11.05.23: Regulatory Capture

November 5, 2023

本周的主题是 Regulatory Capture 监管捕获。

前微软高管、Windows 业务的掌舵人 Steven Sinofsky 本周发表了一篇长文 Regulating AI by Executive Order Is the Real AI Risk，针对 Biden 总统发布的行政命令 Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence 进行了批评。关于这个行政命令的 AI 摘要：

该行政命令由乔·拜登总统于 2023 年 10 月 30 日发布。^[1]
该命令旨在建立人工智能安全的新标准。它强调需要对人工智能系统进行稳健和标准化的评估，以确保其安全性和可靠性。 ^[2]
该命令还优先考虑保护美国人的隐私，并寻求促进人工智能开发和部署的公平和公民权利。 ^[2-1]
包括国土安全部 (DHS) 在内的多个机构和部门负责领导和执行该命令的规定。 ^[3]

在这项行政命令发布 3 天后，英国科技部长在 AI Safety Summit 上发布了一项由 28 个国家联署的政策（policy paper），肯定了人工智能的潜力，同时呼吁加强对下一代大型语言模型的审查。

Sinofsky 的评论文章被广泛引用，他一向善于调动计算机软件发展历史中大小案例来借古喻今。对于政府对 AI 的担忧和监管，他这样写道：

Imagine where we would be if at the dawn of the microprocessor someone was deeply worried about what would happen if “electronic calculators” were capable of doing math faster than even the best humans. If that would eliminate the jobs of all math people. If the enemy were capable of doing math faster than we could. Or if the unequal distribution of super-fast math skills had an impact on the climate or job market. And the result of that was a new regulation that set limits for how fast a microprocessor could be clocked or how large a number it could compute?

想象一下，如果在微处理器诞生之初，有人深深担心如果「电子计算器」能够比最优秀的人类更快地进行数学计算，将会发生什么。如果这会消除所有数学人员的工作。如果敌人能够比我们更快地进行数学计算。或者超快速数学技能的不平等分配是否对气候或就业市场产生了影响。其结果是出台了一项新规定，对微处理器的时钟速度或计算量设置了限制？

这样的限定是不是很可笑呢？另一个例子：

What if at the dawn of the internet the concern over having computers connected to each other and becoming an all-knowing communications network resulted in regulations that set limits on packet size and speed, or the number of computers that could be connected to the network or to each other?

如果在互联网诞生之初，出于对计算机相互连接并成为无所不知的通信网络的担忧，导致制定了对数据包大小和速度、或者可以连接到网络或互相连接的计算机数量进行限制的法规，会怎样？

我们无法想象，这样的限制会让今天的人类社会变成什么样子。如我在 2023-10-22 Scale Business 这期 newsletter 的结尾写道的：

连接带来的破坏性价值并不比它们的创造性价值低。

这期发布后，小宇宙的 Kyth 来问我这句话的意思，我开始意识到，或许有点故弄玄虚了。计算能力和连接能力毫无疑问创造了巨大的价值，但它也在替代和重组人类社会的拓扑，一些结构变得更加紧密，也自然会有一些节点被无形的巨大离心力抛出轨道之外。

AI 对就业的影响是一个例子。Steven Sinofsky 写道：

There is an example worth calling out in this regard and that is the pivot of AI from technology to AI as a key tool for reorganizing the workforce. This concern for jobs was also a major concern with the rise of the PC and then the internet. The concerns were rather extreme. Many saw the computer, for example, as putting typists, accountants, bookkeepers, graphics producers, and more out of work immediately. Then along came the word processor and spreadsheet and an immense explosion in the number of employees participating in those tasks with advanced skills. When training was needed the businesses, then private market, then even community colleges stepped in upleveling everyone in the economy. Being able to use a spreadsheet went from a highly coveted resume skill to an assumption in just a couple of years. Those worried that in the near-term AI simply eliminates jobs and so magic software replaces a human should experience self-checkout at a grocery store or see that Amazon Go stores switched to having more humans work in them. To think this won’t happen with marketing professionals or lawyers using AI, at least for some projectable future, is to be making a baseless projection at a time when the President is placing specific constraints on the technology.

