the code is being written by Claude and less of it is being understood.

我只是清楚资源流向了哪里。

I just know where the resources are going.

它们似乎并没有

They don't seem to be

流向测试这一侧。

going into the testing side.

我看到我们在短短两年到两年半的时间里，从零发展到了一个大多数人认为有效的生物武器测试体系。

I've seen us go from zero to having what I think people generally feel is an effective bioweapon testing regime in maybe two years, two and a half.

所以这是可以做到的。

So it can be done.

这非常困难，但我们已经有了一个实证。

It's really hard, but we have a proof point.

因此我认为我们能够达到这一目标，今年你们会听到我们更多地谈论我们如何开始构建针对这一领域的监控和测试机制。

So I think that we can get there, and you should expect us to kind of speak more about this this year about precisely how we're starting to try and build monitoring and testing things for this.

我认为，在我们发现的内容方面，我们和其他AI公司需要变得更加公开透明。

And I think this is an area where we and the other AI companies will need to be, significantly more more public about what we're finding.

我们并不是不公开信息。

We're not we're not not being public now.

这些内容都写在模型卡片里，你们完全可以阅读到。

It's in the model cards and things that you can really read.

但显然，人们已经开始阅读这些内容并说：等等。

But clearly, people are starting to read this and say, hang on.

这看起来相当令人担忧，他们正期待我们提供更多的数据。

This looks like quite concerning, and they are looking to us to produce more data.

现在我想回到入门级工作的问题上。

I wanna go back now to the entry level jobs question.

你们的首席执行官达里奥·阿马代认为，人工智能在今后几年内可能取代一半的入门级白领工作。

Your CEO, Dario Amade, has said that he thinks AI could displace half of all entry level white collar jobs in the next couple of years.

当我看到相关报道时，总觉得人们忽略了其中'入门级'这个关键词。

I always think that the the people sort of miss the entry level language there when I see it reported on.

但首先，你同意这个观点吗？

But first, do you agree with that?

你

Do you

你是否担心，在未来几年内，一半的入门级白领工作会被取代？

worry that half of all entry level white collar jobs can be replaced in the next couple of years?

我相信这项技术将渗透到广泛的知识经济领域，并影响大多数入门级工作。

I believe that this technology is gonna make its way into the broad knowledge economy, and it will touch the majority of entry level jobs.

这些工作是否真的会发生变化，是一个更加微妙的问题，从数据中并不明显。

Whether those jobs actually change is a much more, like, subtle question, and it's not obvious from the data.

比如，我们或许能看到毕业生招聘放缓的迹象。

Like, we maybe see the hints of a slowdown in graduate hiring, maybe.

如果你看看目前出炉的一些数据，我们或许能看到生产率飙升的迹象，但这还非常非常早期，很难下定论。

If you look at some of the data coming out right now, we maybe see the signatures of a productivity boom, but it's very, very early and it's hard to be definitive.

但我们确知，所有这些工作都会发生变化。

But we do know that all of these jobs will change.

所有入门级岗位最终都会改变，因为人工智能让某些事情成为可能，这将改变公司的招聘计划。

All of the entry level jobs are eventually going to change because AI has made certain things possible, and it's going to change for hiring plans of companies.

因此，作为一群体，你可能会看到入门级岗位的职位空缺减少。

So as a cohort, you might see fewer job openings for entry level jobs.

这将是所有这些变化中一种天真的预期。

That would be one naive expectation out of all of this.

但让我们谈谈，这甚至可能根本不是一种天真的预期。

But let's talk about that maybe not even being a naive expectation.

你说在Anthropic，你已经看到这种情况正在发生

You say it's already happening at Anthropic that what you're seeing

我看到我们的偏好正在发生变化。

I'm seeing us shift our preference.

没错。

Exactly.

我猜测，其他地方也会发生类似的情况。

And I I my guess is that that would be happening elsewhere.

就我们目前的情况而言，就连我使用这些系统的方式来看，我认为Claude、ChatGPT、Gemini或其他任何系统都很少能超越某个领域中最优秀的人。

And and where we are right now, I mean, even in the way I use some of these systems, it is rare, I think, that Claude or ChatGPT or Gemini or any of the other systems is better than the best person in a field.

嗯。

Mhmm.

它们通常还没有突破这一点，而且还有很多事情它们做不到。

It has not typically breached that, and there's all kinds of things they can't do.

但它们比普通大学毕业生更强吗？嗯。

But are they better than your median college graduate Mhmm.

在很多方面吗？

At a lot of things?

是的。

Yeah.

它们确实可以。

They are.

在一个你需要更少普通大学毕业生的世界里，我看到人们争论的一个问题是，这些系统目前是否能胜过一般或替代水平的工作。

And in a world where you need fewer of your median college graduates, One thing I've seen people arguing about is whether these systems at this point can do better than sort of average or replacement level work.

但我每次看到这种说法都会非常担忧，因为一旦我们接受它们能胜任一般或替代水平的工作，那么根据定义，大多数工作和大多数从事这些工作的人都是普通的。

But I always really worry when I see that because once we have accepted they can do average or placement level work, well, by definition, most of the work done and most of the people doing it Is average.

是普通的。

Is average.

对吧？

Right?

最优秀的人只是例外。

The best people are the exceptions.

而且，人们变得更好的方式是通过那些能让他们学习的工作。

And, also, the way people become better is that they have jobs where they learn.

是的。

Mhmm.

我的职业生涯中花了很多时间招聘年轻的记者。

I mean, I have spent a lot of time hiring young journalists over my career.

当你从大学招聘新人时，在某种程度上，你是在根据他们当时的文章和工作表现来雇佣他们。

And when you hire people out of college, to some degree, you're hiring them for their possible articles and work at that exact moment.

是的。

Mhmm.

但某种程度上，你也在对他们进行投资，相信他们的能力会随着时间推移不断提升，最终带来回报。

But to some degree, you're making a investment in them that you think will only pay off over time as they get better and better and better.

