播客开场白

Joe Weisenthal: 各位 OddLots 听众，大家好。我是 Joe Weisenthal。

Tracy Alloway: 我是 Tracy Alloway。

Joe Weisenthal: Tracy，我们最近去了 South by Southwest。

Tracy Alloway: 是的，没错。虽然在奥斯汀没吃到烧烤，但我们确实吃了一些非常美味的墨西哥食物。我们还录制了一期非常有趣的播客节目。

Joe Weisenthal: 没错，更重要的是，我们录制了一期好节目。

Tracy Alloway: 是的，没错。所以，请各位听众留意。我们做了一期现场播客节目，讨论了 AI 可能导致大规模白领失业的前景，以及政治家应如何思考这个问题，以及选民对此的看法。我们的嘉宾是 Blue Rose Research 的创始人 David Shore，以及撰写精彩 DIFF 简报和 Anomaly Fund 普通合伙人 Burn Hobart。请听。

AI与未来工作

嘉宾: 感谢大家在这个寒冷的周日上午前来。

Joe Weisenthal: 大家好，欢迎收听 OddLots 播客的现场录制。这绝对将是本周末所有对话中最令人振奋的一场，对吧？

David Shore: 我想是的。我认为它真的会是。

Joe Weisenthal: 这里的每个人都会感到非常满意。

David Shore: 对未来。

Joe Weisenthal: 好的，我们开始吧。我们有两位出色的嘉宾。我们将与 David Shore 对话。他是 Blue Rose Research 政治咨询公司的创始人、民意测验专家，对 AI 有很深的了解。我们还有 Burn Hobart，DIFF 简报的创始人，这是一份大家都应该阅读的优秀简报，他还是 Anomaly Funds 的普通合伙人。我们将讨论所有关于 AI、潜在失业以及其政治影响等话题。David 和 Burn，非常感谢你们今天来到现场。

David Shore: 很高兴来到这里。谢谢。

Joe Weisenthal: 那么，我们来谈谈这个问题。David，你认为现在正在发生。经济可能在一年、18个月后就会发生根本性的变化，你正在努力唤醒政治家。这正在发生。但是，请告诉我们现在正在发生什么，或者即将发生什么。

David Shore: 是的，我不是 AI 专家，我也不想声称自己是。但我想说的是，我大量使用 AI。我大量使用 cloud code。我认为在去年 12 月，我将大约 15% 的税前收入花在了 cloud code 的超额费用上。我认为我周围的朋友之间存在着一种真正的脱节，那些使用 cla code 的人和不使用的人之间。我能真切地感受到，与一个月前和更早的一个月前相比，我现在能做的事情更多了。这些东西改进的规模和速度确实令人震惊。而且我认为，如果你只是使用 ChatGPT，你可能不会注意到这一点。就像 ChatGPT 似乎比一年前好了一点。

Joe Weisenthal: 但话又说回来，对未来做出预测是非常困难的。但我确实认为，如果事情继续以这种规模改进，那么情况可能会非常迅速地变得非常奇怪。

Tracy Alloway: Burn，我们之所以想和你谈谈，原因之一是你处于技术和金融的交汇点。如果我现在看看大型科技公司和一些 AI 公司的估值，它们基本上表明它们将接管整个经济。当你看到这些数字时，它们对你来说预示着劳动的未来会是怎样？

Burn Hobart: 所以，我认为现在确实如此，你可以将这看作一个连贯的类别，这是一个 AI 公司，或者这是一个非 AI 公司，但他们正在整合 AI，并且他们拥有这些分销优势，所以他们可能会做得很好。但我认为，如果认为这是一个持久的独立类别，就像你可以将许多公司称为电力公司一样，那是一个错误。如果是在 1925 年，你试图弄清楚要买哪些股票，并且你对电力非常看好，那么你就会非常关心 RCA 是否与电力相关，而 US Steel 则大多不相关。但最终，每个公司都成为电力公司，从某种意义上说，如果灯不亮，你就会经营一个非常不同的业务。所以它就像被经济的其他部分所吞噬。你也可以在软件领域看到这一点，有更多的公司拥有软件开发人员并为内部使用编写软件。它们本身并不是软件公司。它们可能是餐馆或拖拉机公司或其他什么，但它们具有这种元素。所以，我认为这只是任何通用技术推出初期所看到的。你有很多非常狭隘的特定赌注，然后随着时间的推移，影响变得如此广泛分布，以至于很难追溯，你必须回过头来审视历史，审视汽车的兴起导致郊区的兴起，但也导致杂货店的兴起，或者说是超市的兴起，你可以有更多的选择，这意味着每售出单位的劳动力成本更低，这意味着总成本更低，如果人们不是步行去买杂货，那就可以奏效。如果人们是步行，而且每天下班回家的路上都会停留，那就不行。所以，我们可能会看到很多这种奇怪的结果。我想，如果你考虑某个职业的风险，我认为对于大多数人们担心的职业，平均薪酬会上升，而目前在该行业的人的平均薪酬可能会下降，很多人会被淘汰。但这以前也发生过。就像电子表格并没有淘汰投资银行家或会计师这份工作。它实际上使这份工作更有利可图。但它也使这份工作更容易衡量，你不能像以前那样在某些白领职业中有所懈怠。只是容易得多。对产出的期望如此之高。

Joe Weisenthal: 我整天都在 Twitter 上，很多人都在发推文，我觉得很多人现在都在偷懒。我心想，你们怎么有时间的？我有时间，因为我是一名记者，我专业地创作文字。

Tracy Alloway: 有人可能会说，你实际上没有时间整天发推文。

Joe Weisenthal: 没错。但是。

Tracy Alloway: David，那么，AI 已经取得了很大的进展，毫无疑问。有新的 AI 模型工具可以增强我们的能力。这与我们都知道的情况不同。这与大规模的失业潮不同。在你看来，为什么你认为 AI 的进展是如此迫在眉睫，以至于我们必须讨论它可能重塑白领劳动力？

David Shore: 我经常想到的类比是 CO，因为 AI 的进步在很多方面都是指数级的。在过去的 6 年里，AI 在没有人为干预的情况下自主运行的时间每 112 天或 12 天就会翻一番。当我想起 CO 时，那是没有人预料到的事情。然后它发生得非常快。然后我认为政治体系非常被动。而且我认为，私下里，很多民主党人希望他们能以不同的方式处理事情。但很酷的是，与 CO 不同，我们真的可以看到 AI 的到来。所有的警示信号都在闪烁。我想在这里提出的另一点是，我个人认为大规模失业的可能性很大，特别是白领，但卡车司机和 Uber 司机也很多。各种各样的人都可能失业，而且这一切都可能发生得非常快。但我认为更重要的一点是，美国人民看到了这一点，并且非常担忧。当你问人们，在未来 5 年内，AI 导致大规模失业的可能性有多大？70% 的人表示非常可能或有点可能。所以，我认为这是我在这里提出的主要观点，即政治家现在就应该采取行动，而不是等到问题出现才采取行动，原因有二：一是美国人民已经对此感到担忧；二是当它已经发生时，我们的政治体系将为时已晚，无法应对。所以，我认为提前行动很重要。

新技术对劳动力市场的影响

Joe Weisenthal: 我肯定想更深入地了解政治，但 Burn，你提到了一个似乎是这些对话中的标准观点，那就是我们以前也遇到过这种情况。我们都，好吧，不是真正经历了工业革命，但那是发生过的事情，我们经历了互联网繁荣，经济和社会或多或少都适应了。但当你现在问人们白领工人的替代职业是什么时，我们无法真正提供一系列可能性。我知道很难想象未来，但如果你是一名保险经纪人，你已经做了 20 年，在新经济中你会做什么？新工作是什么？

Burn Hobart: 是的，这确实是个难题。比如其中一个只是暂时的，我认为有很多工作基本上是出于监管原因需要人工干预的，比如医生是 AI 工具的快速采用者，而医生的供给是人为受限的。所以，如果你减少他们花在行政任务上的时间，减少他们犯错误的概率，你基本上就相当于制造了更多的医生。在医疗保健这样的领域，需求实际上是无限的。因为还没有哪个经济体，人们不会将更多的边际收入花在健康上。

Tracy Alloway: 所以，我们都将成为医疗工作者。

Burn Hobart: 我认为这实际上是，医疗领域可能会增长。说某些白领工人地位会下降，他们可能会从事听起来不那么酷的工作，这有点令人沮丧。但是，如果总体产出足够高，如果资本回报率足够高，人们就会喜欢，经济开始将更多的增量生产转移到仅仅建设数据中心。这意味着，如果你是数据中心的补充，你就是整个供应链中不可或缺的一部分，那么你的议价能力就会强很多，因为你所处的资本环境更多。如果你完全可以被数据中心取代，那么你就处于困境。我们总是发现模型具有这些非常突出的能力。例如，它们在某些方面是超人的，而在其他方面则不然，比如在数学能力方面。它们已经超越了我可以可靠地区分两个模型并说“这个数学真的很好，这个数学还可以”的程度。

Burn Hobart: 但在其他领域，它们表现平平，因为它们没有一个全面的世界模型。原因在于它们是在文本上训练的，而文本实际上偏向于不确定和有争议的领域。所以我用“可能球体”这个词来形容，就像你想象有一块事实的基岩，它太明显了，没有人会费心去写下来。然后有无限多的问题，它们太奇怪了，几乎肯定没有答案。就像有一个狭窄的层，像大气层一样，在那里提问是值得的，你可能会得到答案。所以它们对于我们不确定或已在教科书中编纂的世界部分有一个非常好的世界模型，而对于许多显而易见的事情却有一个非常糟糕的世界模型。所以，如果我的工作是向这个超人智能说些极其显而易见的事情，那会有点奇怪。我甚至不知道历史上什么工作头衔可能与此对应，比如一个仆人为一个聪明但又心不在焉的教授服务。但我认为未来会有更多这种“为心不在焉的教授服务的男仆”职业。为心不在焉的教授服务的男仆，听起来不错。

Tracy Alloway: David，你有一家公司，你雇佣员工。你的招聘性质是否发生了变化？考虑到技术的变化，你现在招聘的职位类型是否与几年前不同？

David Shore: 绝对是。我想举一个简单的例子，我们过去有很多文字编辑来撰写民意调查问题或信息，但现实是，现在 AI 在这方面通常比人类做得更好。并非完全如此，但我们有很多。

Joe Weisenthal: 它们擅长撰写民意调查吗？比如 AI 能不能找到有趣的民意调查问题，而不是那些显而易见的问题，这样你就能从中获得真实的信号？

David Shore: 嗯，我不想谈得太具体，但我可以说有大量的文字编辑任务。坦率地说，我认为。

Joe Weisenthal: 你为什么不想谈得太具体呢？这意味着这是我应该问的问题。

David Shore: 不，不，不。但是你看，有很多像翻译这样的事情，有很多像文字编辑这样的事情。我认为我们最大的转变是，我们更注重以人为本的工作，而且现在你可以做更多的工程工作。所以我认为在我们的招聘方式上，肯定发生了很大的工作转变。绝对是。

AI在内容创作中的应用

Tracy Alloway: 也许我们可以在这里稍微进行一些内容创作的内省，因为我想这可能也引起了 South by Southwest 很多人的兴趣。但是 Burn，你每天都会写一份简报。Joe 和我也一样。你如何在日常工作中利用 AI？

Burn Hobart: 我在研究方面大量使用它，其中一个具体的用例是问这样的问题：这个笑话能奏效吗？或者，我正在发表一个关于我相当熟悉但并非专家的领域的技术性陈述。你是这方面的专家。告诉我我哪里错了。原因之一是我的很多读者都是软件工程师，而且他们。

Joe Weisenthal: 急切地想告诉你你错了。

Burn Hobart: 是的。非常急切。我有点根据人们作为软件工程师的能力来衡量他们，特别是根据我收到他们发来的电子邮件指出打字错误的速度。因为真正优秀的工程师，他们的一项技能就是查看大量文本并立即发现错误。现在这项技能有点过时了。LLM 在这方面做得更好，但“我要查看这些东西并吸收一些连贯的内容，然后寻找其中任何小问题”的心态仍然非常有价值。事实上，由于代码的生产量比以往任何时候都多得多，能够流利地阅读并理解它应该做什么，这真的非常有价值。所以，我大量使用 AI 进行研究。直到最近几个月，我才真正从 ChatGPT 那里获得了写作的灵感，或者说直到最近几个月，它才提出了一些我从未想到的原创观点，这些观点是巧妙的见解，而不仅仅是它背诵了一个我碰巧不知道的事实。David，再多告诉我们一些。那么，这个关于进步的问题，对吧？我们都知道它正在变得更好。这很明显，但更有趣的问题是，它的进步速度是否比人们之前预期的要快？

Burn Hobart: 谈谈我们现在的技术水平，以及你所交谈的人会说我们在什么时候，现在是三月吗？2025 年三月。

David Shore: 是的。我认为过去一年最大的惊喜是 Vibe Coding 的兴起，以及像 cloud code 这样的工具的兴起。如果你回到一年前，我认为没有人真正预料到这些东西能够进行大规模、复杂、自主的编码问题。我认为在很多方面，这些模型变得有用比它们变得更智能要快。而且我认为这并不是人们所期望的。嗯，有趣的是，每年都会有一群 AI 专家会做出预测。其中最大的惊喜之一是这些公司的收入增长，我认为这在很多方面是最重要的基准。我认为 Anthropic 去年的收入大约是专家们预测的两倍，而他们我已经认为是非常 AI 支持者了。所以，我认为这可能是最大的惊喜。我想说的更广泛的转变是，像 LLMs 这样的工具现在被更快地采用。有很多图表，比如收音机、电力或互联网的实施花了多长时间。而 AI 的速度比所有这些都要快得多。所以，我真的很担心，当我们谈论过去的转变，比如电话交换机接线员或工厂工人，所有这些事情都发生在很长一段时间内，并且只影响了经济的某些部门。而这项技术真的有可能同时颠覆每一个工作岗位。在人们对经济的总体看法不佳的时候。所以我真的很担心，从政治角度看，我们的政治体系能应对到什么程度。

Joe Weisenthal: 确实，当你审视技术普及程度的这些衡量标准时，我认为真正难以衡量的是，它在什么时候成为你基线期望的一部分，以及在什么时候其影响是如此明显以至于无需言明。所以如果你看看电气化，我认为任何谈论 AI 的人都必须说，从第一家电气化工厂到大多数美国工厂电气化，花了大约半个世纪。但原因在于，对此有很多有趣的经济史，你必须以不同的方式运营你的工厂。你实际上必须建造一种不同类型的建筑，而且你还必须以不同的方式融资，或者说你可以以不同的方式融资。所以，如果你的工厂有某种机械动力来源，你倾向于以这些离散的工厂规模增量来扩展你的业务。这意味着你的投资者，你将大部分收益作为股息支付出去，因为留存收益无事可做。这就像如果你要增长，你想要发行大量股票，发行大量债券，然后一次性增长。但是一旦你有了电气化工厂，它们可以扩展，它们可以简单地增加一条装配线，或者它们可以将这台机器升级到一台更新的机器等等，它们实际上可以更有机、更增量地扩展。这就是当你开始看到股息支付率下降的时候，也是当你开始看到“增长型公司”这个概念出现的时候。如果你阅读 1920 年代的投资者报告，他们在谈论股市时，其中一个奇怪的事情是，他们非常关注股票是高于还是低于每股 100 美元，因为那是面值，那是股票的标准价值，它应该就是账面价值等等。然后人们有点将股权视为最次级的索赔人，就像你将一家公司的股权视为一个切片之类的东西，而现在我们完全不同地看待股权，所以我们完全不同地部署资金。对于 1926 年左右的投资者来说，说我要投资一家没有运营的公司，它只有人，然后我要把实际的钱投入这个业务，但大部分将由这些人拥有，然后这个业务，我的股票在几年内可能价值增加 50 倍，如果一切顺利的话，那对他们来说是不可理解的。股票从面值上涨到面值 50 倍的想法简直是疯了。所以我们，但这种变化实际上是，我认为它具有因果关系，而且是双向的，美国拥有一套非常灵活的金融体系。我们还拥有一个相对于所有其他国家都非常灵活的劳动力市场，这意味着我们将成为所有失业问题的零号病人，它会先于其他人打击我们，并且会比其他人打击我们更严重。另一方面，这种特殊通用技术推出独特的方面之一是，它的发生速度比以前快得多。但稍微抵消这一点的是，这项特定技术实际上让你能够获取信息和认知，这样你就可以问 ChatGPT，比如这是我的工作，我从事保险销售 20 年了。我应该如何再培训？我该怎么做？它会问后续问题。它会问，好吧，你和你的同事面临的其他问题是什么？或者，让我们分解一下你拥有的技能。是什么让你成为一个特别优秀或糟糕的保险销售员？然后你还可以从事哪些受 AI 影响较小的工作？或者，随着模型变得越来越智能，你可以告诉它，嘿，我希望你为我发明一份新工作，一份我天生就适合的定制工作。

Tracy Alloway: 不，你已经有那份工作了。

Joe Weisenthal: 没错。

Tracy Alloway: 播客主持人是安全的。我想我们可以提问。但我的意思是，当好处是你可以问 ChatGPT 你的替代工作是什么时，这确实有点反乌托邦。

Burn Hobart: 但这些东西在当时总是感觉反乌托邦。如果你在 200 年前告诉某人，嘿，你继承你父亲的农场并在那个农场工作，然后把那个农场传给你的儿子，这将是完全不可行的。如果你说，这不仅在经济上不可行，而且你也不会如此专注于是你的儿子还是你的女儿，而且你可能会搬到一个城市，你会被完全陌生的人包围，你会有一份在一个吵闹、嘈杂、非常不舒服的建筑里工作，摆弄着这些你正在制造的物理东西。很多人会说那简直是噩梦。事实上，很多当时的观察者都谈到那是一种噩梦，但最终随着时间的推移，它运作得相当好。它只是新的、奇怪的，从最初的角度来看是完全不可理解的。

