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Hard Fork · · 68 分钟

SignalGate 背后的技术 + Dwarkesh Patel 的“Scaling Era” + AI 正在让我们的听众变笨吗?

Dwarkesh Patel

播客
TL;DR
  • SignalGate 是端点安全和操作纪律的失败,不是 Signal 加密的失败。 18名高级官员使用一款私营部门应用讨论详细的也门打击时间安排,意外把 The Atlantic 的 Jeffrey Goldberg 拉进了群聊,而且显然将消息设置为4周后消失。Casey Newton 给出的判断标准最简洁:“Signal 是一款安全应用,但仅仅使用 Signal,并不会让你的消息安全。”

  • 这起事件暴露出一个公共部门技术市场:易用性、互操作性与合规要求仍然严重错位。 安全的政府系统并非不存在,包括不接入公共互联网的网络、SCIF 以及 Microsoft 的 Azure Government,但各机构使用着一套拼凑式系统,让跨机构协调变得异常笨重。Kevin Roose 认为,商业产品或许能缩小这一差距;Casey 则认为,战争计划“可能本来就应该非常烦琐、非常不方便”。

  • Dwarkesh Patel 认为规模化会产生智能,但没人能给出令人满意的解释。 他目前最好的解释是,智能由一堆“杂凑”的模式匹配回路构成,能够识别不断上升的抽象层次,从猫到时间、光速这样的概念。他不接受人类与机器之间存在某种非物质本质的说法,但也承认今天的系统仍然缺乏常识、持久记忆,以及维持一个月任务连贯性的能力。

  • Patel 认为,大多数科技公司 CEO 的行为,并不像是真的预期 AGI 即将到来。 如果自主远程员工近在眼前,它们的价值将达到“数十万亿美元”,这会让虚拟机部署、安全护栏和大规模算力储备的重要性超过争夺聊天机器人市场份额。他用约7万美元的人均 GDP 粗略代表人类智能的价值;如果算力能够实例化相当水平的智能,算力就会成为一个巨大的瓶颈。

  • 对 AI 的乐观,并不能让它的下行风险变得可以接受。 Patel 仍然认为 AI 净利多于弊的概率更高,但他称10%或20%的 p(doom)“不可接受”;其上行图景是,更多人——无论是生物人还是数字人——都能体验连接、学习、喜悦及其他巅峰体验。他的判断标准是:未来的人是否会拒绝1500年的任何财富,转而选择一个普通的未来生活水平。

  • 在经济实现自动化之前,AI 可能先提高知识与行动力的回报。 Patel 转述朋友 Asholto Douglas 的框架称,人们可能拥有“100倍的未来杠杆”。他的建议是深入理解一个行业,找到真正的问题,并保留在模型仍然无法行动之处采取行动的能力。由于传统职业建议很快就会过时,他更明确的处方是相信真正的兴趣,并“进行更多实验”。

  • 听众的经历显示,AI 既能放大能力,也会加大人们放弃理解的压力。 一位圣公会牧师、一名程序员和一位 ADHD 患者分别描述了更好的检索、调试和思路整理体验;一位 Airtable 用户甚至把 ChatGPT 的错误指令转化成了可行的解题线索。但一名学生发现 Cursor 的速度“令人上瘾”,逐渐不再理解它的修复方案,于是 Kevin 区分了提升产出效率的“叉车”与建设能力的“举重”,Casey 则追问:员工最终还会不会有时间进行批判性思考?

摘要 · 为研究而整理的核心内容

1. SignalGate 始于一次基础的群聊控制失误

  • Kevin 还原了 Jeffrey Goldberg 被意外加入“Houthi PC Small Group”的经过;群里还有包括 Marco Rubio、Tulsi Gabbard、Pete Hegseth 和 JD Vance 在内的18名高级官员。

  • 官员否认讨论过机密材料后,The Atlantic 发布了这些消息。Kevin 表示,完整对话似乎包含机密信息,包括详细的打击时间安排;Casey 的判断标准是:这些内容是否会帮助一名胡塞武装成员躲过导弹袭击。

  • 这个日常层面的失误才是关键:既没有识别出那名不明身份的参与者,也没有平台选择阻止对话继续。正如 Casey 打趣的那样,普通社交群聊在分享生日派对信息之前,反而会执行更严格的“操作安全”检查。

2. Signal 的加密无法保护一部已经被攻陷的手机

  • Casey 介绍称,Signal 是一项由非营利组织资助的开源服务,自2014年7月起可用。它既不保存用户聊天记录,也不保存调查人员可能要求提供的联系人元数据,因此被网络安全专业人士广泛视为“黄金标准”。

  • 但关键限定条件在于:“Signal 是一款安全应用,但仅仅使用 Signal,并不会让你的消息安全。” 人类行为和存在漏洞的个人设备,都不在加密协议的保护范围内。

  • Casey 指出,零日漏洞的价格可能达到数百万美元;一旦攻击者进入手机,Signal 的加密就失去意义,因为攻击者可以读取用户所读取的一切。因此,高级官员的个人设备会成为价值极高的攻击目标。

3. 政府安全依赖隔离、摩擦与留痕

  • 获批的替代方案包括面对面交谈、通常不允许手机进入的 SCIF、与公共互联网隔离的网络,以及专门用于处理机密信息的服务。

  • Kevin 发现的不是一个无缝衔接的政府统一通信工具,而是一套拼凑式系统:国防部门和国务院可能使用不同系统,使跨机构对话变得复杂。Microsoft 的 Azure Government 展示了这个专业化市场的形态:客户群有限,因此需要强大的产品和销售团队。

  • Signal 的阅后即焚消息又带来了另一个问题。这个群聊似乎设置了4周删除窗口,但《联邦记录法》和《总统记录法》要求保存政府通信,包括重大决策背后的推理过程,例如那些会导致人员死亡的军事行动。

4. 主持人就改善政府用户体验是否是答案产生分歧

  • Casey 推测,误邀可能有一个合理解释:Signal 的消息请求可能只显示姓名首字母,而不是完整姓名,用户只能在“一锅首字母汤”里搜索。这让错误变得可以理解,也让 Signal 更不适合用于战争计划。

  • Kevin 用奥卡姆剃刀解释这一事件:便利性。Signal 比获批工具更直观,官员自然会寻找“便利与安全之间恰到好处的组合”。他希望这场闹剧能推动一款具有竞争力、可互操作、由政府拥有的产品出现。

  • Casey 拒绝同情这种权衡。战争计划“可能本来就应该非常烦琐、非常不方便”;那些层层累积的规程本来就是在保护某种东西,而硅谷从第一性原理重新打造一切的习惯,可能会丢掉旧系统中沉淀的经验。

  • Kevin 称这种行为“可能愚蠢到不可原谅”,而不是可以被原谅。他曾收到双方发来的 Signal 消息和个人 Gmail 邮件,但 Casey 指出,这并不能证明此前的政府曾在那里计划军事打击。

5. Patel 的规模化历史保留了技术上的不确定性

  • Patel 最初利用业余时间做播客,给经济学家和历史学家发冷邮件,后来把它当作大学毕业后的间隔年。播客意外走红后,它成了比传统计算机科学工作“更有趣的创业公司”。

  • 他的方法是在无意中形成的:“这就是我,是为我做的。” 他会提出人们在晚餐时可能会问的关键问题,而《Scaling Era》则把2019—2025年的访谈整理成一份写给“另一个领域里聪明的大学室友”的注释版入门读物。

  • 当被问到规模化为什么有效时,Patel 坦率回答:没人有一个好的解释。他目前最好的解释是一堆“杂凑”的回路,其模式匹配能力从识别猫一路提升到思考时间、以太和光速。

6. 模型持续推进“人类”智能的边界

  • Kevin 不接受彻底的物质主义,疑问伦理或情境判断是否需要某种超越算力、数据和下一个 token 预测的东西。Patel 无法指出物质系统之外任何可以拿来辩论的机制。

  • Patel 指出,GPT-4 和 Claude 已经能够阐述伦理,然后反问:“你觉得你的伦理从哪里来?” 同一社会中的人也许能在约99%的基础问题上达成一致,但与1500年的人可能只有50%的共识,因为双方的“训练分布”不同。

  • Casey 提出的制衡因素是当前能力:模型在常识、记忆,以及从未出现在训练数据中的技能获取方面仍然薄弱。因此 Patel 表示,对未来2—3年内出现 AGI 持怀疑态度是合理的;要实现跨越一个月的连贯性,可能需要5年或10年。

  • Patel 所称的“差距智能”,指的是一种绝对判断:机器永远不会抵达智能。Aristotle 曾把推理视为人类最本质的能力,但推理恰恰是这些模型首先学会的事情;而他所谓的“纯爬虫脑”能力——例如对物理世界的直觉理解——反而更难。