所以，这样一个可能对初级岗位产生真正影响的世界，对我来说并不遥远，它引发了许多深刻的问题：如何提升整体人口的技能？未来如何培养出胜任高级职位的人才？以及人们在成长过程中错过了哪些关键学习？

So this world where you have a a potential real impact on entry level jobs, and that that world does not feel far away to me, seems to me to have really profound questions it is raising about the upskilling of the population, how you end up with people for senior level jobs down the road, what people aren't learning along the way.

我们观察到，有一类年轻人已经多年沉浸并深度接触人工智能了。

And one thing we see is that there is a certain type of young person that has just lived and breathed AI for several years now.

我们雇佣他们。

We hire them.

他们非常优秀，能够以完全新颖的方式思考如何让Claude为他们工作。

They're excellent and they think in entirely new ways about basically how to get Claude to work for them.

这就像那些在互联网环境中成长起来的孩子。

It's like kids who grew up on the Internet.

他们自然而然地精通这一点，而他们所加入的许多组织中的其他人却并不具备这种能力。

They they were naturally versed in it in a way that many people in the organizations they were coming into weren't.

因此，学会如何培养这种基本的实验思维和对这些系统的探索精神，并加以鼓励，将变得至关重要。

So figuring out how to teach that basic experimental mindset and curiosity about these systems and to encourage it is going to be really important.

那些花大量时间玩味这些技术的人，会发展出非常宝贵的直觉，进入组织后能够变得极其高效。

People that spend a lot of time playing around with this stuff will develop very valuable intuitions, and they will come into organizations and be able to be extremely productive.

同时，我们还得弄清楚，我们希望培养哪些手工技能，或许可以借鉴行会式的理念来维持人类的卓越表现，以及组织如何选择传授这些技能。

At the same time, we're gonna have to figure out what artisanal skills we want to almost develop maybe a guild style philosophy of maintaining human excellence in and how organizations choose how to teach those skills.

好的。

Okay.

那那些处于中间位置的人怎么办呢？

Then what about all those people in the middle of that?

在硅谷以外的现实经济中，事情进展得很缓慢。

Things move slowly in the real economy outside Silicon Valley.

我认为我们常常看到软件工程，就以为它能代表整个经济的运行方式，但事实往往并非如此。

I think that we often look at software engineering and think that this is a proxy for how the rest of the economy works, but it's often not.

这常常是一种不恰当的类比。

It's often a disanalogy.

组织会把人员调配到那些人工智能系统尚未发挥作用的地方。

Organizations will move people around to where the AI systems don't yet work.

我认为，就业结构不会立即发生巨大的变化。

And I think that you won't see vast immediate changes in the makeup of employment.

但你会看到人们被要求从事的工作类型发生显著变化。

But you will see significant changes in the types of work people are being asked to do.

而那些最擅长调动人员的组织将会变得极其高效。

And the organizations which are best at sort of moving their people around are going to be extremely effective.

而那些做不到的组织，最终可能不得不做出一些极其艰难的决定，比如裁员。

And ones that don't may end up having to make, like, really, really hard decisions involving involving laying off workers.

AI技术的不同之处在于，它可能比以往任何技术都发生得快得多。

The difference with this AI stuff is it maybe happens a lot faster than previous technologies.

我认为，包括Anthropic在内的许多人对这一问题的焦虑在于：这种速度会不会带来根本性的变化？

And I think many of the anxieties people might have about this, including at Anthropic, is is the speed of this going to make all of this difference?

它是否引入了我们此前从未遇到过的全新问题？

Does it introduce sheer points that we haven't encountered before?

如果你要打个赌，三年后大学毕业生的失业率会和现在一样吗？

If you had to bet three years from now, is the unemployment rate for college graduates, is it the same as it is now?

是更高了，还是更低了？

Is it higher or is it lower?

我猜会略高一些，但不会高太多。

I would guess it is higher, but not by much.

我的意思是，今天有一些专业领域，AI已经介入并彻底改变了其就业市场的结构，可能对那些拥有这些专业技能的人不利。

And what I mean by that is there will be some disciplines today which actually AI has come in and and completely changed and completely changed the structure of that employment market, maybe in a way that's adverse to to people that have that specialism.

但总的来说，我认为三年后，人工智能将推动整个经济实现显著增长。

But mostly, I think three years from now, AI will have driven a pretty tremendous growth in the entire economy.

因此，你会看到许多新的工作类型因这一变化而出现，而这些目前还无法预测。

And so you're going to see lots of new types of jobs that show up as a consequence of this that we can't yet predict.

我预计，毕业生们会大量涌入这些新领域。

And you will see graduates kind of flood into that, I I expect.

你有

Do you have

我知道你无法预测这些新工作，但如果你要猜测它们可能是什么样子，会是什么？

a I know you can't predict those new jobs, but if you had to guess what some of them might look like.

我的意思是，其中一个现象就是微型企业家的兴起。

I mean, one thing is just the phenomenon of the the kind of micro entrepreneur.

现在，你可以通过很多种方式在线创业，而人工智能系统能为你完成大量工作，使这一切变得极其容易。

I mean, there are lots and lots of ways that you can start businesses online now, which are just made massively easier by having the AI systems do it for you.

你不需要雇用一大群人来帮你完成启动企业所需的繁重琐碎工作。

And you don't need to hire a whole load of people to help you do the huge amount of schlep work that involves getting a business off the ground.

更重要的是，如果你有一个清晰的想法和明确的商业愿景，那么现在正是创业的最佳时机，你只需极少的成本就能迅速起步。

It's more a case of if you're a person with a clear idea and a clear vision of something to do a business in, it's now the best time ever to start a business and you can get up and running for pennies on the dollar.

我预计我们会看到大量具有这种特征的事物涌现。

I expect we'll see tons and tons and tons of stuff that has that nature to it.