效率收益的分配与挑战

Joe Weisenthal: 让我换一种方式提问，那就是，谁在这里获得了生产力收益，以及它们是如何分配的？因为我可以想象这样一种情况：我们都有工作。我们的工作中有些任务是我们不喜欢做的，如果我们可以使用 AI 更高效地完成这些任务，那么这可能对我们很有好处。但历史上充满了新技术的例子，这些技术被宣传为生产力增强器，比如电子邮件会让你更快地完成工作，但结果却是电子邮件意味着我们必须全天 24 小时回复电子邮件，我们只是得到了更多的邮件，这实际上让我们更痛苦。谁在这里获得了效率收益？

Burn Hobart: 那些在能够产生更多经济产出时不会感到痛苦，但必须以不同方式付出关注或投入更多努力的人。不，这些东西确实有负面副作用，但当沟通成本下降时，你可以进行的协调量就会大幅增加，并且你可以以不同方式进行协调。我认为这也说明了预测服务业工作的需求是非常困难的，因为它很多都是如此元化，比如很多都是与其他服务业部分互动。所以像 Excel 是一个正确的例子，但也有文字处理，你可以认为，文字处理让律师更容易快速起草合同，所以我们需要更少的律师。但实际上，这意味着他们可以将两页的合同变成 50 页的合同，然后你需要更多的律师来处理。Joe，我有没有告诉你我在康涅狄格州遇到一个人，他正在接受文字编辑培训？他两年前开始的，我当时只是想，天哪，时机太糟糕了。

Joe Weisenthal: 我听过一些其他故事，比如我最近听说有人在大约六个月前参加了一个编码训练营，我觉得时机真尴尬。

Tracy Alloway: David，在你的民意调查中，谁最喜欢 AI，谁最不喜欢 AI？

David Shore: 是的，有一个非常明确的联盟。实际的水平很大程度上取决于你如何提问，但主要的人口结构差异是年轻人比老年人更喜欢 AI，男性比女性更喜欢 AI，这可能不足为奇。然后我认为有趣的是，总的来说，受过教育的人对 AI 的看法要积极得多，他们讽刺的是，尽管谈论白领失业，但拥有学位的人，我认为他们是最乐观的，而工薪阶层的人则不那么乐观。最后，总的来说，非白人对 AI 更悲观，而黑人和拉丁裔选民则普遍更乐观。例如，密西西比河三角洲实际上是那些对 AI 感到兴奋的人比例最高的地区。

Tracy Alloway: 这很有趣。等等，解释一下受过教育的人和更像工薪阶层的人之间的态度差异。这仅仅是因为工薪阶层，我想，也许历史上更习惯于被坑，说句不好听的话？

David Shore: 我认为这正是如此。你看，那种“工作会改变，但会有大量的增长，会有新的工作”的故事，我认为非常值得一说的是，选民对这种说法极其怀疑。如果你去问，“你对 AI 会创造大量新工作的说法有多信任？”我认为大概是负 40。现实是，选民现在对经济极其负面。真的很难夸大其词，大约三分之二的公众认为经济被操纵了。只有 35% 的公众认为自己财务安全。在这种背景下，人们感到非常愤怒，他们对“事情会好起来”的说法极其怀疑。而且很明显，工薪阶层的人记得制造业的衰落。他们喜欢基本上每一次重大的经济转型都有赢家和输家，赢家通常是前 1% 或前 10%。经济学家对此争论不休，但其他人则遭受了损失。所以，我想说的主要观点是，我认为 Burn 所描绘的图景不会被允许发生，因为公众有发言权。这是一个非常重要的问题。公众会，如果不了解政治将会如何，几乎不可能谈论未来。让我问你，你与民主党人合作，当我想起民主党人和 AI 时，我认为有几件不同的事情。在“L”大写左翼阵营中，有相当大一部分人认为这都是骗局，认为这就像是 Theranos 再现，就像 NFT，这在经济上是不可持续的。然后有点像反数据中心的人。他们不希望数据中心出现在他们后院。他们根本不希望数据中心存在。然后有点像民主党内部一直在发展的东西。就像反大科技公司和反寡头等等。有没有你与之交谈的人，他们最，我正在努力思考确切的词语，认真对待它，认为它是一项将要发展的重要技术？有没有你与之交谈的人说，不，这实际上是有效的，这是真实的，这可能带来生产力收益等等，或者几乎只是各种政治负面情绪？

David Shore: 嗯，我认为背景是这是一个非常新的政治问题。甚至自去年以来，关心 AI 的选民比例比我们跟踪的其他 39 个问题中的任何一个都增长得更多。所以政治家显然正在迎头赶上。通常政治家都是相当被动的。但是，我想说的是，我认为民主党人比共和党人更有能力利用这一点，原因很简单，共和党人在这方面把自己逼到了绝境。Donald Trump 在录音中说 AI 将创造大量新工作，失业不会发生。JD Vance 发表演讲说：“哦，我们永远不会监管 AI。”所以我想，从我的对话来看，我看到民主党政治家比六个月前更关心这个问题。而且我认为人们正在努力弄清楚正确的应对方式是什么。等等，多说说你为什么认为 AI 会如此迅速地成为一个关注点，因为我知道，这个房间里的每个人可能都玩过 ChatGPT 之类的东西，但我想对于大部分人口来说，它还没有真正影响到他们的日常生活。所以，看到 AI 担忧如此迅速地爬上担忧榜，这有点令人惊讶。

David Shore: 嗯，我认为人们确实看到了未来的迹象。基本上，目前大约 60% 的公众使用过这些工具，13% 的公众每天使用它们，我认为人们真的低估了公众的担忧程度，或者说，我认为这些工具确实正在广泛地应用于各个不同的行业。上周末我与一位医疗技术人员交谈，他告诉我，“哦，是的，AI 正在部署。”她在一个蒙大拿州的农村医院工作，即使在那里，她也说，“哦，是的，AI 正在广泛部署。”我认为，这又是在选民对经济感到极其负面的背景下发生的。所以，每当他们看到大规模革命的前景以及他们的所有工作将如何发生变化时，我认为他们非常担心自己会倒霉。Burn，我想你和对立面的人有联系。是的。而且在那里也有一些有趣的裂痕，因为显然我们有那种非常热衷于进步和加速等的科技右翼。然后你有一些显而易见的民粹主义联盟。政治家们谈论如果有了自动驾驶卡车那会多么糟糕，那对司机来说会多么可怕。你如何看待另一边正在移动的构造板块？

Burn Hobart: 嗯，我喜欢 AI，所以我在政治维度上非常悲观。我认为部分原因在于，当你向人们提出 AI 问题时，当你使其突出时，他们会持一种观点。但如果你看他们的行为，他们会持另一种观点。我认为这是一个更广泛的观点，即大规模部署技术会增加衡量到的收入和财富不平等，但会减少消费不平等。所以像坐飞机这样的事情就变得更容易负担得起。最近有一些数据表明 DoorDash 的使用在低收入人群中最为频繁。所以你只是能够获得很多东西，而以前要么没有人拥有它，要么只有非常富有的人拥有它。实际上，CHTBT 就是这样一种东西，如果它不存在，而且我更富有，我就会雇人做这类事情。我只会问他们一些关于历史的奇怪问题，或者让他们去做一些小小的研究任务，而且如果他们一周后回来向我提交这份报告，我说：“哦，我实际上改变主意了。我不再关心那个了。但我现在要下一个任务。”我一点也不会感到不好意思。但你可以在 LLM 上做这件事。但老年人群名义上不喜欢 AI，但他们在 Facebook 上花了很多时间，这意味着他们实际上非常喜欢 AI。他们喜欢 AI 推荐引擎。他们非常容忍 AI 推荐的广告。他们喜欢 AI 生成的图像和 AI 生成的文本。他们在 AI 会告诉他们评论应该说什么而他们不必自己想出评论的网站上感到更自在。人们实际上从消费角度喜欢 AI，但从外部抽象角度讨厌它。所以让我更乐观的是，这些不同问题的突出程度会随着时间的推移而波动。也许 AI 的部署速度如此之快，以至于它变成了背景噪音，就像内燃机或电力，甚至是互联网一样。现在互联网不是一个竞选议题。它在 2000 年曾是一个议题，我想在 2016 年和 2020 年也存在一些互联网问题，但它的突出程度越来越低。我们不再考虑你是支持还是反对它，它只是存在。我认为，随着 AI 带来的许多无形的生产力收益，或者说不那么突出的生产力收益，我们处于一个更好的世界，人们不会认为 AI 只是作弊和剽窃，比如可否认的剽窃机器，再加上夺走我最好潜在工作的东西。

Joe Weisenthal: 你们有没有最喜欢的历史类比，可以用来理解现在 AI 的政治或社会视角？

David Shore: 你知道，对我来说，正如我之前所说，我认为它是 CO，我认为这会很快发生。人们痴迷于它何时发生，或者如何发生。但我认为选民讨厌改变。我认为这是政治中最被低估的现状偏见之一，这种偏见非常强烈。如果你看看这个国家最受欢迎的政治家是谁，总是一些什么都不做的州长。你知道，这是一个被低估的政治事实。所以我认为，如果你谈论一个所有工作都在同时转型，有大量赢家和输家的世界，人们显然会纠结于 AI 是否会让人人都失业这个问题，但如果 3% 的人因为 AI 而失业，那就会成为世界上最大的问题。你知道，每当收益分散而损失集中时，那就像是公共选择理论中的混乱秘方。所以，我真的很喜欢 CO 的类比，因为 CO 基本上是一次性发生的，然后我们的政治体系被打乱了，新的联盟形成了，很难做出回应。每当你回溯过去，正如我们之前谈到的，很难想到一个经济转型发生得如此之快。

Joe Weisenthal: Burn

Burn Hobart: 是的，我认为 CO 的类比可能以另一种方式揭示了一些东西，那就是联盟完全多次转变。就像在一月份，只有那些奇怪的、极度在线的右翼匿名人士和少数理性主义者说这是一件大事，我们需要关闭往返中国的航班，对于 EA 类型的人，对于理性主义者类型的人来说，这更像是一种对潜在生存威胁的审慎回应。然后我认为对于许多极右翼人士来说，这是一种让中国难堪的方式，也是为了减少往返中国的航班，因此我们希望这样做。然后，我认为 Trump 非常依附于 S&P 告诉他这是好事还是坏事。你可以看到，我想如果他有一个实时行情显示器告诉他市场对他的早期 COVID 演讲的反应，我们就会有一个完全不同的 CO 政策。然后我们有点翻转了，现在右翼变得更像 CO 自由主义者，你知道，就是任其发展。你知道，我们都会在某个时候对这种病毒免疫。这对我来说真的很奇怪，因为右翼的年龄偏大，而老年人更容易受到风险。

政治与公共议题

Burn Hobart: 但我想这又回到了显着性和信息环境。如果你处于你久坐不动、年迈且久坐不动的群体中，因为你花了很多时间看电视。如果你在电视上看的是 Fox，那么你可能会对世界有一个非常不同的看法。所以我认为联盟可能会波动很大。我认为实际上没有任何，我认为两个主要政党都不是“增长派”的良好归宿，他们可以是民主党中的少数，也可以是共和党中的少数，并且必须在某种程度上妥协才能拥有任何影响力。所以从这个意义上说，再次非常悲观。但当你谈到显着性变化的议题时，我认为在你拥有的数据中，就像一年前是贸易，每个人都痴迷于贸易，然后贸易成为一件大事，并且一度成为头条新闻的主要制造者，然后它就有点淡出了。所以，即使像现在全球贸易的状况仍然非常混乱。事实上，就石油贸易而言，它比几周前更混乱。没错。所以，从这个意义上说，贸易就像日常的“你比一周前过得更好吗”这个问题，贸易仍然是最显着的问题。我的意思是，也许如果有新的模型发布，那会改变一些事情，但就目前而言就是这样。所以，是的，这都是非常不稳定的。我认为与此最密切相关的技术是晶体管和集成电路，它们可能是最接近的映射，从字面上讲，它们是一种让你生活中所有东西都变得更智能一点的方式。而想到我们家里有多少小小的白痴天才设备可以进行小计算和运算，并且拥有一个漂亮的界面，以及这些东西变得如此便宜以至于基本上免费，这简直令人震惊。就像，想到我们能否建造一个完全由机械控制的微波炉，里面没有晶体管，那将毫无意义。为什么要这样做？说到政治，David，你认为这可能吗？比如说，总统支持，未来的总统支持，有人提出一项法案说，“我们要禁止 AI，禁止新的 AI 数据中心建设。”你认为有可能通过这样的法案吗？因为我觉得这听起来很疯狂，但我也越想越觉得。

Joe Weisenthal: 这似乎有可能通过。

David Shore: 是的，我可以看到各种事情都可能发生。我们可能会有一个分裂的政府，所以在这种情况下，押注任何特定事情的发生都是不明智的。但就像我们一样，禁止投资者拥有房屋非常受欢迎，两党似乎都非常支持公司不应该拥有大量单户住宅的观点，这似乎完全跨越了两党。反数据中心的事情在我看来也类似，它似乎不是一个左派或右派的事情。它似乎是一个非常广泛的民粹主义、TikTok 政治的事情。

David Shore: 是的，我想说的是关于数据中心的民意调查，如果你调查“你想要你家附近有一个数据中心吗？”人们会说不。但另一方面是，如果你添加任何东西，比如“如果它由清洁能源建造，或者如果它能降低你的税单 10% 呢？”那么它就会变得非常受欢迎。我看到很多政治家似乎都抓住了数据中心这个问题，因为这只是一个巨大的可怕问题，而数据中心的东西只是一个非常清晰的土地利用问题，我认为那将是一个错误。不是因为我个人非常关心我们是否禁止数据中心，而仅仅是因为我认为公众真正想要的是其他东西。比如如果我们明天禁止数据中心，那并不能改变选民认为经济被操纵了，或者他们非常害怕未来的事实。而且你知道，在我们的测试中，我们通常测试了几十种谈论 AI 的不同方式。而且你知道，数据中心的事情我认为并没有真正打动公众。而我认为真正打动公众的是，更激进地谈论工作保障或收入保障，或驱逐保护。我认为存在巨大的恐惧，政治体系应该努力解决它，而且不仅仅是应该，我认为它会，你知道，因为我们生活在一个民主国家。

AI与监管：电力、责任与经济模式

Tracy Alloway: 实际上，Burn，这让我想起，我们经常听到关于 AI 的一件事是电力作为限制因素。每个人都说那是最大的限制。当你自己考虑技术的采用及其在美国乃至全球的传播时，你对数据中心和电力消耗的考虑有多少？

Burn Hobart: 嗯，我现在较少考虑这些，因为供应链中的每个人都已预订了很远的未来产能，而且新供应的弹性很小。我不会完全惊讶地看到 AI 公司只是保证他们会在 2032 年或以后从 Seamus Energy 或 G 公司接收货物，这样他们就可以开始新的制造产能。但我认为，由于这是一个滞后很长的过程，它在某种程度上是既定的。我认为实际的限制更多地在于内部组织方面，你是否真的有一个组织结构图，如果你到处都有 AI，它总是将信息路由给需要它的人。比如你是否可以只有一个人是 CEO，而其他所有人都是个体贡献者，并且你 AI 化了所有中层管理？可能不会，因为你，另一个限制因素是责任。你确实希望有人类在循环中。你知道，我之前开玩笑说过，但这是真的，现在处于理想位置的人是那些从事受监管工作的人，那里有某种行业协会限制新进入者进入该工作，但对他们提供的服务有过剩的需求，并且 AI 可以提高他们的每小时产出。这些人将赚大钱，而且只要他们能限制供应流入，他们就会继续这样做。所以我们最终可能会得到一个更像行会化的经济，我们对谁有权力做一些事情进行了限制，不是谁可以做这份工作，而是谁可以真正地盖章说我对此负责，如果出了问题你可以起诉我，因为这实际上是非常有价值的事情，而且你仍然不能真正起诉一个数据中心。你可以尝试起诉 OpenAI，但他们可能请得起比你更好的律师。你实际上，起诉我因为 ChatGPT 告诉我做了一些我没有通过询问 cla code 再次检查的事情，这在经济上可能更有效。所以我们会觉得，想到我们作为有血有肉的人类，我们的经济目的之一是成为一个容易被起诉的目标，这很奇怪，但它实际上是我们能做的一些经济上有价值的事情，而且因为我们都有不同的风险偏好和风险承受能力。这实际上意味着我们会看到 AI 的部署不均衡，会有人只是证明你可以走得太远，而且如果你决定成为一个为上千人报税的 CPA，你很可能是第一个专门因为 LLM 告诉你做的事情而入狱的 CPA，如果还没有发生的话。但我认为，这种模型，你希望有人类在循环中，因为我们经济和社会中的许多结构都假定有一个人，这可能还会继续存在。

Tracy Alloway: 你写了很多关于金融和技术的内容，我一直在思考 AI 在金融领域的未来。其中一个问题是，我们和 PNC Bank 的 CEO 做了一期非常棒的节目。我们当时谈论了一些关于 AI 和贷款的事情，他说如果你拒绝给某人贷款，你必须有理由。有一些法律，比如反歧视法之类的。所以如果某人被拒绝信用，你必须能够解释原因。AI 的一个特点是它可以做出非常好的决策，但很难解释，而且 AI 通常无法解释它是如何得出结论的。我很好奇，从金融行业来看，你认为这将在多大程度上限制 AI 颠覆这个行业？很多事情都需要用英语来表达，基本上。