7. 企业行为尚未给自动化智能定价

  • 除了少数值得注意的例外,Patel 担心的是,AI 领导者并没有一幅具体的成功图景,也没有明确说明成功的障碍是什么。他们会提到2040年治愈癌症,却不说明财富如何重新分配、人类将如何与数十亿高级智能相处,或人类是否有义务不虐待这些系统。

  • “他们几乎没有一个真正被 AGI 说服,”他总结道。一个完全自主的远程员工将价值“数十万亿美元”,因此严肃的 AGI 战略应优先考虑部署接口、安全护栏,或许还有虚拟机,而不是聊天机器人市场份额。

  • 这样一来,算力就会成为一个巨大的瓶颈。Patel 用约7万美元的人均 GDP 作为人类智能价值的经济学粗略指标:如果算力能够生成接近人类水平的智能,那么在部署前锁定算力容量的重要性,就应当超过普通的聊天机器人市场定位。

8. 巨大的上行空间可以与不可承受的 p(doom) 并存

  • Patel 仍然认为 AI 造福人类的概率高于不造福人类,但他拒绝淡化10%或20%的 p(doom)。一切以及所有在乎的人都可能被消灭或剥夺能力,这种可能性“实在是一个高得惊人的数字”。

  • 他的乐观判断更难量化:人类已经知道巅峰体验、爱、好奇和连接是什么,而先进技术可以让更多人——“我们、数字人,随便是什么”——体验到这些东西。

  • 他的历史思想实验是:一笔只能在1500年使用的财富,需要多大才值得人们离开今天?Patel 猜想,“没有任何数量的钱”能胜过普通的现代生活;他希望未来的人对自己的时代也抱有同样的感受。

  • 他还预计,AGI 出现后,人类媒体人格仍将保有价值:即便周围的办公室工作都实现自动化,观众仍可能想要那些能够解释、交谈并与人建立关系的熟悉面孔。

9. AI 可能先奖励更深的知识,再取代工作

  • 对于担心2年内出现 AGI 的学生,Patel 给出的回答很务实:他认为这个时间点不太可能;即便真的发生,个人也几乎无能为力。在更缓慢的情境下,模型首先会提供更多杠杆,而不是完成全面自动化;他转述朋友 Asholto Douglas 的框架,称人们会拥有“100倍的未来杠杆”。

  • 这种杠杆更偏向那些深入理解行业、能识别真实问题,并能够在物理或数字世界中执行的人。Patel 称,现在“可能是身处其中最令人兴奋的时代”。

  • Casey 认为,不断向聊天机器人提问、阅读和综合报告,本身就是劳动;教育仍然是更好的基础,AI 应该被选择性地使用。Kevin 更简单的辩护是:“学习很有趣。”

  • Patel 自己的职业经历也让职业预测建议显得可疑:没有一个合理的顾问会建议年轻时的他放弃计算机科学、转去做播客。他的答案是探索——相信真正的兴趣,避免自欺,并“进行更多实验”。

10. 有意识地使用 AI 可以加深专业能力并扩大获取机会

  • 在讨论 Carnegie Mellon 和 Microsoft 的研究后,主持人收到了近100条回复,但 Casey 提醒其中存在选择偏差。圣公会牧师 Nathan Born 使用 Readwise 和 Claude 检索布道材料,同时把解释和判断工作留给自己。

  • 软件工程师 Jessica Mock 不会在处理自己已经熟悉的代码时使用 Copilot,而是让它进行审查,或询问错误的含义。这种克制让她能够进入陌生的编程语言并真正学习,而不是单纯粘贴输出:“这完全取决于你怎么使用它。”

  • 62岁的 ADHD 营销人员 Gary 把 AI 当作一个无限耐心的思维伙伴:他沿着分叉的思路继续探索,然后要求 AI 总结,而不是重新拼接散落的笔记。收益在于组织信息和追踪想法,而 Gary 仍然负责判断哪些内容是真的。

  • Airtable 高级用户 Anna 连续两轮收到 ChatGPT 的错误指令,但她识别出了两处错误,并最终从中找到解锁方案的线索。Kevin 的限定条件至关重要:正是既有知识,让这个不可靠的助手变得有用。

11. 截止日期压力可能把杠杆变成认知投降

  • 在 Northwestern MBA 的一项实验中,使用电脑的学生比同伴提出了更多非常规想法。教授 Andrew Fano 推断,AI 给了他们一种社会许可:被拒绝的建议不必反映个人能力,因为那是“电脑”提出的。

  • 一名使用 Cursor 的硕士生则走上了相反的道路。随着截止日期临近,“速度令人上瘾”;她从逐行检查代码,转向一轮又一轮自动修复 bug,最后连修复过程都不再理解。

  • Casey 看到了这种投降背后的职场机制:一旦老板提高产出要求、同事开始使用 AI,拒绝使用就可能危及职业生涯。员工可能变成“几乎只是在监督一台机器”,这是人类失去能力的一则小型样本。

  • Kevin 的决策规则是“叉车还是举重”:如果任务的目的只是搬运产出,就把它自动化;如果任务的目的是增强能力,就保留它。Casey 更阴暗的问题是:AI 是否会让人变笨并不是重点,重点是他们到底还会不会有时间进行批判性思考。

Speaker 1

Listen to this. This week, I checked my credit card bill, normally a pretty boring process in my life, and I saw a number that astonished me in its size and gravity. The first thing I thought was, “How much DoorDash is it possible to eat in 1 month? Have I hit some new level of depravity?” But then I went through the statement and found a charge from the heating and plumbing company that I used when I lived in the home of Kara Swisher. Kara Swisher, of course, the iconic technology journalist, friend and mentor, originator of the very podcast feed that we're on today, Kevin.

Speaker 2

And former landlord of Casey Newton.

Speaker 1

Former landlord of me. When I investigated, it turned out that Kara Swisher had charged my credit card for $18,000.

Speaker 2

For what? What costs $18,000?

Speaker 1

I don't know what is going on, but it cost $18,000 to fix. Until I made a few phone calls yesterday, that was going to be my problem. So here's what I want to say to the people of America: You need to watch these landlords. You might think that you're out from underneath their thumb, but they will still come for you, and they will put $18,000 on your credit card if you do not watch them.

Speaker 2

Now, this is slightly terrifying to me—the idea that Kara has access to your credit card—

Speaker 1

Mm-hmm, mm-hmm.

Speaker 2

—in some way, shape, or form.

Speaker 1

Well, I should say, it was on file with the heating and plumbing company, so I'm not sure that I can actually blame Kara for this, but I did have to talk to her about it.

Speaker 2

Oh, she's crafty. I think she knew what she was doing.

Speaker 1

She's been waiting to get back at us like this for a long time. Mission accomplished, Kara.

Speaker 2

I'm Kevin Roose, a tech columnist at The New York Times.

Speaker 1

I'm Casey Newton from Platformer.

Speaker 2

And this is Hard Fork.

Speaker 1

This week, the group chat that's rocking the government. We'll tell you why the government turned to Signal for planning military operations and why it's probably not a great idea. Then, podcaster Dwarkesh Patel stops by to discuss his new book and tell us why he still believes AI will benefit all of us in the end. And finally, we asked you if AI was making you dumber. It's time to share what you all told us.

Speaker 2

I feel smarter already. Well, Casey, the big story of the week is Signal-gate.

Speaker 1

Yes. What I would say, Kevin, is the group chats are popping off at the highest levels of government.

Speaker 2

Yes. And if you have been hiding under a rock or on a silent meditation retreat for the last few days, let's quickly catch you up on what has been going on.

Speaker 1

Yeah.

1. The Signal Gate Failure

Speaker 2

So on Monday, The Atlantic, and specifically Jeffrey Goldberg, the editor in chief of The Atlantic, published an article titled “The Trump Administration Accidentally Texted Me Its War Plans.” In this article, Goldberg details his experience of being added, seemingly inadvertently, to a Signal group chat with 18 of the U.S.'s most senior national security leaders, including Secretary of State Marco Rubio, Tulsi Gabbard, the director of national intelligence, Pete Hegseth, the secretary of defense, and even Vice President JD Vance. The chat was called “Houthi PC Small Group,” with PC presumably standing for Principals Committee and not personal computer.

Speaker 1

Mm-hmm.

Speaker 2

And I would say this story lit the internet on fire.

Speaker 1

Absolutely. We have secure communications channels that we use in this country, Kevin, to organize and plan for military operations. They were not used in this case. That is a big deal in its own right. But to accidentally add one of the more prominent journalists in all of America to this group chat as you're planning it is truly unprecedented in the history of this country.

Speaker 2

Yeah, and unprecedented in my life, too. I never get invited to any secret, classified group chats. But I also feel like there is an etiquette and a procedure around the midsize group chat.

Speaker 1

Yes.

Speaker 2

So I'm sure you've had the experience of being added to a group chat. In my case, it's usually planning a birthday party or something, and there's always a number or two on this group chat that you don't have stored in your phone, right?

Speaker 1

That's right.

Speaker 2

The unfamiliar area code pops up along with the named accounts of everyone who you do know who's in this group chat.