我还预计会出现一种你可能称之为‘AI对AI经济’的现象，即AI代理和AI企业之间将相互开展业务。

I also expect that we're gonna see the emergence of what you might think of as the AI to AI economy, where AI agents and AI businesses will be doing business with one another.

我们会看到一些人找到了通过这种模式获利的方法，形式是各种奇特的新组织。

And we'll have people that have figured out ways to basically profit off of that in the forms of strange new organizations.

比如，一家专门从事AI对AI法律合同的公司会是什么样子？

Like, what would it look like to have a firm which specializes in AI to AI legal contracts?

因为我相信，今天你就能找到一些富有创意的方式来创办这样的企业。

Because I bet you there's a way that you can figure out creative ways to start that business today.

会有大量类似性质的事物出现。

There'll be a lot of stuff of that flavor.

我所担心且认为最有可能发生的情况是：如果你告诉我，Anthropic将在一年后发布Claude Plus。

So the version of this that I both worry about and think to be the likeliest, if you told me what was gonna happen was that Anthropic was gonna release Claude plus in a year.

而Claude Plus会成为一个完全成型的同事，能够端到端地模仿众多职业的技能，甚至达到高管级别。

And Claude plus is somehow a fully formed coworker, and it can mimic end to end the skills of a lot of different professions up to the C suite level.

是的。

Mhmm.

而且这一切会同时发生，并给企业带来巨大的即时压力，迫使它们裁员以保持竞争力。

And it's gonna happen all at once, and it's gonna create tremendous all at once pressure for businesses to downsize, to remain competitive with each other.

从政策层面来看，如果这种颠覆性变化像COVID那样一次性大规模爆发，所有人都居家，我反而没那么担心。

At a policy level, the fact that that would be so disruptive in that big bang, everybody stays home because of COVID style way, it worries me less.

因为当事情成为紧急状况时，我们会做出反应。

Because when things are emergencies, we respond.

我们确实会制定政策。

We actually do policy.

但如果你告诉我

But if you told

说市场营销专业毕业生的失业率会上升175%到300%，但即便如此，失业率依然不会太高。

me that what's gonna happen is that the unemployment rate for marketing graduates is going to go up by, you know, a 175%, 300% to still not be that high.

我的意思是，在大衰退期间，整体就业率最高时也不过在百分之九左右。

I mean, the overall employment rate during the Great Recession topped her out, you know, in the nine ish percentile range.

所以，你可以经历很大的动荡，而不会让一半的人失业。

So you can have a lot of disruption without having 50% of people thrown out of work.

对吧？

Right?

如果你有10%、15%，我的意思是，这已经非常高了。

If you have 10%, 15, I mean, that's very, very, very high.

但还不算太高。

But it's not so high.

如果这种变化只发生在几个行业，而且受影响的是毕业生，而不是整个行业的每个人，那也许只是你不够优秀。

And if it's only happening in a couple of industries at a time and it's grads, not everybody in the industry being thrown out of work, well, maybe it's just that you're not good enough.

是的。

Yep.

对吧？

Right?

你知道，那些顶尖的、非常优秀的毕业生仍然能找到工作。

You know, the the superstars, really good graduates are still getting jobs.

你应该更努力一些。

You should have worked hard.

你应该去一所更好的学校。

Should have gone to a better school.

我担心的是，我们对这种类型的失业反应不佳，比如来自中国的那种失业，这种失业似乎更有可能发生，因为它分布不均，而且发生的速度让我们还能把个人的命运归咎于他们自己。

And one of my worries is that we don't respond to that kind of job displacement well, right, which is the kind of job displacement we got from China, which is the kind of job displacement that seems likelier because it's uneven, and it's happening at a rate where we can still blame people for their own fortunes.

我想知道你是怎么看待这个说法的。

I'm curious how you think about that story.

我觉得

I think

默认的结果就像你描述的那样，但如何达到这个结果其实是一种选择，我们可以做出不同的选择。

the default outcome is something like what you described, but getting there is actually a choice, and we can make different choices.

我们发布Anthropic经济指数的全部目的，就是为了获得能够关联到具体职业、关联到经济中真实工作岗位的数据。

The whole purpose of what we release in the form of the Anthropic Economic Index is the ability to have data that ties to occupations, that tie to real jobs in the economy.

我们这样做是有意为之，因为这能随着时间推移绘制出人工智能如何逐步渗透到不同工作岗位的图景，并帮助Anthropic之外的经济学家将这些信息串联起来。

We do that very intentionally because it is building a map over time of how this AI is making its way into different jobs and will empower economists outside Anthropic to tie it together.

我相信，如果我们能对工作变动或转型的原因做出更有实证依据的主张，政策上就可以做出不同的选择。

I believe that we can choose different things in policy if we can make much more well evidenced claims about what the cause of a job disruption or change is.

我们面临的挑战是，能否充分描述这个新兴的人工智能经济，使其变得如此清晰明确？

And the challenge in front of us is can we characterize this emerging AI economy well enough that we can make this extremely stark?

然后，我认为我们才能真正就这个问题展开政策讨论。

And then I think that we can actually have a policy discussion about it.

那我们来谈谈政策讨论吧。

Well, let's talk about the policy discussion.

是的。

Yep.

我之所以特别邀请你来，其中一个原因是你在OpenAI做过政策工作。

One reason I wanted to have you in particular on is you did policy at OpenAI.

是的。

Yep.

你在Anthropix做政策工作。

You do policy at Anthropix.

你一直参与这些政策辩论。

You've been around these policy debates for a long time.

你长期以来一直在你的通讯中追踪模型的能力。

You've been tracking model capabilities in your newsletter for a long time.

我的感觉是，我们已经就人工智能展开了多年的讨论，是的。

My perception is we are many, many years into the debate about AI and Mhmm.