Burn Hobart: 嗯，我认为 AI 像人类一样，不善于知道它为什么会做某事，但非常善于解释它所做的一切都是正确的。所以它可能，我的意思是，我不是 PNC 的负责人，所以我不确定，但我想象它实际上让找出一些非常可靠的合理化理由变得更容易。它们非常擅长合理化。所以我对此不会那么担心。我实际上认为拥有更开放、更容易理解的推理方式很好，你可以实际阅读推理痕迹。我认为它对金融业的影响之一是，那些提出建议的人，比如发放这笔贷款，不发放那笔贷款。拥有更多详细的完整思考过程记录会很有意义。所以你可能会让他们在 DataBricks Notebooks 或类似的东西中工作。这样你就可以看到，他们首先提出了这个问题，然后他们深入研究了这个难题，然后他们决定这不相关，然后他们又转向了这个问题，然后他们花了一些时间研究它，等等。因为如果你只有问题和某人想出并编辑过的完善答案，你就会错过很多中间层，所以很难训练一个能够追踪并重现这种过程的模型。现在，如果你有一个足够智能的模型，它基本上会隐式地重现所有这些推理。但这确实意味着当推理非常巧妙而那个人没有展示他们的工作时，它会做得更差。而很多聪明的人只是想出了事情，然后他们就已经对这个问题感到厌倦了。所以他们不想告诉你他们是怎么做的，然后他们转向下一件事。

Joe Weisenthal: 我最近确实有一个家庭 DIY 项目，我问 ChatGPT 怎么做，它基本上让我去反抗重力。

Burn Hobart: 而且无法解释它为什么要这么做。我稍后会告诉你更多，因为它是一个很长的故事。总之，如果我们能稍微进行一些政治民意调查的内省，David，当我想到 AI 和你所做的一些工作时，我认为它对你非常有帮助，因为你可以为民众识别出更细致的问题。你可以提出更好的民意调查问题，但我认为所有人都会接触到基本相同的技术。因此，最糟糕的结果可能会实现，那就是我们只会得到更多的身份政治和文化不满政治。你认为这会如何发展？政治竞选会因为 AI 变得更智能，还是我们只会更深地陷入文化政治？

AI、政治两极化与公共政策

David Shore: 嗯，显然很难预测未来，我想我今天已经说过了，但很容易想象会发生非常糟糕的事情。深伪技术，无法追踪什么是真什么是假。现在很多人能够制作出有说服力的内容，主张以前不在领域内的事情。但是，我认为在这次讨论中，人们有点低估了现状有多么功能失调。例如，如果你看看社交媒体，大约 5% 的公众负责大部分的社交媒体内容。这很疯狂。我认为现在因为内容制作成本高昂，如果你是一个政治影响者或作家，你的经济动机确实是关注那 5% 的公众，他们消费的政治内容比其他人多得多，而现在政治领域基本上没有人制作专注于不那么关心政治的普通人的内容。举个例子，我认识的一个人有一个 TikTok 用户小组，他录制了他们的手机，大约有 200 人，他付钱让他们这样做，他可以看到谁在看什么。在 Charlie Kirk 被枪击后，有一个人负责大部分的 Charlie Kirk 视频。就在那天，他一直在刷屏观看数百个 Charlie Kirk 暗杀视频。如果你是一个内容生产者，这正是你目前的激励。所以我的观点是，现状确实非常糟糕。而且我认为，如果你看看这些人是谁，他们往往非常焦虑。他们往往非常神经质。现在，注意力游戏确实让你倾向于更负面，而像“你如何真正改变一个人的想法”这样的说服游戏则让你走向完全相反的方向。你知道，我每次做民意调查，每次做测试，通常都说你应该更积极。你应该更多地关注影响人们生活的普通事情。而你知道，这没有发生的原因是实际内容创作者的激励。所以我可以看到，降低内容制作成本，以及扩大谁能够制作内容。这可能是好事，但也，你知道，清楚地说，它也可能很糟糕。我们只是进入了一个完全不同的世界，很难预测任何事情。奇怪的是，政治、 discurso 和思想似乎真的与影响人们日常生活的任何事物脱节。我的意思是，这以前也被提出来过。为什么没有政治家真正把“摆脱垃圾短信”这样的事情作为一个大问题呢？我们都觉得它非常烦人，但你不会，这几乎是不可想象的。

Joe Weisenthal: 我敢肯定你能找到一些关于垃圾短信的单一议题选民。

Tracy Alloway: 没错？但是，如果有人真的认真对待这件事，认为它困扰着所有人，并且努力推动，那会很棒。然而它没有发生，是吗？

David Shore: 是的。我非常喜欢这个统计数据，如果你问人们你最关心什么问题，答案是生活成本，而且优势巨大。但另一方面，如果你看看在过去一年中向民主党竞选活动捐款的人口中 0.7% 的人，那么生活成本就会从第一位下降到第五位，而气候变化则排在首位。所以我想，如果你看看，我认为现状是，政治家现在所谈论的，更多地取决于他们的捐助者关心什么，而不是公众关心什么。我认为这确实很糟糕。我认为我们目前政治功能失调的巨大根源在于，两边的人都没有足够倾听普通人关心什么。你们俩有没有对那些在 AI 调整过程中（我不想说是 AI 厄运场景，因为我知道你们对此意见不一，而是痛苦的 AI 调整过程）真正具有政治可行性的政策有何看法？

David Shore: 我认为公众在这个问题上比人们想象的要激进得多。我个人通常不是那种会说“人们渴望激进的政策变革”的人。但我们现在确实处于一个非常激进的时代。如果你问选民，你是否支持价格管制，答案是 2:1 的支持，这在 5 年前是闻所未闻的。你知道，当我们进行测试时，我们有一个非常激进的测试，我们说“哦，我们将保证你的收入高达 15 万美元。我们将确保你有一份工作。我们将确保你不会被驱逐。”它的测试结果比民主党专业人士制作的 98% 的片段都要好。这个具体的政策，我认为相当激进，在 Trump 选民中获得了约 30% 的支持率和 15% 的净支持率。所以我想说的是，现在每个人都在讨论时间线和政策细节。而你知道，公众所处的激进程度远超政治家或评论员。所以，我认为这是我将要说的最重要的事情，我认为这是被低估最多的问题。最好的测试主题，比民粹主义更好，比 AI 更好的是 AI 民粹主义。而且我认为，我认为这就是事情发展的方向。

深伪技术与民主化

Joe Weisenthal: Burn，这太不祥了。我想回到你提到的关于深伪技术和媒体上每个人都在为少数真正关心政治的人写作的两个观点。我实际上认为深伪技术在一个特定的意义上是一个积极的发展。

Tracy Alloway: 这太棒了。我们可以就这个问题聊上一个小时。

Burn Hobart: 我写这个很久了。我的观点是，总是可以创建一些具有操纵性的媒体剪辑。总是可以说，好吧，在过去的一天里，已经录制了 50 个关于一些令人发指的事件的视频。这是我们选择用来制作新闻报道的一个。这在有足够的资源的情况下一直都是可能的，现在每个人都可以做到。因此，如果你处于可以选择推广哪种叙事的位置，我认为这有点像现代的，就像它实际上是选举人团一样，人们选择观看某些类型的媒体，然后这些媒体会塑造他们的观点，使他们与那种媒体更加相关。所以我们有点在“民主化民主”。我们说任何人都可以制作误导性视频。你不必观看这个人在说话的 20 个小时的录像来找到一个失误。你可以伪造它。而且伪造必须是可信的，例如，如果想要一个能够改变人们看法的可信伪造，它必须与现实相当相似。它不能只是说 Donald Trump 实际上是个外星人。它必须是这样的：Donald Trump 收到了一名卡塔尔商人的现金贿赂。但如果你只能制作那些实际上有点可信的伪造，那么它们就存在于一个与现实相距不远的空间中。同样，那些热门的病毒视频通常是现实中的一个样本，它们是现实中的一个样本，但它们可以通过全方位的视频报道来放大事件的感知频率。所以这是一个观点，我确实认为它实际上让我们这个文化不太可能通过观看一段模糊不清的、抖动的 12 秒视频来对重要问题做出判断。我认为这很好。我认为我们应该多读书，少看视频。但我也认为，当 AI 的另一个方面，目标定位推荐算法，其中有很大一部分 AI 支出和 AI 影响，可能意味着某人更有可能通过煽动反对垃圾税等事情来谋生。我们确实看到了“点击取消”之类的功能正在推进。所以，你知道，那些小小的生活质量改进，比如“点击取消”，是一个市长会非常自豪的事情，但它必须在联邦层面完成。但也许，如果有可能真正瞄准那些，例如，真的想恢复收费厕所的人群，因为他们认为禁止收费厕所会造成各种反常的经济后果，而这确实会发生。你可以找到那些人，你可以动员他们，你可以让他们，你知道，如果某个众议院选举中有一个非常接近的竞争，而其中一位政治家恰好支持这个特定的问题，他们就可以像加密货币社区的人一样，用金钱轰炸那个恰好也支持他们喜欢的事情的人。所以我们实际上有可能以这种方式进一步实现 AI 民主化民主，你可以实际协调那些不太关心政治但仍然关心应该通过政治进程解决问题的人群的利益群体。

David Shore: 是的。我只是想很快插一句，因为，你知道，你说 Burn 说这很可怕，而我，我，我想稍微反驳一下。我真的很喜欢 Ed Glazer 的一句话，你知道，每个人都希望宏观经济学有微观基础，但微观基础本身应该有微观基础，除非我们能给选民一些安全感，否则我们不会体验到任何潜在的生产力收益，或者只会体验到一小部分生产力收益。公众确实在大声疾呼，他们想要经济安全，他们希望能够展望未来 5 年而没有恐惧。如果你能提供一个新的社会契约，如果你能真正提供高水平的经济安全，那么你就可以真正拥有所有这些像部门特定的转变，以获得更高的生产力。但是，如果政治家不提出这样的愿景，那么我们只会陷入一系列拜占庭式的部门特定，你知道，法规和行会，我认为你也不想要。所以我想，你知道，自由主义者真的应该选择，你知道，他们想要什么样的世界。你知道，我们要么可以有一个大规模的解决方案，保护人们的收入，防止他们成为失败者，要么我们只能在每个行业同时进行一场巨大的负和博弈。而且我还要说，你知道，我们现在的情况并不理想，你知道，对于后一种情况而言。所以，我认为情况真的可能会变得相当糟糕。

Joe Weisenthal: David 和 Burn，非常感谢。这是一次引人入胜的对话。我们真的需要再花一个小时来讨论深伪技术正在做什么。但是，非常感谢大家的加入，祝大家今天愉快。

Tracy Alloway: 那是我们在奥斯汀 South by Southwest 现场录制的与 David Shore 和 Burn Hobart 的对话。我是 Tracy Alloway。你可以在 Tracy Alloway 关注我。

Joe Weisenthal: 我是 Joe Weisenthal。你可以在 the stalwart 关注我。关注我们的嘉宾 Burn Hobart，他在 Burn Hobart；David Shore 在 David Shore。关注我们的制作人 Carmen Rodriguez 在 Carmen Arman Dash Bennett 在 Dashbot 和 Kalebrooks 在 Kalebrooks。更多 OddLots 内容，请访问 bloomberg.com/odlots。

Joe Weisenthal: 我们有每日简报和所有节目。你可以在我们的 Discord 上 24 小时 7 天讨论所有这些话题，discord.gg/odlots。

Joe Weisenthal: 如果你喜欢 Odd Thoughts，如果你喜欢我们录制这些现场节目，那么请在你最喜欢的播客平台上给我们一个好评。请记住，如果你是 Bloomberg 订阅者，你可以完全免费收听我们所有的节目。你只需要在 Apple Podcast 上找到 Bloomberg 频道并按照那里的说明操作。感谢收听。

Joe Weisenthal: 是的。

area: "tech-engineering" category: "tech-trends"

project: []

tags:

• "ai-impact"
• "job-displacement"
• "political-economy"
• "technological-change"
• "public-perception"

people:

• "Donald Trump"
• "JD Vance"
• "Ed Glazer"
• "Charlie Kirk"

companies_orgs:

• "Blue Rose Research"
• "Anomaly Fund"
• "OpenAI"
• "Anthropic"
• "PNC Bank"
• "DoorDash"
• "Facebook"
• "Fox"

products_models:

• "ChatGPT"
• "LLMs"

media_books: []

[BODY_START]
### 播客开场白

**Joe Weisenthal**: 各位 **OddLots** 听众，大家好。我是 **Joe Weisenthal**。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Hello, OddLobots listeners. I'm Joe Weisenthal.

</details>

**Tracy Alloway**: 我是 **Tracy Alloway**。

<details>
<summary>Original English</summary>

**Tracy Alloway**: And I'm Tracy Aloway.

</details>

**Joe Weisenthal**: Tracy，我们最近去了 **South by Southwest**。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Tracy, we were down at South by Southwest recently.

</details>

**Tracy Alloway**: 是的，没错。虽然在奥斯汀没吃到烧烤，但我们确实吃了一些非常美味的墨西哥食物。我们还录制了一期非常有趣的播客节目。

<details>
<summary>Original English</summary>

**Tracy Alloway**: Yeah, that's right. I didn't get to have any barbecue in Austin, but we did have some really good Mexican food. We did have really good Mexican food and we recorded a really fun episode of our podcast.

</details>

**Joe Weisenthal**: 没错，更重要的是，我们录制了一期好节目。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: That's right. More importantly, we recorded a good episode.

</details>

**Tracy Alloway**: 是的，没错。所以，请各位听众留意。我们做了一期现场播客节目，讨论了 **AI** 可能导致大规模白领失业的前景，以及政治家应如何思考这个问题，以及选民对此的看法。我们的嘉宾是 **Blue Rose Research** 的创始人 **David Shore**，以及撰写精彩 **DIFF** 简报和 **Anomaly Fund** 普通合伙人 **Burn Hobart**。请听。

<details>
<summary>Original English</summary>

**Tracy Alloway**: That's right. So, check it out listeners. We did a live episode of the podcast talking about sort of the prospect of mass white collar displacement due to AI as well as the politics and how politicians should be thinking about this and how voters are thinking about this. Our guests were David Shore, founder of Blue Rose Research, and Burn Hobart, who writes the excellent DIFF newsletter and a general partner at Anomaly Fund. Take a listen.

</details>

### AI与未来工作

**嘉宾**: 感谢大家在这个寒冷的周日上午前来。

<details>
<summary>Original English</summary>

**嘉宾**: Thanks everyone for coming out on a cold Sunday morning.

</details>

**Joe Weisenthal**: 大家好，欢迎收听 **OddLots** 播客的现场录制。这绝对将是本周末所有对话中最令人振奋的一场，对吧？

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Yeah. Hello, and welcome to a live recording of the OddLots podcast. This is definitely going to be the most uplifting of all the conversations that have happened this weekend, right?

</details>

**David Shore**: 我想是的。我认为它真的会是。

<details>
<summary>Original English</summary>

**David Shore**: I think so. I think it really will be. We are

</details>

**Joe Weisenthal**: 这里的每个人都会感到非常满意。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Everyone here is going to leave feeling really good about

</details>

**David Shore**: 对未来。

<details>
<summary>Original English</summary>

**David Shore**: about the future.

</details>

**Joe Weisenthal**: 好的，我们开始吧。我们有两位出色的嘉宾。我们将与 **David Shore** 对话。他是 **Blue Rose Research** 政治咨询公司的创始人、民意测验专家，对 **AI** 有很深的了解。我们还有 **Burn Hobart**，**DIFF** 简报的创始人，这是一份大家都应该阅读的优秀简报，他还是 **Anomaly Funds** 的普通合伙人。我们将讨论所有关于 **AI**、潜在失业以及其政治影响等话题。David 和 Burn，非常感谢你们今天来到现场。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: All right. Well, let's kick it off. So, we have uh two great guests. We are going to be speaking with David Shore. He is the founder of Blue Rose Research political consultancy pollster knows a lot about AI and we have Burn Hobart, the founder of the DIFF, a great newsletter that everyone should read and a general partner at Anomaly Funds. And we're going to talk about all things AI and job loss potential and the politics of it and so forth. And so, David and uh Burn, thank you so much for uh joining us on stage here.

</details>

**David Shore**: 很高兴来到这里。谢谢。

<details>
<summary>Original English</summary>

**David Shore**: Great to be here. Yeah, thank you.

</details>

**Joe Weisenthal**: 那么，我们来谈谈这个问题。David，你认为现在正在发生。经济可能在一年、18个月后就会发生根本性的变化，你正在努力唤醒政治家。这正在发生。但是，请告诉我们现在正在发生什么，或者即将发生什么。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: So, let's just start um on this question. David, you're pretty like this is happening now. The economy is going to look radically different maybe even a year, 18 months from now and you're trying to wake politicians up. This is happening right now. But like tell us what's happening right now or what's about to happen.

</details>

**David Shore**: 是的，我不是 **AI** 专家，我也不想声称自己是。但我想说的是，我大量使用 **AI**。我大量使用 cloud code。我认为在去年 12 月，我将大约 15% 的税前收入花在了 cloud code 的超额费用上。我认为我周围的朋友之间存在着一种真正的脱节，那些使用 cla code 的人和不使用的人之间。我能真切地感受到，与一个月前和更早的一个月前相比，我现在能做的事情更多了。这些东西改进的规模和速度确实令人震惊。而且我认为，如果你只是使用 **ChatGPT**，你可能不会注意到这一点。就像 **ChatGPT** 似乎比一年前好了一点。

<details>
<summary>Original English</summary>

**David Shore**: Yeah, you know, I'm not an AI expert and I don't I don't want to claim I'm one, but you know what I'll say is that I use AI a lot. I use cloud code a lot. I think in December I spent maybe like 15% of my pre-tax income on cloud code overage fees. And I think there's a real disconnect among my friends between, you know, people who use cla code and people who don't where I could really feel the extent to which I can do so much more now versus a month ago and a month before that. Like the scale at which these things are getting better and the speed at which things are getting better is really jarring. And I think you might not notice that if you're just using chat GBT like you know chat GBT is like a little better than it was a year ago.

</details>

**Joe Weisenthal**: 但话又说回来，对未来做出预测是非常困难的。但我确实认为，如果事情继续以这种规模改进，那么情况可能会非常迅速地变得非常奇怪。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: But again it's very hard to make predictions about the future but I do think that if if things continue to improve on this scale then things could get really weird really quickly.