Speaker 1

Absolutely.

Speaker 2

And the first thing that I do when that happens to me is try to figure out who the unnamed people in the group chat are.

Speaker 1

Yes.

Speaker 2

And until you figure that out, you can't be giving your A material to the group chat.

Speaker 1

This is so true. I saw someone say on social media this week that gay group chats have so much better operational security than the national security adviser does. And this is the exact reason. If you're going to be in a group with 7 or 8 people and there's 1 number that you don't recognize, you're going to be very tight-lipped until you find out who this interloper is.

Speaker 2

Exactly.

Speaker 1

Yeah.

Speaker 2

And maybe someone will even say, “Who? Hey, who's 347?” There's a protocol for this, is what I'm saying.

Speaker 1

Yes, it's a protocol that, as you're pointing out, most people take extremely seriously.

Speaker 2

Yes. But—

Speaker 1

Even when they are talking about things like planning birthday parties—

Speaker 2

Yes.

Speaker 1

—and not military strikes.

Speaker 2

Exactly.

Speaker 1

Yeah.

Speaker 2

So before we get into the tech piece, let's say what has been happening since then. This story came out on Monday in The Atlantic. Everyone freaked out about it. The government officials involved in this group chat were asked to respond to it. There was actually a hearing in Congress where several of the members of this group chat were questioned about how a reporter got access to these sensitive conversations. Basically, the posture of the Trump officials implicated in this has been to deny that this was a secret at all. There have been various officials saying nothing classified was discussed in it. This wasn't an unapproved use of a private messaging app. Basically, nothing to see here, folks.

Speaker 1

Yes, and on Wednesday, The Atlantic actually published the full text message exchanges so that people could go read these things for themselves and see just how detailed the plans shared were.

Speaker 2

Yes. Let's just say it does look like some of this information was in fact classified. It included details about the specific timing of various airstrikes that were being ordered in Yemen against the Houthis, which are a rebel terrorist militia. This was not a party-planning group chat.

Speaker 1

Here's a good test for you. When you read these chats, imagine you're a Houthi in Yemen. Would this information be useful to you to avoid being struck by a missile? I think it would be. To me, that's the test here, Kevin.

Speaker 2

Totally.

Speaker 1

Yeah.

2. Signal Is Not Enough

Speaker 2

So let's dive into the tech of it all, because I think there is actually an important and interesting tech story beyond the headlines here. So, Casey, what is Signal and how does it work?

Speaker 1

Signal, as you well know as a frequent user, is an open-source, end-to-end encrypted messaging service that has been with us since July 2014. It has been growing in popularity over the past several years. A lot of people like the fact that, unlike something like an iMessage or a WhatsApp, this is built by a nonprofit. It's funded by a nonprofit organization, and it is fully open source. It's built on an open-source protocol, so anyone can look and see how it is built. They can poke holes in it and try to make it more secure. As the world has evolved, more and more people have found reasons to have both end-to-end encrypted chats and disappearing chats. Signal has been part of this move away from permanent chats stored forever to more ephemeral, more private communications.

Speaker 2

Yeah. And I think we should add that among the people who think about cybersecurity, Signal is seen as the gold standard of encrypted communications apps. It is not perfect. No communications platform is ever perfectly secure, because it is used by humans on devices that are not perfectly secure. But it is widely regarded as the most secure place to have private conversations.

Speaker 1

If you want to know why that is, we could go into some level of detail here. Signal makes it a priority to collect as little metadata as possible. For example, if the government went to them and said, “Hey, we have Kevin's Signal number. Tell us all of the contacts that Kevin has,” they don't actually know that. They don't store that. They also do not store the chats themselves, right? Those are on your devices. So if the government says, “Hey, give us all of Kevin's chats,” they don't have those. And there are some pretty good encryption and privacy practices in some of the other apps that I think a lot of our listeners use on a daily basis.

WhatsApp has pretty good protection. iMessage has pretty good protection, but there are a bunch of asterisks around that. And so, if security is super, super important to you, then I think many of us would actually recommend Signal as the best place to do your communicating.

Speaker 2

Yeah, and you and I both use Signal. Most reporters I know use Signal to have sensitive conversations with sources. I know that Signal has been used by government officials in both Democratic and Republican administrations for years now. So, Casey, I guess my first question is: Why is this a big deal that these high-ranking government officials were using Signal if it is sort of the gold standard of security?

Speaker 1

Sure. I would try to put it in maybe 2 sentences, Kevin, that sums this whole thing up. Signal is a secure app, but using Signal alone does not make your messages secure.

So what do I mean by that? Well, despite the fact that Signal is secure, your device is vulnerable, particularly if it's your personal device, if it's your iPhone that you bought from the Apple Store. There is a huge industry of hackers out there developing what are called zero-day exploits, and a zero-day exploit is essentially an undiscovered hack. They are available for sale on the black market. They often cost millions of dollars, and criminals, and more often state governments, will purchase these attacks because they say, “Hey, it is so important to me to get into Kevin's phone. I have to know what he's planning for Hard Fork this week. So I'm going to spend $3 million. I'm going to find a way to get onto his personal device.”

And if I have done that, even if you were using Signal, it doesn't matter because I'm on your device now. I can read all of your messages, right? So this is the concern. So, wait, what are American military officials supposed to do instead? Well, we have specially designated channels for them to use. We have networks that are not the public internet, right? We have messaging tools that are not commercially available, and we have set up protocols to make them use those protocols to avoid the scenario that I just described.

3. Government Secure Channels

Speaker 2

Yeah, so let's go into that a little bit because, as you mentioned, there are designated communications platforms and channels that high-ranking government officials, including those with access to classified information, are supposed to use, right?

Speaker 1

Yeah.

Speaker 2

There are these things called SCIFs, these Sensitive Compartmented Information Facilities. Those are the physical rooms that you can go into to receive classified briefings. Usually, you have to keep your phone out of those rooms for security.

Speaker 1

Yeah, I keep all of my feelings in a Sensitive Compartmentalized Information Facility.

Speaker 2

But you're working on that in therapy.

Speaker 1

I'm working on that. I'm working on it.

Speaker 2

But if you're not physically in the same place as the people that you're trying to meet with, there are these secure communication channels. Casey, what are those channels?

Speaker 1

Well, there are just specialized services for this. This is what a lot of the tech giants work on. Microsoft has something called Azure Government, which is built specifically to handle classified data, and this is sort of rarefied air, right? Not that many big platforms actually go to the trouble of making this software. It's a pretty small addressable market, so you have to have a really solid product and a really good sales force to make this worth your while. But the stuff exists, and the government has bought these services over the years and installed them, and this is what the military is supposed to use.

Speaker 2

Yeah, so I did some research on this because I was basically trying to figure out: Are these high-ranking national security and government officials using Signal because it is the easiest and most intuitive thing for them to use? Are they doing it because they don't want to use the stuff that the government has set up for its own employees to communicate? Why were they doing this?

Because one thing that stuck out to me in the transcripts of these group chats is that nobody in the chats seems surprised at all that this was happening on Signal, right? No one, when this group was formed and these 18 people were added to it, said anything about, “Hey, why are we using Signal for this? Why aren't we using Microsoft Teams,” or whatever the official approved thing is.

What I found out when I started doing this research is that there is something of a patchwork of different applications that have been cleared for use by various agencies of the government. And one reason that these high-ranking government officials may have been using Signal instead of these other apps is because some of these apps are not designed to work across the agencies of government, right? The DoD has its own communication protocols. Maybe the State Department has its own communication protocols. Maybe it's not trivially easy to start up a conversation with a bunch of people from various agencies on a single government-owned and controlled tool.

Speaker 1

Yeah. And that should not surprise us because something that is always true of secure communications is that it is inconvenient and annoying. This is what makes it secure: You have gone to great lengths to conceal what you are doing.

I read some reporting in The Washington Post this week that, for the most part, when they are doing their most sensitive communications, those communications are supposed to be done in person, right? That is the default. And if you cannot do it in person, then you're supposed to use these secure communication channels. Again, not the public internet. So that is the protocol that was not followed here.

4. Why Officials Chose Signal

Speaker 2

Right. And I think one other possible explanation for why these high-ranking officials were using Signal is that Signal allows you to create disappearing messages, right? That is a core feature of the Signal product: You can set, in any group chat, for all these messages to delete themselves after an hour, a day, or a week. In this case, they seem to have been set to delete after 4 weeks.

Now, there are good reasons why you might want to do that. If you're a national security official, you don't want this stuff to hang around forever. But we should also say that that is an apparent violation of the rules for government communication because there are records acts that require the preservation of government communications. And so one reason that the government and various agencies have their own communications channels is because those channels can be preserved to comply with these laws about federal record-keeping.

Speaker 1

Yes. There is a Federal Records Act and a Presidential Records Act, and the idea behind those laws, Kevin, is that, well, if the government is planning a massive war campaign that will kill a bunch of people, we should have a record of that. In a democracy, you want there to be a preservation of some of the logic behind these attacks that the government is making. So, yes, it seems like they clearly have just decided they're not going to follow those.