早在ChatGPT出现之前很久，就已经有多年的讨论了，是的。

Many, many years dating far before ChatGPT Mhmm.

关于人工智能和就业，我们已经在阿斯彭和其他地方举办了无数会议，讨论我们该如何应对。

Of there being conferences at Aspen and everywhere else about, you know, what are we gonna do about AI and jobs?

但不知为何，我仍然几乎没有看到任何可操作的政策，如果我刚刚描述的情况真的出现——即大量行业的初级岗位突然变得极其难找，是的。

And somehow, I still see almost no policy that seems to me to be actionable if the situation I just described begins showing up, where all of a sudden entry level jobs are getting much harder to come by across a large range of industries all at once Mhmm.

以至于经济无法将这些市场营销专业的毕业生重新分配到数据中心建设、护士或其他行业。

Such that the economy cannot reshift all these marketing majors into data center construction or nurses or something.

是的。

Mhmm.

所以，好吧，你比我对这个话题的参与更深。

So, okay, you've been deeper in this conversation than I've been.

当你说到我们可以就这个问题展开政策讨论时，其实我们已经在进行政策讨论了。

When you say we can have a policy conversation about that we've been having a policy conversation.

我们有具体的政策吗？

Do we have policy?

我们对人工智能对经济和就业的影响感到普遍的焦虑。

We have generalized anxiety about the effect of AI on the economy and on jobs.

但我们没有清晰的政策构想。

We don't have clear policy ideas.

部分原因是，民选官员并不单纯或主要被高层次的政策讨论所驱动。

Part of that is that elected officials are not moved solely or mostly by the high level policy conversation.

他们更关注选民的实际遭遇。

They're moved by what happens to their constituents.

就在几个月前，我们才刚刚能够提供各州层面的经济指数数据，而现在你们可以开始进行政策层面的讨论了。

Only a few months ago were we able to produce state level views for our economic index, And now you can start having the policy conversation.

我们曾与民选官员讨论过这个问题，现在我们可以这样说：哦，您来自印第安纳州。

And we've had this with elected officials where now we can say, oh, you're from you're from Indiana.

比如，这是您州内人工智能的主要应用领域，我们可以将其与主要的就业来源结合起来。

Like, here's for, like, major uses of AI in your state, and we can join it with major sources of employment.

我们开始看到，这能激发他们的行动，因为这将政策与他们的选民联系起来，而选民会追问政客：你做了什么？

And what we're starting to see is that activates them because it makes it tied to their constituents who are going to tie it to the the politician of what did you do.

现在，针对这个问题，你需要采取一种多层次的应对措施，从延长失业救济（特别是针对那些我们知道将受到最严重影响的职业）到考虑学徒计划等措施。

Now, what you do about this is going to need to be an extremely kind of multilayered response ranging from extending unemployment for especially occupations that we know are going to be hardest hit to thinking about things like apprenticeship programs.

随着情况变得越来越严重，你可能还需要扩展到更大规模的社会项目，比如补贴那些你希望人们转向的经济领域中的工作岗位——而这些措施只有在经历显著经济增长所带来的富足时才可能实现。

And then as the scenarios get more and more significant, you may extend to much larger social programs or things like subsidizing jobs in the parts of the economy where you want to move people to, that you're only able to do if you experience the kind of abundance that comes from significant economic growth.

但经济增长本身可能有助于解决一些其他政策挑战，因为它能为你可以采取的措施提供资金支持。

But the economic growth may help solve some of these other policy challenges by funding some of the things you can do.

我总是觉得这个答案令人沮丧。

I always find this answer depressing.

我实话跟你说吧。

I'm gonna be honest.

失业是一件非常糟糕的事。

Unemployment is a terrible thing to be on.

我们需要这个项目，但领取失业救济的人并不为此感到开心。

It's a program we need, but people on unemployment are not happy about it.

是的。

Mhmm.

这也不是任何人的长期解决方案。

And it's not a good long term solution for anybody.

学徒再培训项目，其成效并不理想。

Apprentice retraining programs, they don't have great track records.

我们在帮助人们从被外包的制造业岗位中再就业方面做得并不好。

We were not good at retraining people out of having their manufacturing jobs outsourced.

我不是说我们不可能在这方面变得更好，但我们必须迅速提升能力。

I'm not saying it is conceptually impossible that we could get better at it, but we would need to get better at it fast.

嗯。

Mhmm.

而且我们还没有投入足够的练习、实验、制度建设或能力提升来实现这一点。

And we have not been putting in the reps or the experimentation or the institution or capacity building to do that.

而关于大规模社会保险改革这个更广泛的问题，我觉得这对我来说很难。

And the the broader question of big social insurance changes doesn't seem I mean, that seems tough to me.

我想就这一点再深入一下。

I wanna push on this

请说。

Please.

就在我们明知有一种干预措施，能比其他任何方法都更有效地帮助人们应对经济变化时。

Just a bit where we know that there is one intervention that helps people dealing with, like, a changing economy more than almost anything else.

那就是时间。

It is just time.

给人们一些时间，去找到本行业的工作，或者找到一份互补的工作。

Giving the person time to find either a job in their industry or to find a job that's complementary.

如果人们没有时间，他们就会接受更低工资的工作。

If people don't have time, they take lower wage jobs.

他们会脱离自己原本所处的经济阶层，跌落下去。

They fall out of their whatever economic rung they're on, they fall down at.

能够为人们提供寻找工作时间的政策干预，我认为是一种非常有效的措施，并且在政策制定中有很多可以调整的细节。

Policy interventions that can just give people time to search is, I think, a a robustly useful intervention and one where there are many, dials to turn in a policy making sense that you can use.

我认为这一点得到了大量经济学文献的有力支持。

And I think this is just well supported by lots of the economic literature.

所以我们已经有了这一点。

So we have that.