</details>

**Tracy Alloway**: Burn，我们之所以想和你谈谈，原因之一是你处于技术和金融的交汇点。如果我现在看看大型科技公司和一些 **AI** 公司的估值，它们基本上表明它们将接管整个经济。当你看到这些数字时，它们对你来说预示着劳动的未来会是怎样？

<details>
<summary>Original English</summary>

**Tracy Alloway**: And Burn one of the reasons we wanted to talk to you is because you're sort of at the intersection of technology and finance. If I look at the valuations of big tech at the moment and a bunch of the AI companies, they basically suggest that they're going to take over the entire economy. When you see those numbers, what do they suggest to you about the future of labor?

</details>

**Burn Hobart**: 所以，我认为现在确实如此，你可以将这看作一个连贯的类别，这是一个 **AI** 公司，或者这是一个非 **AI** 公司，但他们正在整合 **AI**，并且他们拥有这些分销优势，所以他们可能会做得很好。但我认为，如果认为这是一个持久的独立类别，就像你可以将许多公司称为电力公司一样，那是一个错误。如果是在 1925 年，你试图弄清楚要买哪些股票，并且你对电力非常看好，那么你就会非常关心 **RCA** 是否与电力相关，而 **US Steel** 则大多不相关。但最终，每个公司都成为电力公司，从某种意义上说，如果灯不亮，你就会经营一个非常不同的业务。所以它就像被经济的其他部分所吞噬。你也可以在软件领域看到这一点，有更多的公司拥有软件开发人员并为内部使用编写软件。它们本身并不是软件公司。它们可能是餐馆或拖拉机公司或其他什么，但它们具有这种元素。所以，我认为这只是任何通用技术推出初期所看到的。你有很多非常狭隘的特定赌注，然后随着时间的推移，影响变得如此广泛分布，以至于很难追溯，你必须回过头来审视历史，审视汽车的兴起导致郊区的兴起，但也导致杂货店的兴起，或者说是超市的兴起，你可以有更多的选择，这意味着每售出单位的劳动力成本更低，这意味着总成本更低，如果人们不是步行去买杂货，那就可以奏效。如果人们是步行，而且每天下班回家的路上都会停留，那就不行。所以，我们可能会看到很多这种奇怪的结果。我想，如果你考虑某个职业的风险，我认为对于大多数人们担心的职业，平均薪酬会上升，而目前在该行业的人的平均薪酬可能会下降，很多人会被淘汰。但这以前也发生过。就像电子表格并没有淘汰投资银行家或会计师这份工作。它实际上使这份工作更有利可图。但它也使这份工作更容易衡量，你不能像以前那样在某些白领职业中有所懈怠。它只是容易得多。对产出的期望如此之高。

<details>
<summary>Original English</summary>

**Burn Hobart**: So, I think right now it's definitely true that we're think you can think of this coherent category of this is an AI company or this is a non this was a non-AI company, but they're incorporating AI and they have these distribution advantages, so they'll probably do well at that. But I think that it's a mistake to think that this is a a durable discreet category in the same way that you could refer to a lot of companies as electricity companies. And if it were 1925 and you're trying to figure out which stocks to buy and you're just really really bullish on electricity, then you you would really really care that RCA is exposed to electricity and I don't know, US Steel is mostly not. But eventually every company becomes an electricity company just in the sense of you would run a very different business if the lights did not turn on. And so it like gets subsumed by the rest of the economy. And you see that with software too where there just a lot more companies that have software developers and are writing software for internal use. And they're not software companies per se. You know, they're restaurants or like tractor companies or whatever, but they have that element. And so I think that's that's part of what you see just early in the roll out of any general purpose technology is that you have a lot of really narrow specific bets and then over time the impact gets so widely distributed that it's very hard to trace and you have to kind of go back and look at the history and look at things like okay the rise of the car leads to the rise of the suburb but it also leads to the rise of the grocery store because or like the the supermarket where you can have a much larger selection and that means lower labor cost per unit sold and that means lower cost overall and that works if people are not walking to get their groceries. It doesn't work if people are walking and it's like a daily, you know, stop on the way home from work or something. So, we will probably see a lot of those weird kinds of outcomes. Like, I think if you're thinking about the risk to a given career, I think for most of the careers people worry about, the average like the mean compensation goes up, the median compensation of people who are in that industry right now, the median compensation they get from being in that industry probably goes down where a lot of people get washed out. But this has happened before. Like the spreadsheet did not eliminate investment banker or accountant as a job. It actually made it a more lucrative job. But it also made it a more measurable one where you just can't slack off the way that you perhaps used to be able to somewhat slack off in some of the white collar professions. It's just a lot easier. Like the expectation for output is so high.

</details>

**Joe Weisenthal**: 我整天都在 **Twitter** 上，很多人都在发推文，我觉得很多人现在都在偷懒。我心想，你们怎么有时间的？我有时间，因为我是一名记者，我专业地创作文字。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: I'm on Twitter all day and a lot of people are tweeting and I'm like it seems like a lot of people are slacking off these days. I'm like how do you have time? I have time because I'm like a journalist and I sit, you know, I create words professionally.

</details>

**Tracy Alloway**: 有人可能会说，你实际上没有时间整天发推文。

<details>
<summary>Original English</summary>

**Tracy Alloway**: Some would argue that you do not in fact have time to be tweeting all day.

</details>

**Joe Weisenthal**: 没错。但是。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: That's true. But

</details>

**Tracy Alloway**: David，那么，**AI** 已经取得了很大的进展，毫无疑问。有新的 **AI** 模型工具可以增强我们的能力。这与我们都知道的情况不同。这与大规模的失业潮不同。在你看来，为什么你认为 **AI** 的进展是如此迫在眉睫，以至于我们必须讨论它可能重塑白领劳动力？

<details>
<summary>Original English</summary>

**Tracy Alloway**: but David, so okay, there's been a lot of progress. No question. There are new harnesses for AI models that increase all of our capabilities and so forth. That's different than we all know that's true. That's different than like job wipeout in a significant way. What is it about to you that you think yes there is progress but progress on the scale of this is an imminent thing that we have to be talking about that could really reshape white collar labor

</details>

**David Shore**: 我经常想到的类比是 **CO**，因为 **AI** 的进步在很多方面都是指数级的。在过去的 6 年里，**AI** 在没有人为干预的情况下自主运行的时间每 112 天或 12 天就会翻一番。当我想起 **CO** 时，那是没有人预料到的事情。然后它发生得非常快。然后我认为政治体系非常被动。而且我认为，私下里，很多民主党人希望他们能以不同的方式处理事情。但很酷的是，与 **CO** 不同，我们真的可以看到 **AI** 的到来。所有的警示信号都在闪烁。我想在这里提出的另一点是，我个人认为大规模失业的可能性很大，特别是白领，但卡车司机和 **Uber** 司机也很多。各种各样的人都可能失业，而且这一切都可能发生得非常快。但我认为更重要的一点是，美国人民看到了这一点，并且非常担忧。当你问人们，在未来 5 年内，**AI** 导致大规模失业的可能性有多大？70% 的人表示非常可能或有点可能。所以，我认为这是我在这里提出的主要观点，即政治家现在就应该采取行动，而不是等到问题出现才采取行动，原因有二：一是美国人民已经对此感到担忧；二是当它已经发生时，我们的政治体系将为时已晚，无法应对。所以，我认为提前行动很重要。

<details>
<summary>Original English</summary>

**David Shore**: the analogy that I think about a lot is co uh because the thing about AI progress is just that it's really in many ways exponential where the amount of time that an AI uh can operate autonomously without a human really has been doubling every 112 12 days or so for the past 6 years. And you know, when I think about CO, this was a thing that nobody saw coming. Uh, and then it happened really fast. And then I think the political system was very reactive. And I think that a lot of quietly, a lot of Democrats wish that they had handled things a little bit differently. But what's cool is that unlike co, you know, we really can see this coming. All of the warning signs are blinking. And you know the other point I want to make here is you know I personally think that there's a lot of potential for large-scale job loss particularly white collar but you know there are a lot of truck drivers there are a lot of Uber drivers um you know all kinds of people could lose their jobs and this could all happen very quickly. I think the more important point though is that the American people see this and are really quite worried. You know, when you ask people, uh, how likely do you think it is that in the next 5 years there might be large scale job loss because of AI? 70% of the population says that it's either very likely or somewhat likely. And so I that's really the main point I'd make there is the reason politically why politicians should act now rather than waiting until there's a problem is you know one the American people are already worried about this and and two once it's already happening it will be too late for our political system to respond and so I think it's important to try to get ahead of

</details>

### 新技术对劳动力市场的影响

**Joe Weisenthal**: 我肯定想更深入地了解政治，但 Burn，你提到了一个似乎是这些对话中的标准观点，那就是我们以前也遇到过这种情况。我们都，好吧，不是真正经历了工业革命，但那是发生过的事情，我们经历了互联网繁荣，经济和社会或多或少都适应了。但当你现在问人们白领工人的替代职业是什么时，我们无法真正提供一系列可能性。我知道很难想象未来，但如果你是一名保险经纪人，你已经做了 20 年，在新经济中你会做什么？新工作是什么？

<details>
<summary>Original English</summary>

**Joe Weisenthal**: definitely want to get more into the politics but Bern you brought up something that like seems to be kind of standard in these conversations which is we've been here before right We all well not literally went through the industrial revolution but that's something that happened and we went through the internet boom and the economy and society adapted more or less but when you ask people now what the alternative professions are for white collar workers we haven't been able to really get like a slate of possibilities I know it's hard to imagine the future but you know if you're an insurance broker and you have been for 20 years what are you going to be doing in the new economy like what are the new jobs that are coming down the line.

</details>

**Burn Hobart**: 是的，这确实是个难题。比如其中一个只是暂时的，我认为有很多工作基本上是出于监管原因需要人工干预的，比如医生是 **AI** 工具的快速采用者，而医生的供给是人为受限的。所以，如果你减少他们花在行政任务上的时间，减少他们犯错误的概率，你基本上就相当于制造了更多的医生。在医疗保健这样的领域，需求实际上是无限的。因为还没有哪个经济体，人们不会将更多的边际收入花在健康上。

<details>
<summary>Original English</summary>

**Burn Hobart**: Yeah, that is actually a tough question. Like one of them is just like temporarily I think there are a lot of jobs that are basically either human who's required to be in the loop for regulatory reasons like doctors are incredibly rapid adopters of AI tools and the supply of doctors is sort of artificially constrained and so if you decrease the percentage of their time that they spend on admin tasks and you decrease the rate of mistakes that they make you basically get the equivalent of manufacturing more doctors and in cases like healthcare there is effectively unlimited demand. like there's yet to be an economy where people don't spend more of their marginal dollar on health.

</details>

**Tracy Alloway**: 所以，我们都将成为医疗工作者。

<details>
<summary>Original English</summary>

**Tracy Alloway**: So, we're all going to be healthare workers.

</details>

**Burn Hobart**: 我认为这实际上是，医疗领域可能会增长。说某些白领工人地位会下降，他们可能会从事听起来不那么酷的工作，这有点令人沮丧。但是，如果总体产出足够高，如果资本回报率足够高，人们就会喜欢，经济开始将更多的增量生产转移到仅仅建设数据中心。这意味着，如果你是数据中心的补充，你就是整个供应链中不可或缺的一部分，那么你的议价能力就会强很多，因为你所处的资本环境更多。如果你完全可以被数据中心取代，那么你就处于困境。我们总是发现模型具有这些非常突出的能力。例如，它们在某些方面是超人的，而在其他方面则不然，比如在数学能力方面。它们已经超越了我可以可靠地区分两个模型并说“这个数学真的很好，这个数学还可以”的程度。

<details>
<summary>Original English</summary>

**Burn Hobart**: I think that's actually like that sector probably will grow and you know that's it's kind of glum to say okay some some white collar workers are going to kind of move downscale in terms of status where they will probably have jobs that sound less cool. But if overall output is high enough and if the returns on capital are high enough that people like the economy starts shifting more incremental production into just building data centers that does mean that if you are the complement to a data center like you you are a necessary component of this entire supply chain your bargaining power is a lot stronger because there's just a lot more capital that you're adjacent to. If you are completely substitutable by the data centers then you're in a tough spot. We we always find that models have these really spiky abilities. Like they're they're superhuman in some respects and in other respects they are, you know, in terms of things like math ability. Like they they're beyond the point where I could reliably distinguish between two models and say, "Well, this one's really good at math and this okay at math."

</details>

**Burn Hobart**: 但在其他领域，它们表现平平，因为它们没有一个全面的世界模型。原因在于它们是在文本上训练的，而文本实际上偏向于不确定和有争议的领域。所以我用“可能球体”这个词来形容，就像你想象有一块事实的基岩，它太明显了，没有人会费心去写下来。然后有无限多的问题，它们太奇怪了，几乎肯定没有答案。就像有一个狭窄的层，像大气层一样，在那里提问是值得的，你可能会得到答案。所以它们对于我们不确定或已在教科书中编纂的世界部分有一个非常好的世界模型，而对于许多显而易见的事情却有一个非常糟糕的世界模型。所以，如果我的工作是向这个超人智能说些极其显而易见的事情，那会有点奇怪。我甚至不知道历史上什么工作头衔可能与此对应，比如一个仆人为一个聪明但又心不在焉的教授服务。但我认为未来会有更多这种“为心不在焉的教授服务的男仆”职业。为心不在焉的教授服务的男仆，听起来不错。

<details>
<summary>Original English</summary>

**Burn Hobart**: But in other domains, they do just kind of fall flat because they they don't have this comprehensive world model. And the reason for that is that they're trained on text and text actually skews towards areas that are uncertain and open to debate. So I I use the term the maybe sphere which is like if you imagine there's like this bedrock of facts that are so obvious that nobody ever bothers to write them down. And then there's this infinite space of questions that are so weird that it's almost certain they don't have an answer. There's like this little narrow layer like an atmosphere where it's worth asking a question and you might get an answer. So they have a really good world model for the parts of the world that we're either not sure about or that we've codified in textbooks and then a really bad world model for a lot of the obvious stuff. And so it would be kind of weird to be like to say like my job right now is to say extremely obvious things to this superhuman intelligence. I don't even know what what job title historically that might correspond to like sort of a servant for you know a brilliant person who's also like a you know absent-minded professor. But yeah I think we'll we'll have a lot more manservant for absent-minded professor professions in the future. Man servant for absent-minded professor. It sounds fine.

</details>

**Tracy Alloway**: David，你有一家公司，你雇佣员工。你的招聘性质是否发生了变化？考虑到技术的变化，你现在招聘的职位类型是否与几年前不同？

<details>
<summary>Original English</summary>

**Tracy Alloway**: David, you have a firm and you hire people. Has the nature of your hiring changed? Are you hiring for different types of roles than you would have a few years ago or something like that given the change in technology?

</details>

**David Shore**: 绝对是。我想举一个简单的例子，我们过去有很多文字编辑来撰写民意调查问题或信息，但现实是，现在 **AI** 在这方面通常比人类做得更好。并非完全如此，但我们有很多。

<details>
<summary>Original English</summary>

**David Shore**: Absolutely. You know, uh I I think just to give a simple example like we used to have lots of copy editors to write polling questions or to write messages and you know the reality is that now AIs are generally better than people at doing that. Not uniformly but we have a lot.

</details>

**Joe Weisenthal**: 它们擅长撰写民意调查吗？比如 **AI** 能不能找到有趣的民意调查问题，而不是那些显而易见的问题，这样你就能从中获得真实的信号？

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Are they good at writing polling? Like can AI you want to find interesting polling questions right not the obvious stuff is AI good at finding nonobvious polling questions that are non-correlated to things so that you can actually get signal from them

</details>

**David Shore**: 嗯，我不想谈得太具体，但我可以说有大量的文字编辑任务。坦率地说，我认为。

<details>
<summary>Original English</summary>

**David Shore**: well you know I I don't want to talk too specifically about that but I I will say that there's just tons of copy editing tasks that I think frankly

</details>

**Joe Weisenthal**: 你为什么不想谈得太具体呢？这意味着这是我应该问的问题。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: why do you want to talk specifically about that means this is the question I should be asking

</details>

**David Shore**: 不，不，不。但是你看，有很多像翻译这样的事情，有很多像文字编辑这样的事情。我认为我们最大的转变是，我们更注重以人为本的工作，而且现在你可以做更多的工程工作。所以我认为在我们的招聘方式上，肯定发生了很大的工作转变。绝对是。

<details>
<summary>Original English</summary>

**David Shore**: no no no but you know look there's a lot of stuff like translation there's a lot of stuff like copy editing I think the big shift for us is that we're focusing a lot more on personentric jobs and you know now you can do a lot more engineering than before. So I think there's definitely been a big job shift you know in terms of how we've been hiring. Absolutely.

</details>

### AI在内容创作中的应用

**Tracy Alloway**: 也许我们可以在这里稍微进行一些内容创作的内省，因为我想这可能也引起了 **South by Southwest** 很多人的兴趣。但是 Burn，你每天都会写一份简报。Joe 和我也一样。你如何在日常工作中利用 **AI**？

<details>
<summary>Original English</summary>

**Tracy Alloway**: Maybe we can do a little bit of content creation naval gazing here since I imagine this is probably of interest to a lot of people at South by Southwest as well. But Bern you write a newsletter on a daily basis. Joe and I do as well. How are you using AI just in your sort of day-to-day?