Speaker 2

Yeah. And so I think the place where I land on this is that this is, I would say, obviously, a dumb, probably unforgivably dumb mistake—

Speaker 1

Mm-hmm.

Speaker 2

…on the part of a high-ranking national security official. My favorite sort of cover-up attempt on this was the National Security Advisor, Michael Waltz, being asked how this happened because he was the person, according to these screenshots of this chat, who added Jeffrey Goldberg from The Atlantic to this chat. And he basically gave the statement that was like, “We're all trying to figure out what happened here.” It's like, we saw the screenshot, Michael. You added him.

Speaker 1

Yeah.

Speaker 2

And I think there are obvious questions that raises about whether he had mistaken him for someone else named Jeffrey Goldberg, maybe a national security official of some kind.

Speaker 1

Oh, I bet the words “Jeffrey Goldberg” never even appeared on Michael Waltz's screen. Okay, this is the realm of pure speculation, but let me just tell you, as somebody who is routinely contacted by people anonymously on Signal, usually their full name is not in the message request. It's like, “You have a new message request from JG,” so it's just those initials.

And so I will look through my Signal chats, and I'll be trying to think, “Oh, I want to ask that one person about the one thing. What was their Signal name?” And I'm looking through a soup of initials. So, I actually understand why that happened, which is yet one more reason why you might not want to use Signal to do your war planning.

Speaker 2

Yes. Exactly. I think the most obvious sort of Occam's razor explanation for why all these high-ranking officials are on Signal is that it's just a better, easier, and more intuitive product than anything the government is supposed to be using for this stuff.

Speaker 1

It's more convenient.

Speaker 2

Yes. And I find this totally plausible, having spoken with people who have been involved with government technology in the past. It is just not the place where cutting-edge software is developed and deployed.

There famously was this sort of struggle between President Obama and some of his security advisors when he wanted to use a BlackBerry in the Oval Office, and there was sort of no precedent for how to do that securely. And so he fought them until they made him a special BlackBerry that he could use. This is a time-honored struggle between politicians who want to use the stuff that they used when they were civilians while in political office and are told again and again, “You can't do that. You have to use this clunkier, older, worse thing instead.”

Speaker 1

Well, I'm detecting a lot of sympathy in your voice for the Trump administration here, which is somewhat surprising to me. Because while I can stipulate that they must go through an annoying process in order to plan a war, I'm somebody who thinks, well, it probably should be really annoying and inconvenient. You probably should actually have to go physically attend a meeting to do all of this stuff. And if we are going to decide that war planning is something that the secretary of defense can do during commercials for March Madness, just pecking away on his iPhone, we're going to get in a lot of trouble.

Imagine you're an adversary of America right now, and you've just found out that the entire administration is chatting away on their personal devices. Do you not think that they have gone straight to the black market and said, "What's a zero-day exploit that we can use to get on Pete Hegseth's phone?" Of course they have.

Speaker 2

For sure. So what I'm not saying here is that this is excusable behavior. What I am saying is that I think people, including government officials, will gravitate toward something that offers them the right mix of convenience and security. And I would like for this to be an incident that spurs the development of much better and more secure ways for the government to communicate with itself.

It should not be the case that if a bunch of high-ranking officials want to start a group chat with each other, they have to go to this private-sector app rather than something that the government itself owns and controls and that can be verifiably secure.

Speaker 1

Mm-hmm.

Speaker 2

So yes, I think this was extremely dumb. It is also, by the way, something that I'm sure was happening in Democratic administrations too. This is not a partisan issue here.

Speaker 1

Well, what exactly do you think was happening? Yes, the Democrats were using Signal, and yes, they were using disappearing messages. It's not clear to me that they were planning military strikes.

Speaker 2

I don't know. I have no information either way on that. What I do know is that I have gotten messages on Signal from officials in both parties. I have gotten emails from the personal Gmail accounts of administration officials in both parties. This is, I think, an open secret in Washington: The government's own tech stack is not good, and a lot of people, for reasons of convenience or privacy or what have you, have chosen to use these less secure private-sector things instead.

And I think I should make a serious point here—

Speaker 1

Mm-hmm.

Speaker 2

—which is that it is in the national interest of the United States to have a smaller gap between the leading commercial technology products and the products that the government is allowed to use, right?

Speaker 1

Mm-hmm.

Speaker 2

Right now in this country, if you are a smart and talented person who wants to go into government, one of the costs of that move is that you effectively have to go from using the best stuff that anyone with an iPhone or an Android phone can use to using this more outdated, clunkier, less intuitive set of tools.

Speaker 1

Mm-hmm.

Speaker 2

I do not think that should be the case. I think that the stuff that the public sector is using for communication, including for very sensitive things, should be as intuitive and easy to use and convenient as the stuff that the general public uses. Yes, it should have additional layers of privacy. Yes, you should have to do some kind of procurement process.

But a recurring theme on this podcast whenever we talk about government and tech is that it is just way too slow and hard to get standard tools approved for use in government. So if there's one silver lining of the Signal-gate fiasco, I hope it is that our government takes access to good technology products more seriously and starts building things and maintaining things that are actually competitive with the state of the art.

Speaker 1

I'm going to take the other side of this one, Kevin. I think if you look at the way that the government was able to protect its secrets in previous administrations, prior to the spread of Signal, it was actually able to prevent high-ranking officials from accidentally adding journalists to conversations that they shouldn't have been in. There is no evidence to me that because of the aging infrastructure of the communication systems of government, we were unable to achieve some sort of military objective.

Even as somebody who generally likes technology, I think some of these tech oligarchs have this extremely know-it-all attitude: "Our tech is better than your tech. Yours sucks." And they bluster in and say, "All of your aging legacy systems, we can just get rid of those and move on to the next thing." Then you wake up after Signal-gate and you're like, "Oh, that's why there was a system. That's why there was a protocol. It turns out it was actually protecting something."

This is the Silicon Valley story over and over again: We are going to come in and try to build everything from first principles. We're going to be completely ahistorical. We're not going to learn one lesson that anyone else has ever learned before because we think we're smarter than you. Signal-gate shows us that actually, no. Sometimes people have learned things, and there is wisdom to be gleaned from the ages, Kevin. Maybe that should have been done here.

Speaker 2

Well, Casey, the Defense Department may be in its failing era, but AI is in its scaling era. We'll talk to the author of The Scaling Era, Dwarkesh Patel, when we come back.

5. Meet Dwarkesh Patel

Well, Casey, there are a number of people within the clubby and insular world of AI who are so well known that they go by a single name.

Speaker 1

That's true.

Speaker 2

There's—

Speaker 1

Madonna, Cher, and who else?

Speaker 2

Well, there's Dario, Sam, Ilya, various other people, and then there's Dwarkesh—

Speaker 1

Yes.

Speaker 2

—who is not working at an AI company. He is an independent journalist, podcaster—

Speaker 1

Blogger.

Speaker 2

—public intellectual, blogger. He hosts the Dwarkesh Podcast, which has had a number of former Hard Fork guests on it, and he's, I would say, one of the best-known media figures in the world of AI.

Speaker 1

Yeah, absolutely. Dwarkesh seemingly came out of nowhere a few years back and quickly became well respected for his highly technical, deeply researched interviews with some of the leading figures, not just in AI, but also in history and other disciplines. He is a relentlessly curious person, but I think one of the reasons why he is so interesting to us is that on the subject of AI, he has developed an incredible roster of guests and a great understanding of the material.

Speaker 2

Yes. And now, as of this week, he has a new book out, which is called The Scaling Era: An Oral History of AI, 2019–2025. It is mostly excerpts and transcripts from his podcast and the interviews that he's done with luminaries in AI. But through it, he assembles the history of what's been happening for the past 6 or so years in AI development, talking to some of the scientists and engineers who are building it, the CEOs who are making decisions about it, and the people who are reckoning with what it all means.

Speaker 1

Indeed. So we have a lot to ask Dwarkesh about, and we're excited to get him into the studio today and hang out.

Speaker 2

All right. Let's bring in Dwarkesh Patel. Dwarkesh Patel, welcome to Hard Fork.

Dwarkesh Patel

Thanks for having me.

Speaker 2

I want to start with the Dwarkesh origin story. You are 24 years old.

Dwarkesh Patel

Yeah.

Speaker 2

Correct? You graduated from UT Austin, and you majored in computer science. I'm sure a lot of your classmates and people with your interest in tech and AI chose the more traditional path of going to a tech company, starting to work on this stuff—

Dwarkesh Patel

Yeah.

Speaker 2

Directly. Presumably, that was a path available to you.

Dwarkesh Patel

Mm-hmm.

Speaker 2

Why did you decide to start a podcast instead?