如果我们陷入像你提到的那些更极端的情境中，我认为这将促使我们展开关于如何应对这项技术的更大规模的国家讨论，而这种讨论已经开始出现了。

Now if we end up in a more extreme scenario like some of the ones that you're talking about, I think that will just bring us to the larger national conversation of what to do about this technology, which which is beginning to happen.

如果你看看各州以及州一级涌现的立法浪潮，是的，并非所有政策都恰好是正确的应对方式，但它们确实表明了人们希望就这一问题展开更系统、更连贯的讨论。

If you look at the states and the flurry of legislation at the at the state level, yes, not all of it is like the exactly the right policy response, but it is indicative of a a desire for there to be some larger coherent conversation about this.

我认为，用‘时间’来描述这个问题非常恰当，因为我同意你的观点。

Well, I think time is a really good way of describing what the question is because I agree with you.

我的意思是，当我说失业保险不是一个很好的项目时，我不是说人们不需要它。

I mean, when I say unemployment insurance isn't a great program to be on, I don't mean people don't need to be on it.

对。

Yep.

我的意思是，他们希望离开它。

I mean, they wanna get off of it.

当然。

Absolutely.

因为人们想要来自工作的钱。

Because people for they want money from jobs.

他们想要尊严。

They want dignity.

他们想要与他人相处。

They want to be around other human beings.

通常，当你帮助人们争取时间时，你是在帮助他们度过一段有明确期限的中断。

Usually, what you're doing when you are helping people buy time is you're helping them wait out a time delimited disruption.

嗯嗯。

Mhmm.

并不总是如此。

Not always.

对吧？

Right?

中国冲击并不完全如此，但你预期它会过去，然后市场会恢复正常。

The China shock wasn't exactly like that, but that you expect to pass, and then the the market is sort of normal.

在这种情况下，你拥有的是一种技术，如果希望发生的事情发生了，这种技术正在加速。

In this case, what you have is a technology that if what you wanna have happen happens, the technology is accelerating.

嗯嗯。

Mhmm.

所以，你现在看到的是三种不同的速度在同时发生。

So what you have is, like, three different speeds happening here.

你有个人适应的速度。

You have the speed at which individual people can adjust.

我能在多快的时间里学会新技能，适应新世界，掌握人工智能，不管它是什么？

How fast can I learn new skills, figure out a new world, learn AI, whatever it might be?

你有AI系统的速度，几年前它们还无法胜任优秀大学毕业生的工作，还有政策的速度。

You have the speed at which the AI systems, which a couple of years ago, were not capable of doing the work of a median college grad from a good school, and you have the speed of policy.

AI系统变得越来越好、能做更多事情的速度非常快。

And the speed at which the AI systems are getting better and able to do more things is quite fast.

我的意思是，你比我能更深刻地感受到这一点，但我发现连跟进都很难，因为你知道，三个月内就会有新东西出现，彻底改变可能实现的事情。

I mean, that is you you experience this more than I do, but I find it hard to even cover this because, you know, within three months, something else will have come out that has significantly changed what is possible.

我最近当了爸爸，休完陪产假回来后，发现我们搭建的新系统。

I had a baby recently and came back from paternity leave to the new systems we built.

我大吃一惊。

Was deeply surprised.

个体人类的适应速度比这慢得多，而政策和政府机构的调整速度比个人还要慢得多。

Individual humans are moving more slowly than that, and policy and government institutions move a lot more slowly than individual human beings.

因此，通常的干预方式是，时间站在劳动者这一边，就像你所说的那样。

And so, typically, the the intervention is that time favors the worker, as you're saying.

而在这里，将帮助劳动者。

And here, will help the worker.

但我认为令人担忧的问题是，时间是否实际上只是为混乱加剧争取了更多时间。

But I think the scary question is whether time just actually creates time for the disruption to get worse.

你知道的。

You know?

也许你原本打算转向数据中心建设，但事实上，我们现在不需要那么多的数据中心建设了。

Maybe you wanted to move over to data center construction, but, actually, now we don't need as much data center construct.

对吧？

Right?

你可以这样理解。

Like, you can think of it like that.

我的意思是，在你所描述的情况下，经济将变得极度繁荣。

I mean, under the situation you're describing, the economy will be running extremely hot.

这些AI系统将产生巨大的经济活动。

Huge amounts of economic activity will be generated by these AI systems.

在大多数这种情况下，我认为GDP不会保持不变或萎缩。

And under most scenarios where this is happening, I don't think you're going to be seeing GDP stay the same or or shrink.

对吧？

Right?

它会显著增长。

It's going to be getting substantially larger.

我认为，我们在西方已经很久没有经历过重大的GDP增长了，因此我们渐渐忘记了这种增长在政策制定上能带来什么。

I think we just haven't experienced major GDP growth in the West in a long time, and we sort of forget what that affords you in a policy making sense.

我认为，我们可以开展许多大型项目来创造新的工作岗位，但这需要经济实现如此深远的增长，才能为这些项目腾出空间。

I think that there are huge projects that we could do that would allow you to create new types of jobs, but it requires the economic growth to be so kind of profoundly large that it creates space to do those projects.

而且，就像你对丰裕运动的研究非常熟悉的一样，这还需要社会有意愿相信我们能够建设，并且愿意去建设。

And, you know, as you're deeply familiar with with with your work on on the abundance movement, it requires for, like, social will to believe that we can build stuff and to want to build stuff.

但我认为这两点都可能会随之而来。

But I think both of those things might come along.

我认为，我们可能会进入一个相当令人兴奋的场景：由于经济的大幅增长，我们得以选择如何分配社会中的巨大资源。

I think that we could end up being in a pretty exciting scenario where we get to choose how to allocate, like, great efforts in in society due to this large amount of economic growth that has happened.

这将迫使人们讨论一个问题：这不是暂时的，我认为你正是在暗示这一点，而这也是最难向政策制定者传达的——这项技术并没有一个自然的终点。

That is going to require the conversation to be forced about this isn't temporary, which I think is what you're gesturing at and is in a sense, the hardest thing to communicate to policymakers is there isn't a there isn't a natural stopping point for this technology.