</details>

**Burn Hobart**: 我在研究方面大量使用它，其中一个具体的用例是问这样的问题：这个笑话能奏效吗？或者，我正在发表一个关于我相当熟悉但并非专家的领域的技术性陈述。你是这方面的专家。告诉我我哪里错了。原因之一是我的很多读者都是软件工程师，而且他们。

<details>
<summary>Original English</summary>

**Burn Hobart**: So, I use it a ton for research and one of the specific use cases is asking a questions like, does this joke land or hey, I'm making a statement, you know, a kind of narrow technical statement about a domain that I'm reasonably familiar with, but I'm not an expert on. You are an expert on this. Tell me what I'm getting wrong. And one of the reasons for that is just a lot of my readers are software engineers and are

</details>

**Joe Weisenthal**: 急切地想告诉你你错了。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: eager to tell you when you're wrong.

</details>

**Burn Hobart**: 是的。非常急切。我有点根据人们作为软件工程师的能力来衡量他们，特别是根据我收到他们发来的电子邮件指出打字错误的速度。因为真正优秀的工程师，他们的一项技能就是查看大量文本并立即发现错误。现在这项技能有点过时了。**LLM** 在这方面做得更好，但“我要查看这些东西并吸收一些连贯的内容，然后寻找其中任何小问题”的心态仍然非常有价值。事实上，由于代码的生产量比以往任何时候都多得多，能够流利地阅读并理解它应该做什么，这真的非常有价值。所以，我大量使用 **AI** 进行研究。直到最近几个月，我才真正从 **ChatGPT** 那里获得了写作的灵感，或者说直到最近几个月，它才提出了一些我从未想到的原创观点，这些观点是巧妙的见解，而不仅仅是它背诵了一个我碰巧不知道的事实。David，再多告诉我们一些。那么，这个关于进步的问题，对吧？我们都知道它正在变得更好。这很明显，但更有趣的问题是，它的进步速度是否比人们之前预期的要快？

<details>
<summary>Original English</summary>

**Burn Hobart**: Yes. Extremely eager. Like I I sort of measure people's ability as as software engineers in particular based on how quickly I get an email from them that there's a typo because the really good ones like one of the skills that they have is just looking at a lot of text and immediately seeing what's wrong. Now that skill is kind of obsolete right now. LM are better at it, but still the mindset of I'm going to look at this and kind of absorb something coherent and I'm going to look for any little issue with it. That's still quite valuable. In fact, since there's more code being produced than ever before by a huge margin, it's really really valuable to be able to read it fluently and understand what it's supposed to be doing. So, um I do I use AI a lot for research. I have only in the last few months have I actually gotten ideas for things to write specifically from chat GPT or only in the last few months have it has it made some original points I would not have thought of that were just like clever insights and not just it's reciting a fact that I did not happen to know. David, talk to us a little bit more. So, this question of progress, right? We all know it's getting better. That's obvious, but the more interesting question is, is it getting better at a pace faster than what people had previously anticipated?

</details>

**Burn Hobart**: 谈谈我们现在的技术水平，以及你所交谈的人会说我们在什么时候，现在是三月吗？2025 年三月。

<details>
<summary>Original English</summary>

**Burn Hobart**: And talk to us about like, okay, where we are now with the technology and where the people that you were talking to, and maybe I'll throw this to both of you, where would they have said we would be in is it March? March 2025.

</details>

**David Shore**: 是的。我认为过去一年最大的惊喜是 **Vibe Coding** 的兴起，以及像 cloud code 这样的工具的兴起。如果你回到一年前，我认为没有人真正预料到这些东西能够进行大规模、复杂、自主的编码问题。我认为在很多方面，这些模型变得有用比它们变得更智能要快。而且我认为这并不是人们所期望的。嗯，有趣的是，每年都会有一群 **AI** 专家会做出预测。其中最大的惊喜之一是这些公司的收入增长，我认为这在很多方面是最重要的基准。我认为 **Anthropic** 去年的收入大约是专家们预测的两倍，而他们我已经认为是非常 **AI** 支持者了。所以，我认为这可能是最大的惊喜。我想说的更广泛的转变是，像 **LLMs** 这样的工具现在被更快地采用。有很多图表，比如收音机、电力或互联网的实施花了多长时间。而 **AI** 的速度比所有这些都要快得多。所以，我真的很担心，当我们谈论过去的转变，比如电话交换机接线员或工厂工人，所有这些事情都发生在很长一段时间内，并且只影响了经济的某些部门。而这项技术真的有可能同时颠覆每一个工作岗位。在人们对经济的总体看法不佳的时候。所以我真的很担心，从政治角度看，我们的政治体系能应对到什么程度。

<details>
<summary>Original English</summary>

**David Shore**: Yeah. I I I think that the big surprise of the last year has been, you know, the rise of vibe coding, the rise of tools like cloud code. If you just went back a year ago, I think that nobody really expected the extent to which these things would be able to do large scale complex autonomous coding problems. You know, I think in a lot of ways these models have become useful faster than they've become smarter. And I don't think that that's something that people expected pro. Well, you know what's interesting is that every year there are a bunch of AI experts who then go and make predictions. Uh, and one of the biggest surprises has been the revenue growth of these companies, which I think is in many ways the most important benchmark. Uh, I think Anthropic's revenue last year was something like 2x what experts who already I think were quite AID predicted. Uh, and so I think that's probably the biggest surprise. And you know what I would say just on the broader transition is uh questions is just that tools like LLMs have been now adopted faster. You know there are a bunch of graphs that are like how long did it take to implement radio or electricity or the internet. And this is much faster than any of those things. And so, you know, I I I really worry like when we talk about past transitions of like telephone switch operators or factory workers, you know, all of these things happened over an extended period of time and only impacted certain sectors of the economy. And this technology really threatens to upend every single job at the same time. You know, at a point when, you know, people's overall views of the economy are not good. And so I really worry just politically the extent to which our political system can handle this.

</details>

**Joe Weisenthal**: 确实，当你审视技术普及程度的这些衡量标准时，我认为真正难以衡量的是，它在什么时候成为你基线期望的一部分，以及在什么时候其影响是如此明显以至于无需言明。所以如果你看看电气化，我认为任何谈论 **AI** 的人都必须说，从第一家电气化工厂到大多数美国工厂电气化，花了大约半个世纪。但原因在于，对此有很多有趣的经济史，你必须以不同的方式运营你的工厂。你实际上必须建造一种不同类型的建筑，而且你还必须以不同的方式融资，或者说你可以以不同的方式融资。所以，如果你的工厂有某种机械动力来源，你倾向于以这些离散的工厂规模增量来扩展你的业务。这意味着你的投资者，你将大部分收益作为股息支付出去，因为留存收益无事可做。这就像如果你要增长，你想要发行大量股票，发行大量债券，然后一次性增长。但是一旦你有了电气化工厂，它们可以扩展，它们可以简单地增加一条装配线，或者它们可以将这台机器升级到一台更新的机器等等，它们实际上可以更有机、更增量地扩展。这就是当你开始看到股息支付率下降的时候，也是当你开始看到“增长型公司”这个概念出现的时候。如果你阅读 1920 年代的投资者报告，他们在谈论股市时，其中一个奇怪的事情是，他们非常关注股票是高于还是低于每股 100 美元，因为那是面值，那是股票的标准价值，它应该就是账面价值等等。然后人们有点将股权视为最次级的索赔人，就像你将一家公司的股权视为一个切片之类的东西，而现在我们完全不同地看待股权，所以我们完全不同地部署资金。对于 1926 年左右的投资者来说，说我要投资一家没有运营的公司，它只有人，然后我要把实际的钱投入这个业务，但大部分将由这些人拥有，然后这个业务，我的股票在几年内可能价值增加 50 倍，如果一切顺利的话，那对他们来说是不可理解的。股票从面值上涨到面值 50 倍的想法简直是疯了。所以我们，但这种变化实际上是，我认为它具有因果关系，而且是双向的，美国拥有一套非常灵活的金融体系。我们还拥有一个相对于所有其他国家都非常灵活的劳动力市场，这意味着我们将成为所有失业问题的零号病人，它会先于其他人打击我们，并且会比其他人打击得更严重。另一方面，这种特殊通用技术推出独特的方面之一是，它的发生速度比以前快得多。但稍微抵消这一点的是，这项特定技术实际上让你能够获取信息和认知，这样你就可以问 **ChatGPT**，比如这是我的工作，我从事保险销售 20 年了。我应该如何再培训？我该怎么做？它会问后续问题。它会问，好吧，你和你的同事面临的其他问题是什么？或者，让我们分解一下你拥有的技能。是什么让你成为一个特别优秀或糟糕的保险销售员？然后你还可以从事哪些受 **AI** 影响较小的工作？或者，随着模型变得越来越智能，你可以告诉它，嘿，我希望你为我发明一份新工作，一份我天生就适合的定制工作。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: It is true that just it like when you look at these measures of how broadly technology is adopted. I think the thing that's really hard to measure is at what point does it become just part of your baseline expectation and what at what point are the impacts so obvious that they're unspoken. So if you look at electrification like I think anyone who talks about AI is just required to say that it took like half a century to go from the first electrified factory to most US factories being electrified. But it's it and the reason for that and there's a lot of fun economic history on this is that you have to run your factory in a different way. You actually have to build a different kind of building and you also have to finance it a different kind of way or you can finance it a different kind of way. So if you have a factory that has some kind of mechanical power source, you tend to expand your business in these discrete factory-sized increments. And what that means is that your investors, you pay out most of your earnings as dividends because there's nothing to do with retained earnings. It's like if you're going to grow, you want to issue a bunch of stock, you want to issue a bunch of bonds and then grow in like one shot. But once you have electrified factories where they can expand, they can just add another assembly line or they can upgrade this machine to a newer machine, etc., they can actually expand more organically and incrementally. And so that's when you start to see dividend payout ratios come down and that's when you start to see the growth company as a concept emerge. Like if you read investor accounts from the 1920s and they're talking about the stock market, one of the weird things is they're they're very fixated on whether the stock is above or below $100 a share because that was the par value that was just like the standard value for the stock and it was supposed to be the book value etc. then people kind of viewed equity as just the most junior claimant like the way you view equity the equity slice of a co or something like that and now we view equities completely differently and so we deploy money completely differently like it would be incomprehensible to an investor circa 1926 to say I'm going to invest in this company that has no operations it's just people and I'm going to you know put the actual money into this business but most of it will be owned by these people and then the business you know my stock could be worth 50 times as much in a few years if things go perfectly like that wouldn't make any sense to them. The idea of a stock going from par value to 50 times par value is just insane. So we but that that change actually was part of I think it was like causal and in both directions with America just having a really flexible financial system. We also have a really flexible labor market relative to every other country which means we will be patient zero for like all the job loss stuff like it'll hit us before it hits anyone else and it'll hit us harder than anyone else. On the other hand, one of the unique things about this particular general purpose technology roll out is that it is happening much much faster than before. But in the thing that slightly offsets that is that the specific technology actually gives you access to information and cognition such that you can ask chat GPT like here is my job like I've been selling insurance for 20 years. How should I reskill? Like what should I do? And it will ask follow-up questions. It'll ask, okay, well, you know, what do what other problems do the companies and people you work with have? Or, you know, let's break down the skills that you have. What makes you a particularly good or bad insurance person? And then what are the other jobs that might be less AI exposed that you could do? Or, you know, as the models get smarter, you could just tell it, hey, I want you to invent a new job for me, like a bespoke job I was born for.

</details>

**Tracy Alloway**: 不，你已经有那份工作了。

<details>
<summary>Original English</summary>

**Tracy Alloway**: No, you already have that job.

</details>

**Joe Weisenthal**: 没错。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: That's right.

</details>

**Tracy Alloway**: 播客主持人是安全的。我想我们可以提问。但我的意思是，当好处是你可以问 **ChatGPT** 你的替代工作是什么时，这确实有点反乌托邦。

<details>
<summary>Original English</summary>

**Tracy Alloway**: Podcasters are safe. I guess we can ask questions. But I mean it does seem kind of dystopian when the upside is well you can ask the chat GPT what your alternative job is and

</details>

**Burn Hobart**: 但这些东西在当时总是感觉反乌托邦。如果你在 200 年前告诉某人，嘿，你继承你父亲的农场并在那个农场工作，然后把那个农场传给你的儿子，这将是完全不可行的。如果你说，这不仅在经济上不可行，而且你也不会如此专注于是你的儿子还是你的女儿，而且你可能会搬到一个城市，你会被完全陌生的人包围，你会有一份在一个吵闹、嘈杂、非常不舒服的建筑里工作，摆弄着这些你正在制造的物理东西。很多人会说那简直是噩梦。事实上，很多当时的观察者都谈到那是一种噩梦，但最终随着时间的推移，它运作得相当好。它只是新的、奇怪的，从最初的角度来看是完全不可理解的。

<details>
<summary>Original English</summary>

**Burn Hobart**: but this stuff this stuff always feels dystopian at the time like if you told someone 200 years ago hey it's going to be completely non-viable for you to inherit your father's farm and work on that farm and then give that farm to your son like and if you said you know not only is that economically nonviable but you're also not going to be so fixated on is it your son or your daughter and also you're probably going to move to a city you'll be surrounded by complete strangers you'll have a job like in this loud, noisy, very uncomfortable building like messing around with, you know, whatever these physical things you're manufacturing are. Like a lot of people would say that's that's kind of nightmarish. And in fact, a lot of contemporary observers did talk about that being kind of nightmarish, but it did end up working out reasonably well over time. It was just new and weird and completely incomprehensible from the original standpoint.

</details>

### 效率收益的分配与挑战

**Joe Weisenthal**: 让我换一种方式提问，那就是，谁在这里获得了生产力收益，以及它们是如何分配的？因为我可以想象这样一种情况：我们都有工作。我们的工作中有些任务是我们不喜欢做的，如果我们可以使用 **AI** 更高效地完成这些任务，那么这可能对我们很有好处。但历史上充满了新技术的例子，这些技术被宣传为生产力增强器，比如电子邮件会让你更快地完成工作，但结果却是电子邮件意味着我们必须全天 24 小时回复电子邮件，我们只是得到了更多的邮件，这实际上让我们更痛苦。谁在这里获得了效率收益？

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Let me ask the question in a slightly different way, which is like who captures the productivity gains here and how are they distributed? cuz I can imagine a situation where we all have jobs. There are certain tasks in our job that we don't necessarily like doing and if we can use AI to do them more efficiently, then maybe that's great for us. But history is full of examples of new technology that is pitched as, you know, a productivity enhancer like email is going to let you do things faster and then it turns out that actually email means we have to reply to emails 24 hours a day and we just get more volume and it actually makes us more miserable. Who captures the efficiency gains here?

</details>

**Burn Hobart**: 那些在能够产生更多经济产出时不会感到痛苦，但必须以不同方式付出关注或投入更多努力的人。不，这些东西确实有负面副作用，但当沟通成本下降时，你可以进行的协调量就会大幅增加，并且你可以以不同方式进行协调。我认为这也说明了预测服务业工作的需求是非常困难的，因为它很多都是如此元化，比如很多都是与其他服务业部分互动。所以像 **Excel** 是一个正确的例子，但也有文字处理，你可以认为，文字处理让律师更容易快速起草合同，所以我们需要更少的律师。但实际上，这意味着他们可以将两页的合同变成 50 页的合同，然后你需要更多的律师来处理。Joe，我有没有告诉你我在康涅狄格州遇到一个人，他正在接受文字编辑培训？他两年前开始的，我当时只是想，天哪，时机太糟糕了。

<details>
<summary>Original English</summary>

**Burn Hobart**: People who don't feel miserable when they can produce more economic output but have to pay different kinds of attention or put in more effort. No, like it is true that these things have negative side effects, but like when the when the cost of communication goes down, the amount of coordination you can do goes way up and you can coordinate in different kinds of in different ways. And I think this this also illustrates that it's very hard to predict the demand for service sector work because a lot of it is so meta like a lot of this interacting with other parts of the service sector. So like Excel is kind of the tright example, but there's also word processing where you could think, okay, word processing makes it easier for lawyers to just quickly draft contracts and so we'll need fewer lawyers. But actually it meant they could turn a two-page contract into a 50-page contract and then you need more lawyers to handle that. Joe, did I tell you I met someone in Connecticut who was training to be a copy editor? He started two years ago and I just thought, my god, what bad timing.

</details>

**Joe Weisenthal**: 我听过一些其他故事，比如我最近听说有人在大约六个月前参加了一个编码训练营，我觉得时机真尴尬。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: I've heard a few other stories like I heard someone recently they like went to like a coding boot camp like six months ago and I'm like that's awkward timing.

</details>

**Tracy Alloway**: David，在你的民意调查中，谁最喜欢 **AI**，谁最不喜欢 **AI**？

<details>
<summary>Original English</summary>

**Tracy Alloway**: David, in your polling, who likes AI the most and who likes AI the least?

</details>

**David Shore**: 是的，有一个非常明确的联盟。实际的水平很大程度上取决于你如何提问，但主要的人口结构差异是年轻人比老年人更喜欢 **AI**，男性比女性更喜欢 **AI**，这可能不足为奇。然后我认为有趣的是，总的来说，受过教育的人对 **AI** 的看法要积极得多，他们讽刺的是，尽管谈论白领失业，但拥有学位的人，我认为他们是最乐观的，而工薪阶层的人则不那么乐观。最后，总的来说，非白人对 **AI** 更悲观，而黑人和拉丁裔选民则普遍更乐观。例如，密西西比河三角洲实际上是那些对 **AI** 感到兴奋的人比例最高的地区。

<details>
<summary>Original English</summary>

**David Shore**: Yeah, there's a pretty clear coalition. You know, the actual levels depend a lot on how you ask it, but the main demographic split is that young people like AI a lot more than older people than men more than women, which is probably unsurprising. And then I think interestingly, generally, educated people have much more positive views, they they ironically, despite all the talk of the white collar job loss, it's it's the people with degrees, who I think are the most optimistic, and then working-class people are a lot less optimistic. And then finally, after all of that, generally speaking, not white people are more pessimistic about AI, and black and Latino voters are are generally more optimistic. Uh, you know, the Mississippi Delta, for example, actually has the highest rate of folks who are uh excited about AI.