Dwarkesh Patel

It was never my intention for this to become my career. I was doing this podcast in my free time. I was interested in these economists and historians, and it was just cool that I could cold-email them and get them to come on my podcast, and then pepper them with questions for a few hours.

When I graduated, I didn't really know what I wanted to do next, so the podcast was almost a gap-year experience: Let me do this; it'll help me figure out what kind of startup I want to launch or where I can get hired. And then the podcast went well enough that, dot, dot, dot, I'm like, “Yeah, this could actually be a career.”

Speaker 2

Mm-hmm.

Dwarkesh Patel

This is a more fun startup than whatever code-monkey, you know, 3rd-stint-in-Android kind of job. So I basically just kept it up, and it's grown ever since, and it's been a fun time.

Speaker 2

Yeah. I'm curious how you describe what you do. Do you consider yourself a journalist?

Dwarkesh Patel

I guess so. I don't know if there's a good word. There's journalist, content creator, blogger, podcaster. Sure, journalist, yes.

Speaker 2

Humanitarian. I ask because I started listening to your podcast a while ago, back when it was called The Lunar Society, and the thing that I noticed right away was that you were not doing a ton of explanation and translation.

I often think of our job as journalists as one primarily of translation: taking things that insiders and experts are talking about and making them legible to a broader and less specialized audience. But your podcast was so interesting to me because you weren't really doing that. You were not afraid to stay in the wonky, insider zone.

You were having conversations with these very technical experts in their native language, even if it got pretty insidery and wonky at times. Was there a theory behind that choice?

Dwarkesh Patel

No. Honestly, it never occurred to me, because nobody was listening in the beginning, right? So I think it was a bad use of my guest's time to have said yes in the first place, but now that they've said yes, let's just have fun with this, right? Who is listening to this? It's me. It's for me.

And then what I realized is that people appreciated that style. With a lot of these people, they've done so many interviews. You've heard their “What is your book about?” kind of thing before. The intuition I always go for is: pretend like you're at dinner with this person, and if you're at dinner with them, you'd just ask them about your main cruxes: What's going on here? Here's why I disagree with you. You tease them about their big ideas or something. But initially, it was just an accident.

Speaker 2

Yeah.

Dwarkesh Patel

I think in mainstream media, we are terrified that you might read something we write or listen to something we do and not understand a word of it, because there's always an assumption that that is the moment that you will stop reading. I think what you have discovered with your podcast is that that's actually a moment that causes people to lean in—

Speaker 2

Mm-hmm.

Dwarkesh Patel

—and say, “Hmm, I didn't get all of that, but I'm getting enough of it that I'm curious: What is this thing that's going to happen next?”

Speaker 2

Right. And everyone's got Google, right? So if you don't understand something—or ChatGPT—you can—

Dwarkesh Patel

That's right.

Speaker 2

—always look it up—

Dwarkesh Patel

Yeah.

Speaker 2

—in a way that may not have been possible with talk radio back in the day or something.

Dwarkesh Patel

Yeah.

Speaker 2

That's right.

Dwarkesh Patel

That's right.

Speaker 2

So you've got this new book out, The Scaling Era, basically a sort of oral history of the past 6 or so years of AI development. Tell us about the book.

Dwarkesh Patel

I have been doing these interviews with the key people thinking about AI over the last 2 years: CEOs like Mark Zuckerberg, Demis Hassabis and Dario Amodei; researchers working at a deeply technical level; economists who are thinking about what the deployment of these technologies will be like; and philosophers who are talking about these essential questions about AI ethics and how will we align systems that are millions of times more powerful or, at least, more plentiful.

These are some of the most gnarly, difficult questions that humanity has ever faced, like: What is the true nature of intelligence? What will happen when we have millions of intelligent machines running around in the world? Is the idea of superhuman intelligence even a coherent concept? What exactly does that mean, and what exactly will it take to get there, obviously?

All of it was such a cool experience, just to see all of that organized in this way, where we would have annotations and definitions and beautiful graphs. My co-author, Gavin Leach, our editor, Rebecca Hiscott, and the whole team did a wonderful job making this really beautiful artifact. So that's the book.

Speaker 2

I also really liked the way that the book slows down and explains some of these basic concepts and footnotes the relevant research. It really is more accessible than I would say the average episode of the Dwarkesh Podcast, in the sense that you can really start from the beginning.

I would feel comfortable giving this to someone as a gift who doesn't know a ton about AI and saying, “This is a good primer to what's been happening for the past few years in this world.”

Dwarkesh Patel

And it won't treat you like an idiot. A lot of these other AI books are just about this big picture: How will society be changed? And it's like, no, to understand AI, you need to know what is actually happening with the models, what is actually happening with the hardware, and what is actually happening in terms of investments and CapEx and whatever. We'll get into that.

But also, because of the enhancement with the notes, definitions and annotations, it's written for a smart college roommate in a different field.

6. Why Scaling Creates Intelligence

Speaker 2

One question that you asked at least a couple of people in your book, in some version, was basically: What's their best guess at why scaling works? Why does pouring more compute and more data into these models tend to yield something like intelligence? I'm curious what your answer for that is. What's your current best guess of why scaling works?

Dwarkesh Patel

I honestly don't think anybody has a good answer. The best one I've heard is this idea that intelligence is just a hodgepodge of different kinds of circuits and programs. This is so hand-wavy, and I acknowledge this is hand-wavy, but you have to come up with some answer.

Fundamentally, what intelligence is is this pattern-matching thing, this ability to see how different ideas connect and so forth. As you make this bucket bigger, you can start off with noticing whether this looks like a cat or not, and then you get to higher and higher levels of abstraction, like what is the structure of time and the so-called ether and the speed of light and so forth. Again, so hand-wavy, but I think it ultimately will just be this hodgepodge.

Speaker 1

It does strike me that this feels similar to the way that human beings work. You're born into the world, and you essentially get blasted with data for many, many years until you have some kind of symbolic understanding of everything, and then you go from there. That's how I think about it.

Speaker 2

Yeah, there seems to be this philosophical divide among the AGI believers and the AGI skeptics over the question of whether there is something other than just materialism in intelligence, whether intelligence is just a function of having the right number of neurons and synapses firing at the right times, and sort of pattern-matching and doing next-token prediction.

I'm thinking of this famous Sam Altman tweet where he posted, “I am a stochastic parrot, and so are you,” basically rebutting the common attack on large language models, which was that they were just stochastic parrots. They're just learning to regurgitate their training data and predict the next token.

And among a lot of the AGI true believers that I know, there is this feeling that we are just essentially doing what these language models—

Dwarkesh Patel

Yeah.

Speaker 2

—are doing in predicting the next tokens or synthesizing things that we've heard from other places and regurgitating them.

Speaker 1

Right.

Speaker 2

That's a hard pill for a lot of people to swallow, including me. I'm not quite a full materialist. Are you? Do you believe that there's something about intelligence that is not just raw processing power and data and pattern-matching?

Dwarkesh Patel

I don't. It's hard for me to think about what that would be. There are obviously religious ideas that there may be a soul or something like that, but separate from that, something we could debate about or analyze. I'm actually curious about what kind of thing it could be.

Speaker 2

Ethics? I don't know. That sounds very fuzzy and non-scientific, but I do think there is something essential about intelligence and being situationally intelligent that requires something outside of your immediate experience, like knowing what is right and what is wrong.

Speaker 1

Well, I think one reason why this question might be a bit challenging is that there are still many areas where the AI we have to date is just less than human in its quality level, right? These machines don't really have common sense. Their memories are not great. They don't seem to be great at acquiring new skills, right? If it's not in the training data, sometimes it's hard for them to get there.

And so it does raise the question: Is the kind of intelligence we have categorically different from whatever this other kind of intelligence is that we're inventing?

Speaker 2

Yeah.

Dwarkesh Patel

That's right. On the ethics thing, I think it's notable that if you talk to GPT-4, it has a sense of ethics.

Speaker 2

Mm-hmm.

Dwarkesh Patel

If you talk to Claude, it has a sense of ethics. You talk about animal ethics or some kind of moral dilemma, and it has a sense of ethics. I'm not sure what you mean by “a sense of ethics.” In fact, the worry is that it might have too strong a sense of ethics, right? By that, I'm referring to maybe its ethics becoming something like, “I want more paper clips.”

Speaker 2

Sure.

Dwarkesh Patel

Or, I mean, sorry, on a more serious note—

Speaker 2

But those ethics are given to it in part by the process of—

Speaker 1

Yeah.

Speaker 2

—training and fine-tuning the model or making it obey some constitution, like—

Dwarkesh Patel

Where do you think you get your ethics?

Speaker 1

Who trained you, Bruce?

Speaker 2

Yeah. I mean—

Dwarkesh Patel

I mean, it is notable that most people in a given society share the basic worldview that, like, you and I agree on 99% of things, and we would probably agree on 50% of things with somebody in the year 1500.

Speaker 1

Mm-hmm.

Dwarkesh Patel

And the reason we agree on so much has to do with our training distribution, which is the society we live in.