它会持续变得更好，它带来的变化也将与社会其他方面持续叠加。

It's gonna keep getting better, and the changes it brings are going to keep compounding with the rest of society.

因此，这需要改变政治意愿，重新愿意去考虑一些我们许久未曾考虑的事情。

So that will need to create a change in in political will and a willingness to entertain things which we haven't in some time.

所以现在我想换个角度，提出我自己的问题。

So now I wanna flip it, the question I'm asking.

你提到了富足。

You brought up abundance.

我在从事这项工作中学到的一点是，我绝不认为社会中缺乏的是改善事物的好点子，我们的政策之所以不够好，并不是因为政策库枯竭了。

One of the things I have learned doing that work is that it is certainly not my view that what is scarce in society is ideas for better ways of doing things, that our policy isn't better than it is because our policy cupboard is dry.

嗯。

Mhmm.

对吧？

Right?

这不对。

That's not true.

我们有很多好的政策。

We have lots of good policies.

我能举出一大堆例子。

I could name a bunch of them.

但以我们目前的政治体制，这些政策很难得以推行。

They're very hard to get through our political systems as they're currently constituted.

人工智能未来最令人沮丧的一种可能是：你创造了一种方式，将年轻的白领工人赶出工作岗位，用普通水平的人工智能取而代之。

The least inspiring version of the AI future is a world where what you have done is create a way to throw young white collar workers out of work and replace them with average level AI intelligence.

更令人兴奋的版本，用达里奥的比喻来说，就是数据中心里的天才。

The more exciting version, to use Dario's metaphor, is geniuses in the data center.

嗯。

Mhmm.

我认为这确实令人振奋。

And I do think that's exciting.

当我听到你或他谈论，如果我们每年实现10个百分点的GDP增长，或者20个百分点的GDP增长，会怎么样时，我不禁想，

And I wonder when I hear him or you talk about, well, what if we had 10 percentage point GDP growth year on year, 20 percentage point GDP growth year on year?

我们面临的许多问题，是不是其实只受限于想法层面？

I wonder how many of our problems are really bounded at the ideas level.

对吧？

Right?

我们现在就可以去找诺贝尔奖得主，问他们：这个国家我们应该怎么做？

We could go to Nobel Prize winners right now and say, what should we do in this country?

他们中的很多人能给我们提供一些当前我们还没在做的好点子。

And a lot of them could give us good ideas that we are not currently doing.

我有时会担心，或者根据我在其他问题上的经验感到疑惑：我们是否高估了自身面临的障碍——以为阻碍我们走向繁荣经济的，主要是缺乏足够的智慧和这些智慧能产生的想法，而实际上，我们执行能力的削弱更为严重？

I do worry sometimes or wonder, given my experience on other issues, whether we have overstated to ourselves how much of what stands between us and the expanding abundant economy we want is that we don't have enough intelligence and the ideas that that intelligence could create versus our actual ability to implement things is very weakened.

而人工智能将加剧这一瓶颈，因为会有更多东西被推给系统去执行，包括愚蠢的点子、错误信息和投机行为。

And what AI is gonna create is a larger bottlenecks around that because there'll be more being pushed at the system to implement, including dumb ideas and disinformation and slot.

对吧？

Right?

就像，它在账目的另一侧也会有一些东西。

Like, it'll have things on the other side of the ledger too.

你是怎么看待这些限制因素的？

How do you think about these rate limiters?

某种程度上说

There's kind of

这里有一个有趣的教训，来自人工智能公司或一般公司，尤其是科技公司：通常新的想法来自于公司内部创建所谓的‘创业中的创业’，也就是把那些随着时间推移积累起来的后台官僚主义或繁琐工作抛在一边，然后对公司内部一个很小的团队说：你们什么都不用管。

a funny lesson here from the AI companies or companies in general, especially tech companies, where often new ideas come out of companies by them creating what they always call the startups within a startup, which is basically taking whatever process has, like, built up over time leading to back end bureaucracy or schlep work and saying to a very small team inside the company, you don't have any of this.

去干点事情吧。

Go and do some stuff.

这就是像Claude Code和其他一些东西是如何被创造出来的。

And and this is, you know, how things like Claude Code and other stuff get created.

一些开始浮现的想法是：在更广泛的经济体系中，创建这种无许可的创新结构会是什么样子？

Ideas that kind of are starting to float around are what would it look like to sort of create that permissionless innovation structure in in the larger economy.

这真的非常困难，因为它还有一个额外的特性，那就是经济体系与民主制度是紧密相连的。

And it's really, really hard because it has the additional property that, you know, economies are are linked to democracies.

民主制度需要权衡众多民众的意愿，而所有政治都是地方性的。

Democracies weigh the preferences of many, many people, and all politics is local.

因此，正如你在基础设施建设中所遇到的那样，如果你想建立一个无许可的创新体系，就会遇到产权和人们真实意愿等问题，这时你就陷入了一个难以解决的境地。

So often, as you've encountered with infrastructure build outs, if you want to create a permissionless innovation system, you run into things like property rights and what people's preferences are, and now you're in an intractable place.

但我的感觉是，这正是我们将来必须面对的主要问题。

But my sense is that's the main thing that we're going to have to confront.

而人工智能可能给我们带来的一个优势是，如果运用得当，它本质上是一种能吞噬官僚体系的机器；但如果用得不好，它反而会成为制造官僚体系的机器。

And the one advantage that AI might give us is it is kind of a native bureaucracy eating machine if done correctly, or a bureaucracy creating machine if done badly.

你有没有看到，有人创建了一个系统，你只需输入你附近新开发项目的相关文件。

Did you see that somebody created a a system that basically you feed it in the documents of a new development near you.