</details>

**Tracy Alloway**: 这很有趣。等等，解释一下受过教育的人和更像工薪阶层的人之间的态度差异。这仅仅是因为工薪阶层，我想，也许历史上更习惯于被坑，说句不好听的话？

<details>
<summary>Original English</summary>

**Tracy Alloway**: That's interesting. Wait, explain the difference in attitudes between the educated and more like working class. Is that just because the working class is, I guess, maybe historically more used to getting screwed over, for lack of a better word?

</details>

**David Shore**: 我认为这正是如此。你看，那种“工作会改变，但会有大量的增长，会有新的工作”的故事，我认为非常值得一说的是，选民对这种说法极其怀疑。如果你去问，“你对 **AI** 会创造大量新工作的说法有多信任？”我认为大概是负 40。现实是，选民现在对经济极其负面。真的很难夸大其词，大约三分之二的公众认为经济被操纵了。只有 35% 的公众认为自己财务安全。在这种背景下，人们感到非常愤怒，他们对“事情会好起来”的说法极其怀疑。而且很明显，工薪阶层的人记得制造业的衰落。他们喜欢基本上每一次重大的经济转型都有赢家和输家，赢家通常是前 1% 或前 10%。经济学家对此争论不休，但其他人则遭受了损失。所以，我想说的主要观点是，我认为 **Burn** 所描绘的图景不会被允许发生，因为公众有发言权。这是一个非常重要的问题。公众会，如果不了解政治将会如何，几乎不可能谈论未来。让我问你，你与民主党人合作，当我想起民主党人和 **AI** 时，我认为有几件不同的事情。在“L”大写左翼阵营中，有相当大一部分人认为这都是骗局，认为这就像是 **Theranos** 再现，就像 **NFT**，这在经济上是不可持续的。然后有点像反数据中心的人。他们不希望数据中心出现在他们后院。他们根本不希望数据中心存在。然后有点像民主党内部一直在发展的东西。就像反大科技公司和反寡头等等。有没有你与之交谈的人，他们最，我正在努力思考确切的词语，认真对待它，认为它是一项将要发展的重要技术？有没有你与之交谈的人说，不，这实际上是有效的，这是真实的，这可能带来生产力收益等等，或者几乎只是各种政治负面情绪？

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<summary>Original English</summary>

**David Shore**: Well, I think that is exactly it that you know the way it would all just he painted the story of well, you know, the jobs are going to change, but there's going to be tons of growth. There's going to be new jobs. And I think it's just really worth saying that voters are extremely skeptical of this claim. Like if you go and you say, "Oh, how much do you trust the statement that AI is going to create lots of new jobs?" I think it's something like minus 40. The reality is that, you know, voters are extremely negative about the economy right now. It's really impossible to overstate where something like twothirds of the uh public thinks the economy is rigged. Only 35% of the public think feels that they're financially secure. And uh in that context where people are genuinely quite angry, they are extremely skeptical of the claim that things are just going to be okay. Uh and obviously you know working class people remember the decline in manufacturing. They like basically every economic big economic shift has had winners and losers and the winners generally have been either the top one or the top 10%. The economists argue about that but other people have lost. And so you know the main point I want to make is just I think the picture that Brin is uh painting isn't going to be allowed to happen because the public has a say. This is a really important point. The the public will sort of it's almost impossible to talk about the future without knowing what the politics are going to be. Let me ask you, so you work with Democrats and when I think about the Democrats and AI, I think there's like a few different things. There's a pretty big contingent on the sort of capital L left that thinks it's all a fraud, that thinks it's like this is therronos again, this is NFTTS, this is completely economic sustainable. Then there's sort of like the anti-data center people. They don't want them in the backyard. They don't want them around period. Then there's sort of like what's been building in the Democratic party for a while. Just the sort of like anti- big tech and the sort of the anti-olarchs stuff like that. like is there anyone that you talk to who's most um I'm trying to think of the exact term taking it very seriously as an important technology that is going to evolve like is there anyone you talk to who's like no this actually works this is real this could be a productivity gains etc or is it almost just various flavors of political negativity

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**David Shore**: 嗯，我认为背景是这是一个非常新的政治问题。甚至自去年以来，关心 **AI** 的选民比例比我们跟踪的其他 39 个问题中的任何一个都增长得更多。所以政治家显然正在迎头赶上。通常政治家都是相当被动的。但是，我想说的是，我认为民主党人比共和党人更有能力利用这一点，原因很简单，共和党人在这方面把自己逼到了绝境。**Donald Trump** 在录音中说 **AI** 将创造大量新工作，失业不会发生。**JD Vance** 发表演讲说：“哦，我们永远不会监管 **AI**。”所以我想，从我的对话来看，我看到民主党政治家比六个月前更关心这个问题。而且我认为人们正在努力弄清楚正确的应对方式是什么。等等，多说说你为什么认为 **AI** 会如此迅速地成为一个关注点，因为我知道，这个房间里的每个人可能都玩过 **ChatGPT** 之类的东西，但我想对于大部分人口来说，它还没有真正影响到他们的日常生活。所以，看到 **AI** 担忧如此迅速地爬上担忧榜，这有点令人惊讶。

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<summary>Original English</summary>

**David Shore**: well I think the backdrop is that this is a very new political issue you know Even since last year, the share of voters who care about AI has increased more than any of the other 39 issues that we're tracking. And so politicians obviously are catching up. Usually politicians are pretty reactive. Um, but you know what I will say is I think that Democrats are in a much better position to capitalize on this than Republicans are just for the basic reason that Republicans have really painted themselves in a corner on this. You know, Donald Trump is on tape saying that AI is going to create tons of new jobs, that job loss isn't going to happen. JD Vance gave the speech where he was like, "Oh, we will never regulate AI." And so I I think, you know, just from my conversations, I'm seeing Democratic politicians care a lot more about this than they did 6 months ago. And I think that folks are kind of amling about to figure out what the right way to respond is. Wait, say more about why you think AI has become a concern so quickly because I, you know, everyone in this room has probably played around with chat GPT and things like that, but I would imagine for a big chunk of the population, it hasn't necessarily impacted their day-to-day lives just yet. So, it's kind of surprising to see AI concerns rise the ranks of worries so fast.

</details>

**David Shore**: 嗯，我认为人们确实看到了未来的迹象。基本上，目前大约 60% 的公众使用过这些工具，13% 的公众每天使用它们，我认为人们真的低估了公众的担忧程度，或者说，我认为这些工具确实正在广泛地应用于各个不同的行业。上周末我与一位医疗技术人员交谈，他告诉我，“哦，是的，**AI** 正在部署。”她在一个蒙大拿州的农村医院工作，即使在那里，她也说，“哦，是的，**AI** 正在广泛部署。”我认为，这又是在选民对经济感到极其负面的背景下发生的。所以，每当他们看到大规模革命的前景以及他们的所有工作将如何发生变化时，我认为他们非常担心自己会倒霉。Burn，我想你和对立面的人有联系。是的。而且在那里也有一些有趣的裂痕，因为显然我们有那种非常热衷于进步和加速等的科技右翼。然后你有一些显而易见的民粹主义联盟。政治家们谈论如果有了自动驾驶卡车那会多么糟糕，那对司机来说会多么可怕。你如何看待另一边正在移动的构造板块？

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<summary>Original English</summary>

**David Shore**: Well, I do think people see the writing on the wall. you know that basically as it stands something like 60% of the public has used these tools 13% of the public uses them every day and I think that people really underestimate the extent to which the public is concerned or the I I think these tools really are being rolled out quite widely across a whole host of different sectors. You know, I was talking this weekend to, you know, a medical tech who was like, "Oh, yeah, no, the AI is being deployed." Like, you know, she was in a rural hospital in Montana, and even them, she was like, "Oh, yeah, no, AI is being deployed quite widely." And I think that again, this is happening in the context of voters feeling extremely negatively about the economy. And so, whenever they see the prospect of a large-scale revolution and how all of their jobs are going to happen, I think that they're very concerned they're going to be screwed. Burn, you're you're plugged into the opposite side of the aisle, I believe. Yes. And on there, there's some interesting cleavages as well because obviously we have the sort of the tech right that's very enthusiastic, the progress and acceleration and so forth. And then you have the sort of obvious like populist coalition. You have like politicians talk about how awful it would be if you know we ever had self-driving trucks and how terrible that would be for uh drivers. What do you how do you see the uh tectonic plates moving around on the other side?

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**Burn Hobart**: 嗯，我喜欢 **AI**，所以我在政治维度上非常悲观。我认为部分原因在于，当你向人们提出 **AI** 问题时，当你使其突出时，他们会持一种观点。但如果你看他们的行为，他们会持另一种观点。我认为这是一个更广泛的观点，即大规模部署技术会增加衡量到的收入和财富不平等，但会减少消费不平等。所以像坐飞机这样的事情就变得更容易负担得起。最近有一些数据表明 **DoorDash** 的使用在低收入人群中最为频繁。所以你只是能够获得很多东西，而以前要么没有人拥有它，要么只有非常富有的人拥有它。实际上，**CHTBT** 就是这样一种东西，如果它不存在，而且我更富有，我就会雇人做这类事情。我只会问他们一些关于历史的奇怪问题，或者让他们去做一些小小的研究任务，而且如果他们一周后回来向我提交这份报告，我说：“哦，我实际上改变主意了。我不再关心那个了。但我现在要下一个任务。”我一点也不会感到不好意思。但你可以在 **LLM** 上做这件事。但老年人群名义上不喜欢 **AI**，但他们在 **Facebook** 上花了很多时间，这意味着他们实际上非常喜欢 **AI**。他们喜欢 **AI** 推荐引擎。他们非常容忍 **AI** 推荐的广告。他们喜欢 **AI** 生成的图像和 **AI** 生成的文本。他们在 **AI** 会告诉他们评论应该说什么而他们不必自己想出评论的网站上感到更自在。人们实际上从消费角度喜欢 **AI**，但从外部抽象角度讨厌它。所以让我更乐观的是，这些不同问题的突出程度会随着时间的推移而波动。也许 **AI** 的部署速度如此之快，以至于它变成了背景噪音，就像内燃机或电力，甚至是互联网一样。现在互联网不是一个竞选议题。它在 2000 年曾是一个议题，我想在 2016 年和 2020 年也存在一些互联网问题，但它的突出程度越来越低。我们不再考虑你是支持还是反对它，它只是存在。而且我认为，随着 **AI** 带来的许多无形的生产力收益，或者说不那么突出的生产力收益，我们处于一个更好的世界，人们不会认为 **AI** 只是作业作弊和剽窃，比如可否认的剽窃机器，再加上夺走我最好潜在工作的东西。

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<summary>Original English</summary>

**Burn Hobart**: Well, I like AI, so I'm I'm very pessimistic on the political dimension. And I think part of it is that when you ask people about AI, when you're making it salient, they have one set of views. But if you look at their behavior, they have a different set of views. And I think this is like a broader point about the large scale deployments of technologies is that they do increase measured income and wealth inequality, but they decrease consumption inequality. So things like flying on a plane is just a much more attainable affordable thing. There were some recent stats on how Door Dash usage is heaviest among lower income people. And so you you just have access to a lot of things where it used to be that either nobody had it or only very wealthy people had it. And actually, CHTBT, it is the kind of thing where if it didn't exist and I were much much wealthier, I would just hire people to do that kind of thing. I would just ask them weird questions about history or just send them off on little research tasks and I wouldn't feel at all bad if they get back to me, you know, a week later and present me with this report and I say, "Oh, I actually changed my mind. I don't care about that anymore. Just but here's the next one." But like you can you can do that with an LLM. But also, older demographics nominally don't like AI, but they spend a lot of time on Facebook, which means they actually do really like AI. They like AI recommendation engines. They are very tolerant of AI recommended ads. They love AI generated images and AI generated text. They feel much more comfortable on a site where an AI is actually going to tell them what the comment should say and they don't have to come up with a comment. Like people actually love AI from a consumption perspective and hate it from like the outside abstract perspective. So the the thing that makes me more optimistic is just the salience of these different issues fluctuates over time. Maybe AI deployment is so fast that becomes just part of the background noise like the internal combustion engine or electricity or even the internet where like the internet is not a campaign issue right now. It was sort of an issue in 2000 and it's been I guess you know there were internety issues in 2016 and 2020 but it's it's becoming less and less salient. We just don't think about like are you pro or anti like it just is. And I think that with a lot of these invisible productivity gains from AI or, you know, less salient productivity gains from AI, we're in a better world where people are not thinking AI is and is only the homework cheating and plagiarism like deniable plagiarism machine plus the thing that's taking away my best potential job.

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**Joe Weisenthal**: 你们有没有最喜欢的历史类比，可以用来理解现在 **AI** 的政治或社会视角？

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<summary>Original English</summary>

**Joe Weisenthal**: Do either of you have a favorite historical analogy for AI right now in terms of understanding it from a political or social perspective?

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**David Shore**: 你知道，对我来说，正如我之前所说，我认为它是 **CO**，我认为这会很快发生。人们痴迷于它何时发生，或者如何发生。但我认为选民讨厌改变。我认为这是政治中最被低估的现状偏见之一，这种偏见非常强烈。如果你看看这个国家最受欢迎的政治家是谁，总是一些什么都不做的州长。你知道，这是一个被低估的政治事实。所以我认为，如果你谈论一个所有工作都在同时转型，有大量赢家和输家的世界，人们显然会纠结于 **AI** 是否会让人人都失业这个问题，但如果 3% 的人因为 **AI** 而失业，那就会成为世界上最大的问题。你知道，每当收益分散而损失集中时，那就像是公共选择理论中的混乱秘方。所以，我真的很喜欢 **CO** 的类比，因为 **CO** 基本上是一次性发生的，然后我们的政治体系被打乱了，新的联盟形成了，很难做出回应。每当你回溯过去，正如我们之前谈到的，很难想到一个经济转型发生得如此之快。

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**David Shore**: You know, for me, as I said before, I think it's co where I think that this is going to hit very quickly. People get obsessed about, you know, exactly when it will happen or exactly how it will happen. But I think voters hate change. I think that that's one of the most underrated status quo bias of politics is very strong. If you look at who are the most popular politicians in the country, it's always, you know, the governors who do absolutely nothing, you know, um, uh, underrated political fact. So I think if you're talking about a world where every single job is being simultaneously transformed and there are tons of winners or losers like you know obviously people get hung up on this question of will everyone lose their job because of AI but if like 3% of people lose their job because of AI it's just going to be the biggest issue in the world you know whenever you have diffuse benefits and concentrated losers that's just like a public choice recipe for chaos and so I really like the co analogy because co happened basically all at once and then our political system was scrambled and new coalitions were created and it was very difficult to respond and I whenever you go back as we talked about before it's really hard to think of an economic transition that happened that quickly

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**Joe Weisenthal**: Burn

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<summary>Original English</summary>

**Joe Weisenthal**: burn

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**Burn Hobart**: 是的，我认为 **CO** 的类比可能以另一种方式揭示了一些东西，那就是联盟完全多次转变。就像在一月份，只有那些奇怪的、极度在线的右翼匿名人士和少数理性主义者说这是一件大事，我们需要关闭往返中国的航班，对于 **EA** 类型的人，对于理性主义者类型的人来说，这更像是一种对潜在生存威胁的审慎回应。然后我认为对于许多极右翼人士来说，这是一种让中国难堪的方式，也是为了减少往返中国的航班，因此我们希望这样做。然后，我认为 **Trump** 非常依附于 **S&P** 告诉他这是好事还是坏事。你可以看到，我想如果他有一个实时行情显示器告诉他市场对他的早期 **COVID** 演讲的反应，我们就会有一个完全不同的 **CO** 政策。然后我们有点翻转了，现在右翼变得更像 **CO** 自由主义者，你知道，就是任其发展。你知道，我们都会在某个时候对这种病毒免疫。这对我来说真的很奇怪，因为右翼的年龄偏大，而老年人更容易受到风险。

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<summary>Original English</summary>

**Burn Hobart**: yeah I think I think the co analogy might be revealing in another way which is like the coalition's completely shifted multiple times it was like in January it's only the weird online extremely online right-wing anonymous people and then a handful of rationalist people who say this is a really big deal and it's like we need to shut down air travel from China and like the for the EA types for the rationalist types that was more like this is a prudent response to a potential existential threat and then I think for a lot of people on on the far right it was like this is a way to make China look bad and also to have fewer flights to and from China and therefore we want to do it. Um, and then, you know, Trump, I think, was very just tied to what the S&P was telling him about whether this was a good thing or a bad thing. Like, you could kind of see it like I I think if he'd had a live ticker telling him how the market was reacting to some of his early COVID speeches, we would have had a completely different co policy as a country. And then we kind of did this flip where now then the the right became the more co libertarian, you know, just let it rip. You know, we're all going to be immune to this at some point faction, which was really weird to me because the right skew is older and older people were more at risk.