Disruption in the labor pool is enormously difficult on specific individuals. History has shown that the needs of industry will quickly move to fill in gaps, entirely out of self-interest. The lack of support or even faith in the free market combined with a view that new tools reduce labor both lack supporting evidence from any past waves of technology. So far technology innovation has proven to be a creator of jobs, not a destroyer of them. It is also a reorganizing force in work that in doing so creates different jobs and importantly new products and services for everyone.

在这方面有一个例子值得一提，那就是人工智能从技术转向人工智能作为重组劳动力的关键工具。这种对就业的担忧也是个人电脑和互联网兴起的一个主要问题。人们的担忧相当极端。例如，许多人认为计算机会让打字员、会计师、簿记员、图形制作人员等立即失业。随后出现了文字处理程序和电子表格，以及参与这些任务的具有高级技能的员工数量激增。当需要培训时，企业、私人市场，甚至社区大学都会介入，以提升经济中每个人的水平。在短短几年内，能够使用电子表格就从一项令人垂涎的简历技能变成了一项假设。那些担心在短期内人工智能会消除工作岗位、神奇软件会取代人类的人应该在杂货店体验自助结账，或者看到 Amazon Go 商店转向让更多人在里面工作。认为使用人工智能的营销专业人士或律师不会发生这种情况，至少在某些可预测的未来，是在总统对技术施加具体限制的时候做出毫无根据的预测。

劳动力资源的破坏对于特定个人来说是极其困难的。历史表明，工业的需求将迅速填补空白，完全出于自身利益。对自由市场缺乏支持甚至信心，加上新工具减少劳动力的观点，都缺乏过去任何技术浪潮的支持证据。到目前为止，技术创新已被证明是就业机会的创造者，而不是就业机会的破坏者。它也是工作中的一股重组力量，从而为每个人创造不同的就业机会，更重要的是创造新的产品和服务。

虚假信息是另外一个例子。

周五晚上回家的路上，我听完了「声东击西」播客的最新一集：从「纽约时报」的失误说起：巴以冲突报道为何迷雾重重。事情的起因是：

《纽约时报》因其对加沙医院爆炸事件的报道而面临争议。这起爆炸事件发生在 10 月 17 日，有关责任方的说法相互矛盾。哈马斯政府官员声称这是由以色列空袭造成的，而以色列否认对此负责，称袭击描述与他们的行动不符。《纽约时报》刊登了爆炸消息，最初的报道主要是哈马斯的指控。然而，该报随后针对该报道发表了一份编者按。围绕报道的争论凸显了在冲突地区进行报道的挑战以及在突发新闻情况下对准确信息的需求。^[4] ^[5] ^[6]

在一个多小时的对谈中，几位嘉宾主要围绕事实、新闻报道和社交媒体的中心议题提供了大量的观点，但最终谁也无法回答的问题是：在变得更加紧密连接之后，人类社会似乎变得更加疏远了，事实变得更加模糊了，对话的基础更加脆弱了。

很难说，对于 AI 安全的监管动机是否来自于这些已经发生了的后果。一种观点认为，互联网发展之所以如此迅速，与松散的监管高度相关。Ben Thompson 在 Attenuating Innovation 中写道：

自「互联网诞生」以来，科技公司创造的财富大幅增长与消费者福利的更大增长之间的关系实际上可能与以下事实有关：还没有任何重大法规（最重要的法规第 230 条保护互联网免受诉讼；这项立法带来了诉讼）。我并不是说缺乏监管是因果关系，但我非常怀疑如果加强监管，我们是否会实现更大的增长。

监管来得太晚，科技公司增长得太快，造成了我们所不得不面对的世界。而，这就是故事的全部吗？一个相关的概念是 regulatory capture：

Regulatory capture, also known as agency capture or client politics, refers to a form of corruption where a political entity, policymaker, or regulator is influenced or controlled by a particular special interest group to serve their commercial, ideological, or political interests. This phenomenon occurs when the interests of a minor constituency, such as a specific industry or profession, take precedence over the broader public interest. Regulatory capture can result in negative consequences for society as a whole. It is closely related to concepts such as rent-seeking and political failure. ^[7]