哦，它会自动生成环境评估报告？

Oh, and it writes environmental review things?

或者它会写出极其复杂的异议意见，是的。

Or It writes incredibly sophisticated challenges Yep.

针对你能想到的每一个可挑战的环节。

Across every level of the code that you could possibly challenge on.

所以，大多数人没钱请一家非常专业的律师事务所来阻止隔壁建公寓楼。

So most people don't have the money when they wanna stop an apartment building from going up down the block to hire a very sophisticated law firm to figure out how to stop that apartment building.

但基本上，这个系统实现了规模化的效果。

But, basically, this created that at scale.

所以，正如你所说，它既能吞噬官僚体系，也能极大地强化官僚体系。

And so as you say, right, it could eat bureaucracy, could also supercharge bureaucracy.

是的。

Yep.

人工智能的每一件事都有其反面。

It's the everything in AI has the other side of the coin.

我们有一些客户使用我们的AI系统，大幅缩短了提交新药候选材料所需的时间，时间被大大减少了。

We have customers that have used our AI systems to massively reduce the time it takes them to produce all of the materials they need when they're submitting new new drug candidates, and it's cut that time massively.

这正是你刚才描述的镜像世界版本。

It's the Mirror World version of what you just described.

我对这个问题没有简单的答案。

I don't have an easy answer to this.

我认为，只有当这种情况明显演变为危机，并且能够在社会层面进行讨论时，它才会变得可以采取行动。

I think that this is the kind of thing that becomes actionable when it is more obviously a crisis and actionable when it's something that you can discuss at a societal level.

我想，这场对话中一直萦绕的问题是，人工智能的变化几乎会在各个地方发生，而其风险则以一种分散且难以捉摸的方式显现，使得我们很难准确识别它并采取相应措施。

I guess the thing that was circling around in this conversation is that the changes of AI will kind of happen almost everywhere, And the risks of it, it happens in a diffuse unknowable way such that it is very hard to call it for what it is and take actions on it.

但机遇在于，如果我们能够真正看清这一现象，并帮助世界看清正是这种现象在推动变革，我相信这会凸显问题，促使我们摆脱某些惯性，从而学会如何与这些系统共处并从中受益。

But the opportunity is that if we can actually see the thing and help the world see the thing that is causing this change, I do believe it will dramatize the issues to kind of shake us out of some of this stuff and help us figure out how to work with with these systems and benefit from them.

我在这一切中注意到的是，据我所知，目前对公共人工智能完全没有明确的议程。

What I notice in all this is that there is, as far as I can tell, zero agenda for public AI.

社会希望人工智能做什么？

What does society want from AI?

社会希望这项技术具备哪些能力？

What does it want this technology to be able to do?

有哪些事情是你必须通过商业模式、奖励机制、政府补贴或某种政策来塑造市场或激励体系的？

What are things that maybe you would have to create a business model or a prize model or some kind of government payout or some kind of policy to shape a market or to shape a system of incentives?

我们现在的系统不仅在解决私营市场知道如何付费的问题，还在解决那些无人负责、唯有公共部门才该承担的问题。

So we have systems that are solving not just problems that the private market knows how to pay for, but problems that it's nobody's job but the public Mhmm.

政府也需要弄清楚如何解决这些问题。

And the government to to figure out how to solve.

我认为，考虑到过去几年人们对AI的大量讨论以及这些系统变得多么强大，我本该看到更多这方面的提案了。

I think I would have bet given how much discussion there's been of AI over the past couple of years and how strong some of these systems have gotten, that I would have seen more proposals for that by now.

我跟一些人聊过这个问题，也一直在思考，但我很好奇你是怎么看待这个问题的。

And I've talked to people about it and wondered about it, but I I guess I'm curious on how you think about this.

我们需要一个议程，至少要与所有推动AI发展的私人激励并行，这个议程不是关于‘我们害怕AI会对公众造成什么影响’。

What would it look like to have, at least parallel to all the private incentives for AI development, an actual agenda for not what we are scared AI will do to the public.

我们同样需要一个关于这方面的议程。

We need an agenda for that too.

而是关于我们希望AI能做什么，这样才能让像你们这样的公司有动力往这个方向投入？

But what we want it to do such that companies like yours have reasons to invest in that direction?

我喜欢这个问题。

I love this question.

我认为这里存在一个典型的‘鸡生蛋还是蛋生鸡’的问题：如果你亲自接触这项技术，就会对它能实现的能力产生非常强烈的直觉。

I think there's a real chicken and egg problem here where if you work with the technology, you develop these very strong intuitions for just how much it can do.

私人市场非常擅长推动这些直觉的形成。

And the private market is great at forcing those intuitions to get developed.

我们尚未在公共领域大规模部署这项技术。

We haven't had massive large scale public side deployments of this technology.

因此，许多公共部门的人还没有这些直觉。

So many of the people in the public sector don't yet have those those intuitions.

一个积极的例子是能源部正在开展的‘创世计划’，他们的科学家正与包括Anthropic在内的所有实验室合作，探索如何有意识地加速科学的某些部分。

One positive example is something the Department of Energy is doing called the Genesis Project, where their scientists are working with all of the labs, including Anthropic, to figure out how to actually go and intentionally speed up bits of science.

要达到这一程度，我们和其他实验室与能源部的科学家进行了多次黑客松和会议，使他们不仅形成了直觉，还变得兴奋起来，并有了可以将这项技术应用于哪些方向的想法。

Getting there took us and other labs doing multiple hack days and meetings with scientists at the Department of Energy to the point where they not only had intuitions, but they became excited, and they had ideas of what you could turn this toward.

要将这种方法推广到更广泛的公共生活领域，如医疗或教育，需要企业深入这些社区，与当地人接触，开展基层努力。

How we do that for the larger parts of the public life that touch most people, like health care or education, is going to be a combination of grassroots efforts from companies going into those communities and and meeting with them.