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### 政治与公共议题

**Burn Hobart**: 但我想这又回到了显着性和信息环境。如果你处于你久坐不动、年迈且久坐不动的群体中，因为你花了很多时间看电视。如果你在电视上看的是 **Fox**，那么你可能会对世界有一个非常不同的看法。所以我认为联盟可能会波动很大。我认为实际上没有任何，我认为两个主要政党都不是“增长派”的良好归宿，他们可以是民主党中的少数，也可以是共和党中的少数，并且必须在某种程度上妥协才能拥有任何影响力。所以从这个意义上说，再次非常悲观。但当你谈到显着性变化的议题时，我认为在你拥有的数据中，就像一年前是贸易，每个人都痴迷于贸易，然后贸易成为一件大事，并且一度成为头条新闻的主要制造者，然后它就有点淡出了。所以，即使像现在全球贸易的状况仍然非常混乱。事实上，就石油贸易而言，它比几周前更混乱。没错。所以，从这个意义上说，贸易就像日常的“你比一周前过得更好吗”这个问题，贸易仍然是最显着的问题。我的意思是，也许如果有新的模型发布，那会改变一些事情，但就目前而言就是这样。所以，是的，这都是非常不稳定的。我认为与此最密切相关的技术是晶体管和集成电路，它们可能是最接近的映射，从字面上讲，它们是一种让你生活中所有东西都变得更智能一点的方式。而想到我们家里有多少小小的白痴天才设备可以进行小计算和运算，并且拥有一个漂亮的界面，以及这些东西变得如此便宜以至于基本上免费，这简直令人震惊。就像，想到我们能否建造一个完全由机械控制的微波炉，里面没有晶体管，那将毫无意义。为什么要这样做？说到政治，David，你认为这可能吗？比如说，总统支持，未来的总统支持，有人提出一项法案说，“我们要禁止 **AI**，禁止新的 **AI** 数据中心建设。”你认为有可能通过这样的法案吗？因为我觉得这听起来很疯狂，但我也越想越觉得。

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**Burn Hobart**: But I I guess it goes back to salience and information environment. And if you are if you're in the cohort where you're you're sedentary, you're elderly and you are sedentary because you're spending a lot of time watching TV. If what you're watching on TV is Fox, then maybe you just get a very different view of the world. So I think the coalitions probably fluctuate a lot. I don't think there's actually any I don't think either major party is a good home for the progrowth abundance faction like they can be a minority among Democrats or minority among Republicans and will have to sell out in some ways to have any kind of influence whatsoever. So in that sense again pretty pessimistic but when you were talking about the the issues that changed in salience I think in the the data you had it was like a year ago it was trade and everyone was obsessed with trade and then trade became a huge thing and was like the main producer of headlines for a while and then it kind of faded. So and even though like the situation is still very messed up in terms of global trade. In fact it is it is more messed up than it was a few weeks ago in terms of oil trade. That's right. So, in that sense, trade is like the the day-to-day like are you better off than you were a week ago question, trade is still the most salient issue. I mean, maybe if there's a new new model release that'll change things, but uh for now that's the case. So, yeah, it's it's all pretty volatile. I I in terms of the the technology that I think maps most closely to this, I think the transistor and integrated circuits are probably probably the closest mapping like one in the literal sense of they are a way to make everything in your life a little bit smarter. And it is just astonishing to think of how many little idiot savant devices we have in our homes that can do little calculations and computations and have a nice little interface and how that stuff got so cheap that it basically became free. Like it would not make sense to think about can we build a microwave that has entirely mechanical controls with no transistors inside of it. Like why would you do that? Speaking of politics, like David, do you think it's plausible? Let's say the president were for it, a future president were for it, someone puts up a bill and says, "We're gonna ban AI, new AI data center construction." Could you see a world where that actually passes? Cuz I feel like that's like that seems crazy, but also I more I think about it,

</details>

**Joe Weisenthal**: 这似乎有可能通过。

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**Joe Weisenthal**: it almost seems like it could pass.

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**David Shore**: 是的，我可以看到各种事情都可能发生。我们可能会有一个分裂的政府，所以在这种情况下，押注任何特定事情的发生都是不明智的。但就像我们一样，禁止投资者拥有房屋非常受欢迎，两党似乎都非常支持公司不应该拥有大量单户住宅的观点，这似乎完全跨越了两党。反数据中心的事情在我看来也类似，它似乎不是一个左派或右派的事情。它似乎是一个非常广泛的民粹主义、TikTok 政治的事情。

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**David Shore**: Yeah, I could see all kinds of things passing. Uh we're going to we'll probably have divided government and so it's always good to bet against any specific thing happening in that situation. But like we just you know there it's very popular for example to ban investors from owning homes for example which is both parties seem to be like very into that idea that corporations shouldn't own large swaths of single family homes totally seems to cut across both parties. The anti-data center thing strikes me as similar where it does not seem like a right or left thing. It seems like a very broad populist tick- tock politics sort of thing.

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**David Shore**: 是的，我想说的是关于数据中心的民意调查，如果你调查“你想要你家附近有一个数据中心吗？”人们会说不。但另一方面是，如果你添加任何东西，比如“如果它由清洁能源建造，或者如果它能降低你的税单 10% 呢？”那么它就会变得非常受欢迎。我看到很多政治家似乎都抓住了数据中心这个问题，因为这只是一个巨大的可怕问题，而数据中心的东西只是一个非常清晰的土地利用问题，我认为那将是一个错误。不是因为我个人非常关心我们是否禁止数据中心，而仅仅是因为我认为公众真正想要的是其他东西。比如如果我们明天禁止数据中心，那并不能改变选民认为经济被操纵了，或者他们非常害怕未来的事实。而且你知道，在我们的测试中，我们通常测试了几十种谈论 **AI** 的不同方式。而且你知道，数据中心的事情我认为并没有真正打动公众。而我认为真正打动公众的是，更激进地谈论工作保障或收入保障，或驱逐保护。我认为存在巨大的恐惧，政治体系应该努力解决它，而且不仅仅是应该，我认为它会，你知道，因为我们生活在一个民主国家。

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<summary>Original English</summary>

**David Shore**: Yeah. You know what I'll say about the polling on data centers is it's true that if you poll, you know, do you want a data center in your neighborhood? People say no. But the flip side is if you add literally anything to it. If you're like, what if it's built by clean energy or what if it lowered your tax bills by 10%. Then suddenly it becomes really popular. I've seen a lot of politicians like kind of grab for the data center thing because this is just like a big scary issue and the data center stuff is just like a really legible. land use and that I think it would be a mistake. Not because I care that much personally whether we ban data centers or not, but really just because I think the public really wants something else. Like if we ban data centers tomorrow, that really doesn't change the fact that voters think that the economy is rigged or that they're very scared about the future. And you know, in our testing, you know, we've generally tested uh dozens of different ways to talk about AI. And you know, the data center stuff I think just doesn't move the public very much. Uh while what does uh I think is actually just being a lot more radical talking about job guarantees or income guarantees uh or eviction protections. Like I think that there's just an enormous amount of fear and uh the political system should try to address it and it's not just should I think it will you know because we do live in a democracy

</details>

### AI与监管：电力、责任与经济模式

**Tracy Alloway**: 实际上，Burn，这让我想起，我们经常听到关于 **AI** 的一件事是电力作为限制因素。每个人都说那是最大的限制。当你自己考虑技术的采用及其在美国乃至全球的传播时，你对数据中心和电力消耗的考虑有多少？

<details>
<summary>Original English</summary>

**Tracy Alloway**: actually burn that reminds me one of the things we hear a lot when it comes to AI is this idea of electricity as a limiting factor right everyone talks about how that's the big constraint when you yourself think about adoption of the technology and its spread across America and I guess around the world how much are you actually thinking about things like data centers and electricity consumption.

</details>

**Burn Hobart**: 嗯，我现在较少考虑这些，因为供应链中的每个人都已预订了很远的未来产能，而且新供应的弹性很小。我不会完全惊讶地看到 **AI** 公司只是保证他们会在 2032 年或以后从 **Seamus Energy** 或 **G** 公司接收货物，这样他们就可以开始新的制造产能。但我认为，由于这是一个滞后很长的过程，它在某种程度上是既定的。我认为实际的限制更多地在于内部组织方面，你是否真的有一个组织结构图，如果你到处都有 **AI**，它总是将信息路由给需要它的人。比如你是否可以只有一个人是 CEO，而其他所有人都是个体贡献者，并且你 **AI** 化了所有中层管理？可能不会，因为你，另一个限制因素是责任。你确实希望有人类在循环中。你知道，我之前开玩笑说过，但这是真的，现在处于理想位置的人是那些从事受监管工作的人，那里有某种行业协会限制新进入者进入该工作，但对他们提供的服务有过剩的需求，并且 **AI** 可以提高他们的每小时产出。这些人将赚大钱，而且只要他们能限制供应流入，他们就会继续这样做。所以我们最终可能会得到一个更像行会化的经济，我们对谁有权力做一些事情进行了限制，不是谁可以做这份工作，而是谁可以真正地盖章说我对此负责，如果出了问题你可以起诉我，因为这实际上是非常有价值的事情，而且你仍然不能真正起诉一个数据中心。你可以尝试起诉 **OpenAI**，但他们可能请得起比你更好的律师。你实际上，起诉我因为 **ChatGPT** 告诉我做了一些我没有通过询问 cla code 再次检查的事情，这在经济上可能更有效。所以我们会觉得，想到我们作为有血有肉的人类，我们的经济目的之一是成为一个容易被起诉的目标，这很奇怪，但它实际上是我们能做的一些经济上有价值的事情，而且因为我们都有不同的风险偏好和风险承受能力。这实际上意味着我们会看到 **AI** 的部署不均衡，会有人只是证明你可以走得太远，而且如果你决定成为一个为上千人报税的 **CPA**，你很可能是第一个专门因为 **LLM** 告诉你做的事情而入狱的 **CPA**，如果还没有发生的话。但我认为，这种模型，你希望有人类在循环中，因为我们经济和社会中的许多结构都假定有一个人，这可能还会继续存在。

<details>
<summary>Original English</summary>

**Burn Hobart**: Well, I'm thinking less about those right now just because everyone who is in that supply chain has all of their capacity booked out so far in the future and like new supply is pretty inelastic. Like I wouldn't be entirely surprised to see the AI companies just guaranteeing that they will take delivery on, you know, something from Seamus Energy or G um in, you know, the year 2032 or whatever just so that they break ground on new manufacturing capacity. But I kind of view that because it's such a long lag thing, it's kind of a given. I think that the actual constraints are more on the um internal like organization side just you know do you even have an org chart if you have AI everywhere that's always routing messages to whoever needs them. Like could you just have there's one person who's the CEO and everyone else is an individual contributor and you AIify all middle management? Probably not because what you act the other limiting factor is just liability that you do want a human in the loop. You know, I was joking about this earlier, but it is true like the person who's in an ideal position right now is someone who is in a regulated job where there is some kind of trade association that limits new entrance into that job, but there's excess demand for the services they provide and AI can increase their output per hour. Like these people will be minting money and um they will continue to do so as long as they can limit supply inflows. And so what we might end up with is a more kind of guildified economy where we have limits on who specifically not who can do the job but who can actually you know stamp it and say I'm taking credit for this and you can sue me if it goes wrong because that's actually a really valuable thing and it's still like you can't really sue a data center. You you know you can try to sue open AI but they can probably afford better lawyers than you. You actually it's probably more economically efficient to sue me for something chatpt told me to do that I didn't double check by asking Claude. And so we'll like it is weird to think that one of our economic purposes as as you know living in sold human beings is to be an easy target for a lawsuit but it is actually something economically valuable that we can do and because we all have different risk preferences and risk tolerances for things. It actually means that we would get this sort of uneven deployment of AI where there would be people who just demonstrate that you can go way too far and that you know if you decide that you're going to be the CPA who does taxes for you know does a thousand 1040s a day you're probably the first CPA to go to prison specifically for something that an LLM told you to do if that hasn't happened yet. But I think that that that kind of model where you want a human in the loop because so many structures that we have economically and socially just assume there's a person that will probably stick around.

</details>

**Tracy Alloway**: 你写了很多关于金融和技术的内容，我一直在思考 **AI** 在金融领域的未来。其中一个问题是，我们和 **PNC Bank** 的 **CEO** 做了一期非常棒的节目。我们当时谈论了一些关于 **AI** 和贷款的事情，他说如果你拒绝给某人贷款，你必须有理由。有一些法律，比如反歧视法之类的。所以如果某人被拒绝信用，你必须能够解释原因。**AI** 的一个特点是它可以做出非常好的决策，但很难解释，而且 **AI** 通常无法解释它是如何得出结论的。我很好奇，从金融行业来看，你认为这将在多大程度上限制 **AI** 颠覆这个行业？很多事情都需要用英语来表达，基本上。

<details>
<summary>Original English</summary>

**Tracy Alloway**: You write a lot about finance as well as technology and I've been thinking a lot about the future of finance in AI. One of the things that comes up is we did a really good episode with the uh CEO of PNC Bank. We were talking a little bit about AI and lending and he said um you know if you deny a loan to someone you have to have a reason for it. There are various laws that you know anti-discrimination laws and stuff. So if someone is denied credit you have to be able to explain why. One of the things with AI is that it can make very good decisions but it's hard to interpret and the AI often can't explain how it arrived at a conclusion. And I'm curious like from a fi just thinking about the finance industry, how much do you think that's going to be a limiting constraint on the degree to which AI disrupts the industry? The fact that a lot of things need to be articulable in English basically.

</details>

**Burn Hobart**: 嗯，我认为 **AI** 像人类一样，不善于知道它为什么会做某事，但非常善于解释它所做的一切都是正确的。所以它可能，我的意思是，我不是 **PNC** 的负责人，所以我不确定，但我想象它实际上让找出一些非常可靠的合理化理由变得更容易。它们非常擅长合理化。所以我对此不会那么担心。我实际上认为拥有更开放、更容易理解的推理方式很好，你可以实际阅读推理痕迹。我认为它对金融业的影响之一是，那些提出建议的人，比如发放这笔贷款，不发放那笔贷款。拥有更多详细的完整思考过程记录会很有意义。所以你可能会让他们在 **DataBricks Notebooks** 或类似的东西中工作。这样你就可以看到，他们首先提出了这个问题，然后他们深入研究了这个难题，然后他们决定这不相关，然后他们又转向了这个问题，然后他们花了一些时间研究它，等等。因为如果你只有问题和某人想出并编辑过的完善答案，你就会错过很多中间层，所以很难训练一个能够追踪并重现这种过程的模型。现在，如果你有一个足够智能的模型，它基本上会隐式地重现所有这些推理。但这确实意味着当推理非常巧妙而那个人没有展示他们的工作时，它会做得更差。而很多聪明的人只是想出了事情，然后他们就已经对这个问题感到厌倦了。所以他们不想告诉你他们是怎么做的，然后他们转向下一件事。

<details>
<summary>Original English</summary>

**Burn Hobart**: Well, I think AI like humans is bad at knowing why it actually did things and really really good at explaining why whatever it did was the right thing to do. So it probably I mean I'm not the head of PNC so I don't know for sure but I I would imagine it actually makes it easier to just come up with some very solid sounding rationalization for anything like they're they're just really good at rationalizing. So I would be less concerned with that. Like I actually think it's nice to have more open accessible kind of reasoning like you can actually read the reasoning traces. And one of the effects I think it has on finance is that people who are coming up with recommendations like make this loan, don't make that loan. It will make a lot of sense to have much more detailed records of their entire thought process. So you might have them, you know, working in data bricks notebooks or something equivalent to that specifically. So you could see, okay, first they asked this question and then they went down this rabbit hole, then they decided it's irrelevant and then they went to this question and then they spent some time on it, etc. Because you if you have just here's the question and here's the polished answer someone came up with and edited, you're missing a lot of the intermediate layers and so it's hard to train a model that can trace through that and reproduce it. Now, if you have a smart enough model, it's basically implicitly reproducing all of that reasoning on its own. But that means that it does worse when the reasoning is really really clever and the person didn't show their work. And a lot of clever people just figure things out and then they're already bored with the problem. So they don't want to tell you how they did it and they move on to the next thing.

</details>

**Joe Weisenthal**: 我最近确实有一个家庭 **DIY** 项目，我问 **ChatGPT** 怎么做，它基本上让我去反抗重力。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: I did have like a home DIY project recently and I was asking Chad GPT how to do it and it basically told me to defy gravity

</details>

**Burn Hobart**: 而且无法解释它为什么要这么做。我稍后会告诉你更多，因为它是一个很长的故事。总之，如果我们能稍微进行一些政治民意调查的内省，David，当我想到 **AI** 和你所做的一些工作时，我认为它对你非常有帮助，因为你可以为民众识别出更细致的问题。你可以提出更好的民意调查问题，但我认为所有人都会接触到基本相同的技术。因此，最糟糕的结果可能会实现，那就是我们只会得到更多的身份政治和文化不满政治。你认为这会如何发展？政治竞选会因为 **AI** 变得更智能，还是我们只会更深地陷入文化政治？

<details>
<summary>Original English</summary>

**Burn Hobart**: and could not explain why it had to arrive to do that. I'll tell you more about it later because it's a long story. Anyway, if we could do a little bit of like political polling, naval gazing for a second, David, when I think about AI and some of what you do, I think it could be very helpful to you because you can identify even more granular issues for the population. You can come up with like even better polling questions, but then I think that everyone's going to have access to basically the same technology. And so the worst case outcome is probably going to come to fruition, which is we're just going to get more identity and sort of cultural grievance politics. How do you see that going? Like does political campaigning get smarter with AI or do we just kind of descend more into culture politics?