Speaker 2

Yeah.

Dwarkesh Patel

Yeah.

Speaker 2

So, yeah, maybe this argument that there is something more to intelligence than just brute-force computation is somewhat romantic.

Speaker 1

It's what they call cope.

Speaker 2

Yes. I was trying to figure out a more sophisticated way of saying “cope,” but do you think that is cope? Do you think that the people who are skeptical of the possibility of AGI because they believe that computers lack something essential that humans have are just responding to not being able to cope with the possibility that computers could replace them?

Dwarkesh Patel

I think there's 2 different questions. One is: Is it cope to say that we won't get AGI in the next 2 years or 3 years, or whatever short timelines some people in San Francisco—some of our friends—seem to have? I don't think that's cope. I think there are actually a lot of reasonable arguments one can make about why it will take a longer period of time. Maybe it'll be 5 years, 10 years. Maybe this ability to, as you were saying, keep coherence and engage with a task over the course of a month just requires a different kind of skill than these models currently have. I don't think that's cope.

I think the idea that we'll never get there is cope because there's always this argument of the God of the gaps, of the intelligence of the gaps. The thing it can't do is the thing that is fundamentally human. One notable thing: Aristotle had this idea that what makes us human is fundamentally our ability to reason, and reasoning is the first thing these models have learned to do. They're not that useful at most things except for raw reasoning.

Whereas the things we think of as pure reptile brain—having an understanding of the physical world as we're moving about in it or something—that is a thing these models struggle with. So we'll have to think about what the archetypal human skill set is as these models advance.

Speaker 1

That's fascinating. That never actually occurred to me. I think it speaks a lot to why people find them so powerful in this therapist, mentor, or coach role, right? Those figures that we bring into our lives are often just there to help us reason through something, and these models are increasingly very good at it.

Dwarkesh Patel

That's right.

Speaker 1

Yeah.

7. The Case For AI Optimism

Speaker 2

In your conversations with all these AI researchers and industry leaders, are there any blind spots that you feel they have consistently, or places where they are not paying enough attention to the consequences of developing AI?

Dwarkesh Patel

I think, with a few notable exceptions, they don't have a concrete sense of what things going well looks like and what stands in the way.

If you just ask them what the year 2040 looks like, they'll say things like, “Oh, we'll cure cancer. We'll cure these diseases.” But what is our relationship to billions of advanced intelligences? How do we do redistribution such that the—it's not your or my fault that we'll be out of a job, right? There's no in-principle reason why everybody couldn't be better off, but there shouldn't be a zero-sum thing where we should make sure the AIs don't take over, and we should also make sure we don't treat them terribly.

Speaker 1

Something else that's been on my mind recently that you're sort of getting at—or that maybe you were getting at with your question, Kevin—is how seriously the big tech companies take the prospect of AGI arriving. On the one hand, they'll tell you, “We're the leading frontier labs. We're publishing some of the best research. We're making some of the best products.” And yet it seems like none of them are really reckoning with any of the questions that you just raised.

It sort of makes sense. Even saying some of the stuff that you just said right now, which seems quite reasonable to me, would sound weird if Satya Nadella were talking about it on an earnings call, right? And yet, at the same time, I just want—

Speaker 2

Quarter 4 was so strong, with 4,000 happy AIs growing 10% year over year.

Speaker 1

Yeah.

Speaker 2

Right.

Speaker 1

But, like, on some level it's weird to me. Somebody was recently talking to me about Google and was sort of saying, “If you look at what Google is shipping right now, it doesn't seem like they think that very powerful intelligence is going to arrive anytime soon.”

Speaker 2

That's right.

Speaker 1

What they're taking seriously is the prospect that ChatGPT will replace Google Search.

Dwarkesh Patel

Yeah.

Speaker 1

And that maybe if you actually did take AGI seriously, you would have a very different approach to what you were doing. So, as somebody who has talked to the CEOs of these companies, I'm curious: How seriously do you think they're actually taking AGI?

Dwarkesh Patel

I think almost none of them are AGI-pilled.

Speaker 2

Yeah.

Dwarkesh Patel

They might say the word AGI, but if you just ask them, “What does it mean to have a world with actually automated intelligence?” there are a couple of immediate implications.

Right now these companies are competing with each other for market share in chat. If you had a fully autonomous worker, even a remote worker, that's worth tens of trillions of dollars. That's worth way more than a chatbot, right? So you'd be much more interested in deploying that kind of capability. I don't know if API is the right way; maybe it's a virtual machine or something. I'd be much more interested in developing the UI, the guardrails, and whatever else is needed to make that work than trying to get more people to use my chat app.

And then I also think compute will just be this huge bottleneck. If you really believe that what compute buys you is human-level intelligence, human intelligence is worth a lot, right? We can just look at every GDP per capita—it's around $70,000 or something. So I would be interested in getting as much compute as possible and having it ready to deploy once the AIs are powerful enough.

Speaker 1

Mm. Mm.

Speaker 2

One of the things I really enjoyed about your book is getting a sense not just of what the people you've interviewed think about AI, AGI, and scaling, but what you believe. And I have to say, I was surprised that at the end of the book you said that you believe AI is more likely than not to be net beneficial for humanity.

Dwarkesh Patel

Yeah.

Speaker 2

And I was surprised because a lot of the people you talk to have quite high p(doom)s. They're quite worried about the way AI is going.

Dwarkesh Patel

Yeah.

Speaker 2

That seems not to have spread to you. You seem to be much more optimistic than some of your guests.

Dwarkesh Patel

Yeah.

Speaker 2

So why? Is that just a quirk of your personality, or why are you more optimistic than the people you interview?

Dwarkesh Patel

So if you have a p(doom) of 10% or 20%, that is, first of all, unacceptable. The idea that everything you care about, everybody you care about, could in some way be extinguished or disempowered is an incredibly high number. Let's say nuclear weapons is a doom scenario. If you're thinking, “Should I go to war with this country?” and there's a 20% chance that there will be no humans around afterward, you should not take that bet.

But it's harder to express the kinds of improvements which are possible. This will sound very utopian, but we do have peak experiences in our lives. We know that we have people we really care about, and we know how beautiful life can be, how much connection there can be, and how much joy we can get out of learning, curiosity, or other kinds of things.

There can just be many more people—us, digital, whatever—who can experience it. And there’s another way to think about this, because it’s fundamentally impossible to know what the future holds. But one intuition here is: imagine I gave you the choice, “I’ll send you back to the year 1500.”

Tell me the amount of money I would have to give you, but you can only use that money in the year 1500, such that it would be worth it for you to go back to the year 1500. I think it’s quite plausible that the answer is there’s no amount of money I’d rather have in the year 1500 than just be alive right now with my normal standard of living. And I think—I hope—we’ll have a similar relationship with the future.

Speaker 2

Hmm. What is your post-AGI plan? Do you think that you will be podcasting?

Speaker 1

Will you still hang out with us?

Dwarkesh Patel

It’s funny because we have our post-AGI careers already, right? Even after AGI comes, they might automate everybody else in this office, but you and I will just get in front of a camera and—

Speaker 1

There will still be value in having a personality, being able to talk and explain, being somebody that people relate to on a human level.

Dwarkesh Patel

That’s right. I think so.

Speaker 2

I am curious, though, because a thing that I know about you, from our brief interactions and just reading things that have been written about you, is that you believe in learning broadly. You’ve been described as a person who’s been on a quest to learn everything. I think a lot of—

Speaker 1

Sounds exhausting.

Speaker 2

Casey’s on a quest to learn nothing.

Speaker 1

I’m on a quest to learn what I need to learn.

Speaker 2

Just-in-time manufacturing.

Speaker 1

Yes.

Speaker 2

I think a lot of people right now, especially students and younger people, are questioning the value of accumulating knowledge. We all have these pocket oracles now that we can consult on basically anything, and sometimes I think—

I was at a school last week talking with some college students, and one of them basically said they felt like they were a little bit like the taxi drivers in London who still had to memorize all the streets even after Google Maps was invented, and that was sort of obsolete. They felt like they were just doing it for the sake of doing it. I’m curious what, for you, the value of broad knowledge accumulation is in an age of powerful AI.

Dwarkesh Patel

The thing I would say to somebody who is incredibly dismayed is: Why am I going to college? Why is any of this worth it? If you believe AGI or ASI is going to be here in 2 years, that’s fine. I don’t think that’s particularly likely, and even if it is, what are you going to do about it anyway, right? So why—might as well focus on the other worlds.

And in the other worlds, it’s going to happen before we have the fully automated robot that’s automating the entire economy. These models will be able to help you at certain kinds of tasks, but they will fundamentally just give you more leverage on the world. My friend, Asholto Douglas, put it this way: Just imagine you’re going to have 100 times the amount of leverage on the future.