监管捕获，也称为机构捕获或客户政治，是指政治实体、政策制定者或监管者受到特定特殊利益集团影响或控制以服务于其商业、意识形态或政治利益的一种腐败形式。当少数群体（例如特定行业或专业）的利益优先于更广泛的公共利益时，就会出现这种现象。监管捕获可能会给整个社会带来负面后果。它与寻租、政治失败等概念密切相关。

Ben Thompson:

Much attention has been focused on the Executive Order’s ultra-specific limits on model sizes and attributes (you can exceed those limits if you are registered and approved, a game best played by large established companies like the list I just detailed); unfortunately that is only the beginning of the issues with this Executive Order ...

很多注意力都集中在行政命令对模型大小和属性的超具体限制上（如果您注册并获得批准，您可以超出这些限制，这是大型老牌公司最好玩的游戏，就像我刚才详细列出的列表一样）；不幸的是，这只是该行政命令问题的开始......

Steven Sinofsky:

The Order has a few hundred words specifically on privacy. This would come as a surprise to many considering that the biggest issue many see with GPT as implemented today is the absorption of vast amounts of data. The biggest beneficiaries of this have been incumbents who have been amassing data and training models already. Most obviously any changes in privacy will preclude new entrants and harm them more than incumbents. It is now that more substantial laws around data privacy are most needed, laws that apply to the government most decidedly.

If I remain unconvincing that this Order is either the product of incumbent regulatory capture or at the very least enormously beneficial to incumbents, then the last portion of the Order makes it abundantly clear that the regulatory framework that results from those charged with developing it will be the exclusive province of only the largest companies. The Order names 29 executive branch Secretary level (or close) positions that will have oversight or contribute to regulating AI innovation, including an open-ended invitation to add more. As anyone that has worked with new technology companies knows, the efforts that go into simply being able to sell software in the US that meets the basic needs of compliance across merely SOC2, FISMA, and often HIPAA are immense. Few new companies can even cross this threshold. Only the largest existing companies will have the wherewithal to deal with 29 different executive departments. Only the largest existing companies can pick up a phone and call the Deputy Chief of Staff for Policy to begin to deal with the onslaught of regulation and tune it to their capabilities.

该命令有数百字专门讨论隐私问题。考虑到许多人认为当今实施的 GPT 的最大问题是吸收大量数据，这会让许多人感到惊讶。最大的受益者是已经积累数据和培训模型的现有企业。最明显的是，隐私方面的任何变化都会阻止新进入者，并比现有者对他们造成更大的伤害。现在最需要围绕数据隐私制定更实质性的法律，这些法律最明确地适用于政府。

如果我仍然不能相信该命令是现有监管捕获的产物，或者至少对现有者非常有利，那么该命令的最后部分非常清楚地表明，由负责制定该命令的人员所产生的监管框架将成为最大公司的专属省份。该命令指定了 29 个行政部门秘书级（或接近）职位，这些职位将负责监督或有助于监管人工智能创新，包括无限期邀请增加更多职位。任何与新技术公司合作过的人都知道，要在美国销售满足 SOC2、FISMA 和 HIPAA 基本合规性需求的软件，需要付出巨大的努力。很少有新公司能够跨过这个门槛。只有最大的现有公司才有能力与 29 个不同的执行部门打交道。只有最大的现有公司才能拿起电话，致电负责政策的副参谋长，开始应对监管的冲击，并根据自己的能力进行调整。

AI 或许是一个新的技术平台的开端，但它或许不是一个新的产业周期的开端：它来得有点过于突然，以至于上一波大公司（incumbents）都还在自己的青壮年期。它严重的依赖互联网时代所积累的数据、算力、资本和人才。创始人、CEO、律师和政客们刚刚从上一波技术浪潮中完成休整，在面对这项尚在襁褓中的技术革新的时候，准备要充分得多，工具箱里装满了陈词滥调的锤子，等着寻找下一个需要敲打的钉子。

于是，我们可能还是会在舞台上看到同样的几副老面孔，而新的力量还需要更长时间才有机会崭露头角。

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