</details>

### AI、政治两极化与公共政策

**David Shore**: 嗯，显然很难预测未来，我想我今天已经说过了，但很容易想象会发生非常糟糕的事情。深伪技术，无法追踪什么是真什么是假。现在很多人能够制作出有说服力的内容，主张以前不在领域内的事情。但是，我认为在这次讨论中，人们有点低估了现状有多么功能失调。例如，如果你看看社交媒体，大约 5% 的公众负责大部分的社交媒体内容。这很疯狂。我认为现在因为内容制作成本高昂，如果你是一个政治影响者或作家，你的经济动机确实是关注那 5% 的公众，他们消费的政治内容比其他人多得多，而现在政治领域基本上没有人制作专注于不那么关心政治的普通人的内容。举个例子，我认识的一个人有一个 **TikTok** 用户小组，他录制了他们的手机，大约有 200 人，他付钱让他们这样做，他可以看到谁在看什么。在 **Charlie Kirk** 被枪击后，有一个人负责大部分的 **Charlie Kirk** 视频。就在那天，他一直在刷屏观看数百个 **Charlie Kirk** 暗杀视频。如果你是一个内容生产者，这正是你目前的激励。所以我的观点是，现状确实非常糟糕。而且我认为，如果你看看这些人是谁，他们往往非常焦虑。他们往往非常神经质。现在，注意力游戏确实让你倾向于更负面，而像“你如何真正改变一个人的想法”这样的说服游戏则让你走向完全相反的方向。你知道，我每次做民意调查，每次做测试，通常都说你应该更积极。你应该更多地关注影响人们生活的普通事情。而你知道，这没有发生的原因是实际内容创作者的激励。所以我可以看到，降低内容制作成本，以及扩大谁能够制作内容。这可能是好事，但也，你知道，清楚地说，它也可能很糟糕。我们只是进入了一个完全不同的世界，很难预测任何事情。奇怪的是，政治、 discurso 和思想似乎真的与影响人们日常生活的任何事物脱节。我的意思是，这以前也被提出来过。为什么没有政治家真正把“摆脱垃圾短信”这样的事情作为一个大问题呢？我们都觉得它非常烦人，但你不会，这几乎是不可想象的。

<details>
<summary>Original English</summary>

**David Shore**: Well, obviously it's very hard to make predictions about the future, which I guess I've said already today, but it's easy to imagine really bad things happening. deep fakes, the inability to track what's true and what's not. You know, the ability now of lots of people to make content that's persuasive, that argues for things that previously weren't within the domain. But, you know, I do think in this discussion, people kind of underestimate how dysfunctional the status quo is where if you look at social media, for example, something like 5% of the public is responsible for a majority of social media content. Uh, which is crazy. uh you know and I I think that right now because content is expensive to produce you know if you are a influencer or a writer about politics your economic incentives are really to focus on the 5% of the public that is consuming way way more political content than everyone else and really basically no one in the political spectrum right now is making content focused on regular people who don't care that much about politics. You know, just to give an example, someone I know had a a panel of Tik Tok users where he, you know, recorded their phones and it was like 200 people and he was paying them to do that and he could see who was watching what. And after Charlie Kirk got shot, there was one person who was responsible for a majority of the Charlie Kirk videos. Just that day, he was like really swiping and watching hundreds of Charlie Kirk assassination videos. And you know, if you are a content producer, that is currently your incentive. And so my point is really the status quo is really quite bad. And I think that if you look at who these people are, um they tend to be quite anxious. They they tend to be quite neurotic. Like right now the attention game really pushes you toward being more negative while the persuasion game of like how do you actually get someone to change their mind really pushes you in the opposite direction. You know, every time I've done a poll, every time I've done a test, it's generally said you should be more positive. You should focus more on regular things that affect people's lives. And you know the reason why that doesn't happen are the incentives of the actual content creators. And so I could see you know lowering the costs of producing content uh and kind of broadening out who is a able to make content. It could be good but also uh you know to be clear there's a lot of ways it could be bad. Um we're just entering I think a totally different world where it's hard to predict anything. It is weird how much like politics, discourse, and ideas truly seem disconnected from anything that affects people, many people on a day-to-day life. I mean, this has been brought up before. Why has no politician really made a big issue about like getting rid of like spam texts or something like we all find it incredibly annoying and yet you wouldn't it's almost unimaginable.

</details>

**Joe Weisenthal**: 我敢肯定你能找到一些关于垃圾短信的单一议题选民。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: I'm sure you could find some oneisssue voters on spam text,

</details>

**Tracy Alloway**: 没错？但是，如果有人真的认真对待这件事，认为它困扰着所有人，并且努力推动，那会很棒。然而它没有发生，是吗？

<details>
<summary>Original English</summary>

**Tracy Alloway**: right? But like that would be great if someone actually like let's take this seriously as a thing that annoys everybody and let's try to make a push. And yet it doesn't happen, does it?

</details>

**David Shore**: 是的。我非常喜欢这个统计数据，如果你问人们你最关心什么问题，答案是生活成本，而且优势巨大。但另一方面，如果你看看在过去一年中向民主党竞选活动捐款的人口中 0.7% 的人，那么生活成本就会从第一位下降到第五位，而气候变化则排在首位。所以我想，如果你看看，我认为现状是，政治家现在所谈论的，更多地取决于他们的捐助者关心什么，而不是公众关心什么。我认为这确实很糟糕。我认为我们目前政治功能失调的巨大根源在于，两边的人都没有足够倾听普通人关心什么。你们俩有没有对那些在 **AI** 调整过程中（我不想说是 **AI** 厄运场景，因为我知道你们对此意见不一，而是痛苦的 **AI** 调整过程）真正具有政治可行性的政策有何看法？

<details>
<summary>Original English</summary>

**David Shore**: Yeah. The stat I really like on this is if you ask people what issue do you care about the most, it's cost of living by an enormous margin. Um but the flip side is that if you look at the 0.7% of the population that has donated to a Democratic campaign in the last year, then cost of living goes from number one to like number five and like climate change is on top. And so I think, you know, if you look at like I think the status quo is that politicians right now, if you look at what they talk about, it's much more explained by what their donors care about than uh you know, what the public cares about. Um and that's really pretty pretty bad. I think a lot an enormous source of our political dysfunction right now is really that people on both sides aren't listening enough to what regular people care about. Do either of you have a good read on the policies you would expect to be actually politically viable if we do start to get I'm not going to say an AI doom case scenario because I know you disagree on that but a painful AI adjustment process.

</details>

**David Shore**: 我认为公众在这个问题上比人们想象的要激进得多。我个人通常不是那种会说“人们渴望激进的政策变革”的人。但我们现在确实处于一个非常激进的时代。如果你问选民，你是否支持价格管制，答案是 2:1 的支持，这在 5 年前是闻所未闻的。你知道，当我们进行测试时，我们有一个非常激进的测试，我们说“哦，我们将保证你的收入高达 15 万美元。我们将确保你有一份工作。我们将确保你不会被驱逐。”它的测试结果比民主党专业人士制作的 98% 的片段都要好。这个具体的政策，我认为相当激进，在 **Trump** 选民中获得了约 30% 的支持率和 15% 的净支持率。所以我想说的是，现在每个人都在讨论时间线和政策细节。而你知道，公众所处的激进程度远超政治家或评论员。所以，我认为这是我将要说的最重要的事情，我认为这是被低估最多的问题。最好的测试主题，比民粹主义更好，比 **AI** 更好的是 **AI** 民粹主义。而且我认为，我认为这就是事情发展的方向。

<details>
<summary>Original English</summary>

**David Shore**: I think that the public is much more radical on this issue than people think. Me personally, I'm not usually the person who goes out and says, "Ah, the people crave radical policy change." But we really are in a very radical time right now. If you ask voters, you know, do you support price controls, uh, the answer is yes by 2:1, which is not something that was true 5 years ago. You know, when we've done tests, you know, we had one test where we had a really quite radical thing where we're like, oh, we're going to guarantee your income up to $150,000. We're going to make sure that you have a job. We're going to make sure that you uh won't be evicted. and it tested better than like 98% of the clips that were made that were made by Democratic professionals. That specific policy, which I think is quite radical, I think is something like plus 30 and plus 15 among Trump voters. And so that's that's just the thing I want to say is, you know, right now everyone has this discussion about timelines and and policy specifics. And you know, the public is in a much more radical place than politicians or commentators are. So that's I think the big thing I'd say is I think it's the most underpriced issue. Um the very best testing topic better than populism, better than AI is AI populism. And I think I think that's the direction things are going to go.

</details>

### 深伪技术与民主化

**Joe Weisenthal**: Burn，这太不祥了。我想回到你提到的关于深伪技术和媒体上每个人都在为少数真正关心政治的人写作的两个观点。我实际上认为深伪技术在一个特定的意义上是一个积极的发展。

<details>
<summary>Original English</summary>

**Joe Weisenthal**: Burn this is this is ominous. I I did want to return to um two of the points that you you had made on on deep fakes and on how everyone in media is writing for the tiny minority of people who really care about pol or everyone in political media is writing for this tiny minority that cares about politics. And one I I actually I do think deep fakes are a net positive development in the specific sense that

</details>

**Tracy Alloway**: 这太棒了。我们可以就这个问题聊上一个小时。

<details>
<summary>Original English</summary>

**Tracy Alloway**: this is great. We could do a whole hour on this question.

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**Burn Hobart**: 我写这个很久了。我的观点是，总是可以创建一些具有操纵性的媒体剪辑。总是可以说，好吧，在过去的一天里，已经录制了 50 个关于一些令人发指的事件的视频。这是我们选择用来制作新闻报道的一个。这在有足够的资源的情况下一直都是可能的，现在每个人都可以做到。因此，如果你处于可以选择推广哪种叙事的位置，我认为这有点像现代的，就像它实际上是选举人团一样，人们选择观看某些类型的媒体，然后这些媒体会塑造他们的观点，使他们与那种媒体更加相关。所以我们有点在“民主化民主”。我们说任何人都可以制作误导性视频。你不必观看这个人在说话的 20 个小时的录像来找到一个失误。你可以伪造它。而且伪造必须是可信的，例如，如果想要一个能够改变人们看法的可信伪造，它必须与现实相当相似。它不能只是说 **Donald Trump** 实际上是个外星人。它必须是这样的：**Donald Trump** 收到了一名卡塔尔商人的现金贿赂。但如果你只能制作那些实际上有点可信的伪造，那么它们就存在于一个与现实相距不远的空间中。同样，那些热门的病毒视频通常是现实中的一个样本，它们是现实中的一个样本，但它们可以通过全方位的视频报道来放大事件的感知频率。所以这是一个观点，我确实认为它实际上让我们这个文化不太可能通过观看一段模糊不清的、抖动的 12 秒视频来对重要问题做出判断。我认为这很好。我认为我们应该多读书，少看视频。但我也认为，当 **AI** 的另一个方面，目标定位推荐算法，其中有很大一部分 **AI** 支出和 **AI** 影响，可能意味着某人更有可能通过煽动反对垃圾税等事情来谋生。我们确实看到了“点击取消”之类的功能正在推进。所以，你知道，那些小小的生活质量改进，比如“点击取消”，是一个市长会非常自豪的事情，但它必须在联邦层面完成。但也许，如果有可能真正瞄准那些，例如，真的想恢复收费厕所的人群，因为他们认为禁止收费厕所会造成各种反常的经济后果，而这确实会发生。你可以找到那些人，你可以动员他们，你可以让他们，你知道，如果某个众议院选举中有一个非常接近的竞争，而其中一位政治家恰好支持这个特定的问题，他们就可以像加密货币社区的人一样，用金钱轰炸那个恰好也支持他们喜欢的事情的人。所以我们实际上有可能以这种方式进一步实现 **AI** 民主化民主，你可以实际协调那些不太关心政治但仍然关心应该通过政治进程解决问题的人群的利益群体。

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**Burn Hobart**: I've I've been writing about this one for a long time. My view is that it is always possible to create manipulative cuts of some media. It's always possible to say, okay, there have been, you know, 50 videos recorded in the last day of some egregious happening. Here's the one we're choosing to make a new story. That's always been possible with sufficient resources. and now it's possible for everyone. And so to the extent that when you choose what narrative if you're in a position to choose what narrative is promoted, it's I think of it as kind of the modern um it's like it is the deacto electoral college is that people opt into viewing certain kinds of media that will then shape their views to make them more more correlated with that kind of medium. And so what we're kind of doing is democratizing democracy. We're saying anyone can make a misleading video. Like you don't have to watch 20 hours of footage of this person talking to find the one gaff. you can just fake it. And the fake is actually like for the fake to be a plausible, you know, opinion shifting fake. It has to be something fairly similar to reality. It can't just be like Donald Trump is actually an alien. It has to be something like, you know, Donald Trump took a bribe in cash from a Qatari businessman or something like that. But then if you can only make fakes that are actually kind of plausible, then they just exist in this space that is not that far from reality. And similarly the big viral videos they are often a sample from reality like they are a sample from reality but they are something where you can magnify the perceived frequency of an event if there's just wall to-all coverage of that event on video. So that that was one point was I I do think that it actually just makes us a less a culture that is less likely to make up our minds on important issues by watching a you know grainy shaky 12 seconds of footage of something. I think that's good. I think we should read more and watch less. But I also think that when the you know the other piece of AI just the the targeting recommendation algorithms which there's a huge chunk of AI spending and AI's impact that probably does mean that it's potentially more likely that someone could make a career out of something like agitating against spam tax. And we did actually see you know click to cancel is kind of moving along. So you know those little quality of life things like click to cancel is the kind of thing a mayor would be really proud of but it has to be done at more of a federal level. But maybe if it's possible to actually target whatever population niche like really wants to bring back pay toilets because they think that banning paid toilets creates all kinds of perverse economic outcomes which it does. You can find those people, you can mobilize them and you can get them to, you know, if there is like some very close race somewhere in the House race for example and one of the politicians happens to support this particular pet issue, they could be like the crypto people and just money bomb the person who happens to also support the thing that they like. So we could actually have that's another way we could potentially see AI democratizing democracy further is that you can actually coordinate interest groups for people who are just less politics but still actually care about problems that should be solved through the political process.

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**David Shore**: 是的。我只是想很快插一句，因为，你知道，你说 Burn 说这很可怕，而我，我，我想稍微反驳一下。我真的很喜欢 **Ed Glazer** 的一句话，你知道，每个人都希望宏观经济学有微观基础，但微观基础本身应该有微观基础，除非我们能给选民一些安全感，否则我们不会体验到任何潜在的生产力收益，或者只会体验到一小部分生产力收益。公众确实在大声疾呼，他们想要经济安全，他们希望能够展望未来 5 年而没有恐惧。如果你能提供一个新的社会契约，如果你能真正提供高水平的经济安全，那么你就可以真正拥有所有这些像部门特定的转变，以获得更高的生产力。但是，如果政治家不提出这样的愿景，那么我们只会陷入一系列拜占庭式的部门特定，你知道，法规和行会，我认为你也不想要。所以我想，你知道，自由主义者真的应该选择，你知道，他们想要什么样的世界。你知道，我们要么可以有一个大规模的解决方案，保护人们的收入，防止他们成为失败者，要么我们只能在每个行业同时进行一场巨大的负和博弈。而且我还要说，你知道，我们现在的情况并不理想，你知道，对于后一种情况而言。所以，我认为情况真的可能会变得相当糟糕。

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**David Shore**: Yeah. I just wanted to jump in quickly you know because uh you know you said that Bren said that this is ominous and you know I I want to push back on that a little bit. There's an Ed Glazer quote that I really like which is you know everyone wants macroeconomics to have micro foundations but micro foundations itself should be microfounded that we are not going to experience any of the potential productivity gains or or only experience a fraction of the productivity gains unless we can give voters some sense of security. that public is really crying out that they want economic security and that they want to be able to look out at the next 5 years without fear. And if you can provide a new social contract, if you can actually provide economic security at a high level, then you can actually have all of these like sector specific shifts to have higher productivity. But if politicians don't advance a vision like that, then we're just going to collapse into a Byzantine series of sector specific, you know, regulations and guilds, which I think you don't want either. And so I think, you know, the libertarians should really choose, you know, uh what world they want. you know, either we can have a largecale solution that protects people's incomes and prevents them from being losers, or we can just kind of have this giant negative some fight playing out in every single sector simultaneously. And I'll also say, you know, we're not really in the ideal political circumstances, you know, for that latter thing to to happen. And so, I think it really could get quite ugly.

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**Joe Weisenthal**: David 和 Burn，非常感谢。这是一次引人入胜的对话。我们真的需要再花一个小时来讨论深伪技术正在做什么。但是，非常感谢大家的加入，祝大家今天愉快。

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**Joe Weisenthal**: David and Burn, thank you so much. That was a fascinating chat. We really are going to have to do another hour on what deep fakes are doing. But, uh, thank you all for joining and, uh, have a great rest of your day.

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**Tracy Alloway**: 那是我们在奥斯汀 **South by Southwest** 现场录制的与 **David Shore** 和 **Burn Hobart** 的对话。我是 **Tracy Alloway**。你可以在 **Tracy Alloway** 关注我。

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**Tracy Alloway**: That was our conversation with David Shore and Burn Hobart recorded live at South by Southwest in Austin. I'm Tracy Aloway. You can follow me at Tracy Aloway.

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**Joe Weisenthal**: 我是 **Joe Weisenthal**。你可以在 **the stalwart** 关注我。关注我们的嘉宾 **Burn Hobart**，他在 **Burn Hobart**；**David Shore** 在 **David Shore**。关注我们的制作人 **Carmen Rodriguez** 在 **Carmen Arman Dash Bennett** 在 **Dashbot** 和 **Kalebrooks** 在 **Kalebrooks**。更多 **OddLots** 内容，请访问 **bloomberg.com/odlots**。

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<summary>Original English</summary>

**Joe Weisenthal**: And I'm Joe Weisenthal. You can follow me at the stalwart. Follow our guest Burn Hobart. He's at Burn Hobart and David Shore at David Shore. Follow our producers Carmen Rodriguez at Carmen Arman Dash Bennett at Dashbot and Kalebrooks at Kalebrooks. And for more OddLots content, go to bloomberg.com/odlots.

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**Joe Weisenthal**: 我们有每日简报和所有节目。你可以在我们的 **Discord** 上 24 小时 7 天讨论所有这些话题，**discord.gg/odlots**。

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<summary>Original English</summary>

**Joe Weisenthal**: We have a daily newsletter and all of our episodes. And you can chat about all these topics 247 in our Discord, discord.gg/odlots.

</details>

**Joe Weisenthal**: 如果你喜欢 **Odd Thoughts**，如果你喜欢我们录制这些现场节目，那么请在你最喜欢的播客平台上给我们一个好评。请记住，如果你是 **Bloomberg** 订阅者，你可以完全免费收听我们所有的节目。你只需要在 **Apple Podcast** 上找到 **Bloomberg** 频道并按照那里的说明操作。感谢收听。

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<summary>Original English</summary>

**Joe Weisenthal**: And if you enjoy Odd Thoughts, if you like it when we record these live episodes, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely adree. All you need to do is find the Bloomberg channel on Apple Podcast and follow the instructions there. Thanks for listening.

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**Joe Weisenthal**: 是的。

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**Joe Weisenthal**: Yeah.

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