The kinds of things that you will be in a good position to do are if you have a deep understanding of a particular industry and the relevant problems in it. It’s hard to give advice in the abstract like this because I don’t know about these industries, so you’ll have to figure it out. But this is probably the time to be the most ambitious, to have the most agency to actually—

These models currently aren’t really good at actually doing things in the real world or even the digital world. If you can do that and use these as leverage, this is probably the most exciting time to be around.

Speaker 1

Here’s my answer for that. You don’t want to be in a world where you just have to ask ChatGPT everything. Do you know what I mean? There’s a lot of effort involved in just sitting down, writing the prompt, reading the report that comes out of it, internalizing it, synthesizing it, relating it.

You’d be better off actually just getting an education and then checking in with the chatbot for the things the chatbot is good at, at least for the next few years.

Speaker 2

Yeah. I don’t know. I believe that, and I want to believe that the thing I’ve spent my life doing is not going to be obsolete—trying to be smarter and learn things. My guiding principle on this is: Learning is fun.

Dwarkesh Patel

Yes.

Speaker 1

Yes.

Speaker 2

If you can just do it for your own enjoyment, I don’t think learning the streets of London is that fun, but I think learning broadly about the world is fun, and so you should do it if it’s exciting and fun to you.

Speaker 1

Absolutely.

Dwarkesh Patel

No, I think that’s totally correct. Also, if I’m actually talking to a younger version of myself—

Speaker 1

Who would be 6 years old, to be clear. This is a young man we’re talking to today.

Dwarkesh Patel

Hey, little buddy.

Speaker 1

Yeah.

Dwarkesh Patel

Advice on careers in general is so bad, and especially with how much the world is going to be changing, it’s going to get even worse. Who would have told me—what kind of reasonable person would have told me 4 years ago, “Man, this computer science stuff, just stop that. Focus more time on the podcast,” right? So, yeah, it’s going to change a lot.

But then, see, that’s not helpful. What are you going to do with this idea that all advice is wrong? It puts you in an even worse position. Just be a little bit skeptical of advice in general, really trust your own intuition and your own interests. Don’t be delusional about things, obviously.

But, yeah, explore. Try to get a better handle on the world, do more things, and run more experiments rather than just thinking, “This is the thing that’s going to be high-leverage in AI, and that’s what I’m going to do,” based on this first-principles argument.

Speaker 2

Yeah.

Speaker 1

I think “run more experiments” is just really great, underused advice.

Speaker 2

Is that why you built a meth lab in your house?

Speaker 1

Yeah, it’s going great for me. It bought me that hot tub.

Speaker 2

Okay. This is great. Thank you so much, Rakesh.

Speaker 1

Thanks, Rakesh.

Dwarkesh Patel

This was fun. Thanks for having me on, guys.

Speaker 1

Well, Kevin, when we come back, we ask listeners whether they thought AI might be affecting their critical-thinking skills.

Speaker 2

And it’s time to reveal what they all told us.

8. AI And Critical Thinking

Well, Casey, a couple of weeks ago we talked about a study that had come out from researchers at Carnegie Mellon and Microsoft about AI and its effects on critical thinking.

Speaker 1

That’s right, and we wanted to know how our listeners felt about how AI was affecting their critical thinking, and so we asked people to send in their emails and voicemails.

Speaker 2

Yeah, and we got so many responses to this—almost 100 responses from our listeners that reflected the more qualitative side of how people actually feel AI is impacting their ability to think and think deeply.

Speaker 1

Yeah, and look, there may be a bit of a selection effect in here. I think if you think AI is bad and destroying your brain and don’t touch the stuff, you probably are not sending us a voicemail. But at the same time, I do think that these responses show the range of experiences that people are having, and so we should dive in and find out what our listeners are feeling.

Okay, so first up, we’re going to hear from some listeners who felt strongly that AI was not making them dumber or worse at critical thinking, who believe that it is enhancing their ability to engage critically with new material and new subjects. So let’s play one from a perspective that we haven’t really engaged with a lot on this show so far, which is people of the cloth.

Speaker 2

Ooh.

Speaker 8

My name is Nathan Born, and I’m an Episcopal priest.

A big part of my work is putting things in conversation with one another. I'm constantly finding stories, news articles, chapters of books, and little bits of stories that people have shared with me, and interpreting them alongside Scripture.

I've long struggled to find a good system to keep track of all those little bits I've found. Over the last year, I've turned to AI to help. I've used the Readwise app to better store, index, and query pieces that I've saved. I've also used Claude to help me find material that I would never encounter otherwise. These tools have expanded my ability to find and access relevant material that's helped me think more deeply about what I'll preach, and in less time than I used to spend sifting through Google results and the recesses of my own hazy memory.

Speaker 2

Wow, I love this one.

Speaker 1

Yeah.

Speaker 2

This one was particularly fascinating to me because I've spent some time working on religion-related projects. I wrote a book about going to Christian college many years ago, and I spent a lot of time in church services over the years. So much of what the church services that I've been in have done has tried to find a modern spin or a modern take, or some modern insights, on this very old book, the Bible. I can imagine AI being very useful for that.

Speaker 1

Oh, yeah, absolutely. This feels like a case where Nathan is almost setting aside the question of AI and critical thinking and just focusing on ways that AI makes his researching and writing, which he has to do every week, much easier, right? These are just very good, solid uses of the technology as it exists, and they're still leaving plenty of room to bring his own human perspective to the work, which I really appreciate.

And, of course, I always love to hear about a man of the cloth clasping his hands together and saying, “Claude, help me.”

Speaker 2

Right.

Speaker 1

All right, let's hear the next one. This is from a software engineer named Jessica Mock, who told us about how she's taking a restrained approach to asking AI for help with coding.

Speaker 9

When I was being trained, my mentor told me that I should avoid using autocomplete, and he said that was because I needed to train my brain to actually learn the coding. I took that to heart, and I do that now with AI.

I do use Copilot, but I use it for floating theories and asking about things that I don't know. But if it's something that I know how to do, I put it in myself, and then I ask Copilot for a code review. I've found that to be pretty effective.

My favorite use of Copilot, though, is asking, “What does this error mean?” when I'm debugging. I love asking that because you get more context into what's happening, and then I start to understand what's actually going on.

Is it making me dumber? I don't think so. I think it's making me learn a lot. I'm jumping into languages that I was never trained in, and I'm trying things that I normally would have shied away from. So I think it really depends on how you use it.

Speaker 1

So I love this one. If you talk to software engineers about how they solve problems, a lot of what they'll do is just ask a senior software engineer. That creates a lot of roadblocks for people because that senior software engineer might be busy doing something else, or maybe you just feel a little bit shy about asking them 15 questions a day.

What Jessica's describing is a way where she doesn't have to do that anymore. She can just ask the tool, which is infinitely patient and has a really broad range of knowledge. Along the way, she feels like she is leveling up from a more junior developer to a senior one. That's pretty cool.

Speaker 2

Yeah, I like this one. I think it also speaks to something that I have found during my vibe-coding experiments with AI: It does actually make me want to learn how to code.

Speaker 1

Mm-hmm.

Speaker 2

Even though it is probably unnecessary for me to learn how to code to build stuff, and will become increasingly unnecessary, there is this intellectual kick in the pants where it's like, if you just applied yourself for a few weeks, you could probably learn a little bit of Python and start to understand some of what the AI is actually doing here.

Speaker 1

Absolutely. You know what makes me reliably want to finish a video game? It's getting a little bit good at a video game, right? If I'm starting out and I can't figure out how to tie my shoes, I'll throw it away. But that moment where you're like, “Oh, I get this a little bit,” unlocks this whole world of curiosity, and it sounds like AI is maybe giving Jessica that experience.

Jessica's message also highlights something really important, which is that we actually know who the worst writers in the world are: the people who wrote the error messages, right? How many times have you just seen a pop-up that says, “Well, you hit error 642. Try again,” or whatever?

Speaker 2

Right.

Speaker 1

You're like, “Wait, what is error 642?” It turns out all that information was on the internet, and AI has now made that accessible to us and helps us understand. So if nothing else, AI has been good for that.

Speaker 2

Yeah.

Speaker 1

All right, this next one comes to us from a listener named Gary. He's from St. Paul, Minnesota, which is one of the Twin Cities, along with Minneapolis. It points to the importance of considering different learning challenges or disabilities when considering this question of AI's impact on critical thinking. Let's hear Gary.

Speaker 10

I'm a 62-year-old marketing guy who does a lot of writing, and I'm always trying to get new ideas and keep track of random thoughts. I also have ADHD, so I get a ton of ideas, but I also get a ton of distractions, to be honest.

What I've found with AI is that I get to have a thought partner who can help me download all of these different ideas that I've got. If I need to follow a thread, I can follow a thread by asking more questions.

At the end of one of these brainstorming sessions, I can say, “Just recap everything that we came up with. Give it to me in a list.” All of a sudden, my productivity just gets massively improved because I don't have to go back and sort through all of these different notes and all of these different things I've jotted down all over. I can sort through what's real and what isn't real. So it has been super helpful to me in that way.