但最终，我们必须将其转化为政策。

But at some point, we'll have to translate it to policy.

我认为，这可能需要我、你和其他人去论证：这件事是完全可以实现的。

And I think maybe that's me and you and others making the case that this is something that can be done.

我经常对民选官员说：给我们一个目标。

And I often say this to elected officials of give us a goal.

比如，人工智能行业非常擅长通过基准测试来攀登顶峰。

Like, the AI industry is excellent at trying to climb to the top on benchmarks.

为公众利益制定一些基准吧。

Come up with benchmarks for the public good that you want.

那么，假设你真的这样做了。

So let's imagine that you did do something like this.

我一直非常支持以奖励推动公共研发。

I've I've always been a big fan of prizes for public development.

假设有一项立法通过了，卫生与公共服务部或国立卫生研究院（NIH）或其他机构宣布：这里有15个我们希望看到解决的问题，我们认为人工智能可以在这方面大有作为。

So let's say that there was legislation passed and the Department of Health and Human Services or the NIH or or someone came out and said, here's 15 problems we would like to see solved that we think AI could be Mhmm.

有潜力解决这些问题。

Potent at solving.

对吧？

Right?

如果真有这笔钱，如果这些难题背后有1万亿美元的资金支持，因为它们对社会而言值这个价，这会实质性地改变Anthropic等机构的发展优先级吗？

If there was real money there, if there was $1,015,000,000,000 behind a bunch of these problems because they were worth that much to society, would it materially change the sort of development priorities at places like Anthropic?

我的意思是，如果资金到位，这会改变你们的研发方向吗？

I mean, if the money was there, would it alter the sort of r and

你们正在做的工作？

d you all are doing?

我不这么认为。

I don't think so.

为什么？

Why?

因为真正阻碍这些工作的并不是资金。

Because it's not really the money that is the impediment to this stuff.

而是实施路径。

It is the implementation path.

而是真正清楚如何让成果顺利落地并产生效益。

It is actually having a sense of how you get the thing to flow through to the benefit.

公共部门的许多方面并未被设计成对技术普遍友好，也缺乏激励机制。

And many aspects of the public sector have not been built to be super hospitable to technology in general to incentivize it.

我认为，这主要需要以可保证的影响力和明确的实施路径作为奖励。

I think it mostly just takes a bounty in the form of guaranteed impact and guaranteed path to implementation.

因为人工智能组织中最稀缺的资源，其实是组织内人员的时间，因为你可以几乎朝任何方向发展。

Because the main thing that is scarce at AI organizations is just the time of the people at the organization because you can go in almost any direction.

这项技术正在迅速扩展。

This technology is expanding super quickly.

许多新的应用场景正在涌现。

Many new use cases are opening up.

你只是在问自己：我们究竟在哪里才能对世界产生积极而有意义的影响？

And you're just asking yourself the question of where can we actually have a positive meaningful impact in the world.

在私营部门，这非常容易实现，因为它拥有推动一切落地的全部激励机制。

Super easy to do that in the private sector because it it has all of the incentives to push stuff through.

在公共部门，我们更需要解决的是部署问题，而非其他任何问题。

In the public sector, we more need to solve this problem of deployment than anything else.

如果宣布了什么，你会感到兴奋？

What would excite you if it was announced?

你认为哪些项目会是这种类型的合适候选？

What what what do you think would be good candidates for that kind of project?

任何能加快与医疗专业人员沟通并减轻他们工作负担的事情。

Anything that helps speed up the time it takes to both speak to medical professionals and take work off their plate.

你知道，我们最近又有了一个宝宝。

You know, we had another baby recently.

因为宝宝撞到头了，或者今天皮肤颜色不一样了，诸如此类的事情，我花了很多时间在凯撒医疗的咨询热线。

I spend a lot of time on the Kaiser Permanente advice line because the baby's bonked its head or its skin's a different color today or, you know, all of these things.

我会用Claude来帮我和我妻子在等待护士接听时避免恐慌。

And I use Claude to sort of stop me and my wife panicking while we're waiting to talk to the nurse.

但接着我听护士做了所有这些分诊工作，问了这么多问题。

But then I listened to the nurse do all of this like triaging, ask all of these questions.

显然，很大一部分工作都可以用AI系统高效地完成，这能帮助我们短缺的人力更有效地利用时间，也能给正在经历这个系统的人提供安心。

So obviously, a huge chunk of this is stuff that you could like use AI systems productively for and it would help the people that we don't have enough of spend their time more effectively, and it would be able to give reassurance to the people going through the system.

这可能没有你想象中的那些东西那么令人兴奋或炫目。

And that's maybe less inspiring and and glamorous than maybe some of what you're you're imagining.

但我觉得，当人们与公共服务互动时，他们最大的挫败感往往在于流程不透明，而且要等很久才能联系到人。

But I think mostly when people interact with public services, their main frustration is just that it's opaque and it takes you a long time to speak to a person.

但实际上，这些正是人工智能可以真正发挥作用的领域。

But actually, these are exactly the kinds of things that AI could meaningfully work on.

这很有趣，因为你描述的并不是人工智能作为数据中心里一群天才的产物，而是将人工智能视为通信和文档处理的基础基础设施。

It's interesting because what you're describing there is less AI as a country of geniuses in the data center and more AI as standard plumbing of communications and documentation.

我们数据中心里有一群初级员工。

We've got a country of junior employees in the data center.

让我们好好利用这一点。

Let's do something with that.

有一件事我们在这次对话中还没提到，但值得记住的是：如今科学的前沿已经向商业开放，这在过去是前所未有的。

Like, you know, one thing we haven't talked about in this conversation and it's just worth bearing in mind is, like, the frontier of science is open for business now in a way that it hasn't been before.

我的意思是，我们已经找到了一种方法，能够可靠地加速人类科学家的工作。

And what I mean by that is we found a way to build systems that can provably accelerate human scientists.