Speaker 1

Kevin, what do you make of this one?

Speaker 2

Yeah, I like this one because I think that one of the things that AI is really good for is people with not just challenges or disabilities with learning, but different learning styles, right?

Speaker 1

Yeah.

Speaker 2

One of the most impressive early uses of ChatGPT that I remember hearing about was its use in the classroom to tailor a lesson to a visual learner, an auditory learner, or someone who processes information through metaphors and comparisons. It is so good at making something accessible and personalized to the exact way that someone wants to learn something.

Speaker 1

Yeah. I imagine that Gary may be doing this already, but the use cases that he's describing seem like they would be great for somebody who wants to use one of these voice-mode technologies.

Speaker 2

Yes.

Speaker 1

I'm somebody who's most comfortable on a keyboard, but there are so many people who just love to record notes to themselves. There are now a number of AI tools that can help you organize those and turn them into really useful documents.

If you're the sort of person who wants to let your mind wander and talk into your phone for a few minutes, and then give the AI the job of making it all make sense, we have that now. That is kind of crazy and cool.

Speaker 2

Yeah.

Speaker 1

Yeah.

Speaker 2

All right, let's do one more in this camp of people who don't think that AI is making them dumber or worse at critical thinking.

Speaker 11

My name is Anna, and I live in a suburb of Chicago. I wanted to share a recent experience I had with AI and how it made me think harder about solving a problem.

I'm self-employed and don't have the benefit of a team to help me if I get stuck on something. I was using an app called Airtable, which is a database product. I consider myself an advanced user but not an expert. I was trying to set up something relatively complex, couldn't figure it out, and couldn't find an answer in the Airtable forums.

Finally, I asked ChatGPT. I explained what I was trying to do in a lot of detail and asked ChatGPT to tell me how I should configure Airtable to get what I was looking for. ChatGPT gave me step-by-step instructions, but they were incorrect.

I prompted ChatGPT again and said, “Airtable doesn't work that way,” and ChatGPT replied, “You're right. Here are some additional steps you should take.” The resulting instructions were also incorrect, but they were enough to give me an idea, and my idea worked.

In this example, the back-and-forth with ChatGPT was enough to help me stretch the skills I already had into a new use case.

Speaker 2

I love this one because I think what made AI helpful to Anna in this case was not that she used it and it immediately gave her good information. It was that she knew enough about it to know that it was unreliable, and so she did her own deeper dive based on her experience that she wasn't getting good information from the AI.

My worry is that people who aren't Anna, who aren't thinking deeply about these things, will just blindly go with whatever the AI tells them. Then, if it doesn't work, they'll just give up.

I think it really is a credit to her that she kept going and kept figuring out what the real solution to this problem was.

Speaker 1

It is a risk, but let me just say—and this is just a free tip for your life—if you are someone who struggles with using software, I increasingly believe that one of the best uses of chatbots is asking them to explain to you how to use software.

I recently got a PC laptop, and everything is different from what I've been used to for the past 20 years of using a computer. But my PC has a little Copilot button on it, and I press it and say, “How do I connect an Xbox controller to this thing?” It told me in 10 seconds and saved me a lot of Googling. So anyway, Anna, you're onto something here.

Speaker 2

It said, “Get a life.”

Speaker 1

It actually did say that. I was offended. Shame on you, Copilot.

9. The Mental Outsourcing Trap

All right. Now let's hear from some listeners, Kevin, who are more skeptical about the way AI might be affecting their own cognitive abilities or maybe their students' ability to get their work done. For this next one, I want to talk about an email we got from Professor Andrew Fano, who conducted an experiment in a class he teaches for MBA students at Northwestern. Northwestern, of course, is my alma mater. Go Wildcats—and that is why we selected this one.

Andrew sent us a longer story about a class that he was teaching, and the important thing to know about this class is that he had divided the students into 2 groups. One could use computers, which meant also using large language models, and another group of students could not. Then he had them present their findings.

When the computer group presented, he told us that they had much more creative ideas, more outside-the-box ideas, and that those solutions involved listing many of the items that the LLMs had proposed for them. One of the reasons that Andrew thought that was interesting was that many of the ideas they presented were ones that had actually been considered and rejected by the people who were not using the computers because they found those ideas to be too outlandish.

Speaker 2

Hmm.

Speaker 1

The observation that Andrew made about all of this was that the computer-using group saw these AI-generated ideas as something that they could present without them reflecting negatively on themselves, because they weren't their ideas. These were the computer's ideas.

Speaker 2

Right.

Speaker 1

It was like the LLMs were giving them permission to suggest things that might otherwise seem embarrassing or ridiculous. So what do you make of that?

Speaker 2

That's interesting. I usually think of AI as being a flattener of creative ideas because it is just trying to give you the most predictable outputs. But I like this angle where it's actually giving you permission to be a little weird, because you can just say—if someone hates the idea, you can just say, “Oh, that was the AI.”

Speaker 1

Yeah, don't blame me. Blame this corpus of data that was harvested from the internet.

Speaker 2

Which is why I plan, if anyone objects to any segments that we do on the show today or in the future, to blame ChatGPT.

Speaker 1

Yeah, that was ChatGPT's idea.

Speaker 2

Yeah.

Speaker 1

Interesting.

Speaker 2

If it's a good segment, I did it. If not, it was Claude.

All right, let's move to another listener message. This one's from a listener named Katya who's from Switzerland. She told us about how looming deadline pressure caused her to maybe over-defer to AI outputs. She wrote:

“Last semester, I basically did an experiment on this myself. I was working on a thesis during my master's studies and decided to use some help. My choice fell on Cursor,” which is one of these AI coding products. She writes: “Initially, I intended using it for small tasks only, just to be a bit faster, but then the deadline was getting closer, panic was setting in, and I started using it more and more. The speed was intoxicating. I went from checking every line of code to running rounds of automatic bug fixing without understanding what the problems were or what was being done.”

Speaker 1

So I actually think this is the most important email that we've gotten so far because it highlights a dynamic that I think a lot of people are going to start feeling over the next couple of years, which is: “My bosses have woken up to the fact that AI exists. They're gradually raising their expectations for how much I can get done. If I am not using the AI tools that all my coworkers are now using, I will be behind my coworkers and I will be putting my career at risk,” right?

I think we're going to see more and more people do exactly what Katya did here and just use these tools like Cursor. To a certain level, I think that's okay. We've always used productivity tools to make ourselves more productive at work. But there is a moment where you actually just stop understanding what is happening, and that is a recipe for human disempowerment, right?

At that point, you're just barely supervising a machine, and the machine is now doing most of your job. So this is a small story that I think contains a dark warning about what the future might look like.

Speaker 2

Yeah. I think that kind of mental outsourcing does worry me—the autopilot of human cognition. An analogy I've been thinking about recently, in trying to distinguish between tasks that we should outsource to AI and tasks that we probably shouldn't, is forklifting versus weightlifting.

Speaker 1

Okay, tell me about this.

Speaker 2

There are 2 reasons that you might want to lift heavy things. One of them is to get them from point A to point B for some purpose. Maybe you work in a warehouse. Obviously, you should use a forklift for that.

Speaker 1

Yeah.

Speaker 2

Right? There's no salutary benefit to carrying heavy things across a warehouse by yourself, and that's very slow. It's very inefficient, and the point of what you're doing is to try to get the thing from point A to point B. Use a forklift for that.

Weightlifting is about self-improvement. Yes, you could use a machine to lift this heavy object, but it's not going to make you stronger in any way. The point of weightlifting is to improve yourself and your own capabilities.

So I think when you're in a situation where you have the opportunity or the choice of using AI to help you do some task, you should ask yourself whether that task is more like forklifting or more like weightlifting—

Speaker 1

Hmm.

Speaker 2

—and choose accordingly.

Speaker 1

I think it is a really good analogy, and people should draw from that. I want to offer one last thought of my own, Kevin, which is that while I think it is important to continue this conversation of how AI is affecting my critical thinking, in this last anecdote we see this other fear being raised.

What if the issue isn't, “Do I still have my critical thinking skills?” What if the actual question is, “Do I have time to do critical thinking?” Because I think that one effect of these AI systems is that everybody is going to feel like they have less time.

The expectations on them have gone up at work. They're expected to get more done because people know that they have access to these productivity tools. So you might say, “You know what? I actually really want to take some time on this. I don't want to turn to the LLM, and I want to bring my own human perspective to this,” and you're going to see all your coworkers not doing that.

It is just going to drag you into doing less and less of that critical thinking over time. So while I think “Is AI making me dumber?” is a really interesting and funny question that we should keep asking, I think “Am I going to have the time that I need to do critical thinking?” might actually be the more important question.

Speaker 2

Yeah, that's a really good point.

Speaker 1

All right. Well, that's enough critical thinking for this week. I'm going to go be extremely ignorant for the next few days, if that's okay with you, Kevin.

Speaker 2

That's fine by me.

Speaker 1

Hmm.