# Policy on the AI Exponential
- Transcript ID: `1b5061c025e8318a`
- Source tier: `official_authored_text`
- Original language: `en_or_source_language_unlabeled`
- Translation status: `agent_translated_reviewed` (87/87 chunks)
- Original source: https://darioamodei.com/post/policy-on-the-ai-exponential
- Raw evidence: `data/transcripts/web/dario-policy-ai-exponential-2026-06.json`
> 中文是派生翻译，英文是留存的源文本。中文未复核时，以英文和原始音视频为准。
## paragraph 1
**中文**
在《指环王》的一条支线情节中，两名霍比特人试图唤醒树胡——一棵睿智却行动迟缓、拥有知觉的树——让他保卫自己的森林，抵抗一支正在砍伐森林的军队。问题在于，树胡的行动节奏与霍比特人截然不同。他仅仅向另一棵树问好就要花整整一天，因此要让他和同伴足够迅速地采取行动，几乎是不可能的。
**English / Original**
In one of the side plots to The Lord of the Rings, two of the Hobbits attempt to rouse Treebeard—a wise but ponderous sentient tree—to defend his forest from an army that is cutting it down. The problem is that Treebeard operates at a very different speed than the Hobbits. It takes him a full day simply to say hello to another tree, so getting him and his peers to act fast enough is nearly impossible.
## paragraph 2
**中文**
AI 与我们的政治制度相遇，有点像霍比特人与树胡的相遇。AI 正以闪电般的速度进步——短短四年间，AI 模型已经从几乎写不出一行连贯代码，发展到能编写大型 AI 公司大部分代码。在生物学、物理学、数学、金融、法律、翻译及许多其他领域，也取得了类似进展。AI 的缩放定律预测，随着算力增加，通用认知能力将呈指数级提升；如今已有十余年的实证证据支持这些定律。如果缩放定律只需再延续一两年，我们很可能就会获得我所说的“强大 AI”，即“数据中心里的天才之国”。
**English / Original**
The intersection of AI and our political institutions feels a bit like the Hobbits and Treebeard. AI is advancing at a lightning pace—in only four years, AI models have gone from barely being able to write a coherent line of code to writing most of the code at major AI companies. Similar gains have been made in biology, physics, math, finance, law, translation, and many other fields. AI’s scaling laws, which predict an exponential increase in general cognitive capabilities with increasing computing power, now have over a decade of empirical evidence behind them. If these scaling laws continue for only a year or two longer, we are likely to get what I’ve called Powerful AI, or “a country of geniuses in a datacenter”.
## paragraph 3
**中文**
相比之下，政策——尤其是立法——推进得非常缓慢。这往往事出有因：政府掌握着重大的权力，通常不宜过于仓促地动用这些权力。但时间尺度的不匹配仍然非常棘手：在国会可能需要数年才能采取行动的期间，AI 可以从一个有趣的玩具，发展成完整的“天才之国”。
**English / Original**
By contrast, policy—and especially legislation—moves very slowly. Often this is for good reasons: governments have grave powers, and it’s usually for the best that they aren’t used too hastily. But the mismatch in timescale is nevertheless very painful: in the several years that it can take Congress to act, AI can go from an amusing toy to the full country of geniuses.
## paragraph 4
**中文**
过去几年里，随着 AI 成为一项重要的商业技术，希望以负责任方式应对它的人（包括我们）一直面临两难。我们清楚地看到这条指数曲线将通向何方：我们强烈怀疑，几年之内，AI 将成为少数能够从根本上重塑整个政策版图的技术之一，就像核武器重塑地缘政治、工业革命从根本上重塑所有经济和社会议题一样。但只着眼于 AI 当时能力的人，会觉得它只是一项平凡得多的技术——或许类似最新的消费应用或加密货币。要让大多数政策制定者和公司相信，除了放任自流之外还有其他合理态度，非常困难。公平地说，当时 AI 的颠覆性影响尚未显现，我们也不确切知道它们会以何种形态出现；因此，即使具备行动意愿，也很难设计出正确的政策。
**English / Original**
Over the last few years since AI has become a major commercial technology, those of us who wanted to handle it responsibly have faced a dilemma. We could see clearly where the exponential was going: we strongly suspected that within a few years AI would be one of the rare technologies that fundamentally reshapes the entire policy landscape, in the same way that nuclear weapons reshaped geopolitics and the industrial revolution fundamentally reshaped every economic and social issue. But to those looking only at what AI could do at the time, it looked like a much more mundane technology—similar perhaps to the latest consumer app or cryptocurrency. It was hard to convince most policymakers and companies that anything other than a laissez faire attitude made sense. And to be fair, the fact that AI’s radical effects were not yet present, and that we didn’t know exactly what shape they might take, made it difficult to design the right policies even if there had been the will to act.
## paragraph 5
**中文**
受这种局面的限制，许多安全倡导者（包括 Anthropic）迄今主要推动的是能够保留选择空间、为未来快速反应做准备，或让世界更清楚地了解即将发生什么的政策行动——例如透明度立法、芯片出口管制，以及收集 AI 对劳动力影响的数据。这些措施还不够，但此前似乎也只能做到这些。
**English / Original**
Given the limits imposed by this situation, many safety advocates (including Anthropic) have so far been focused on advocating for policy actions that preserve optionality, tee up a fast reaction in the future, or give the world better insight into what is coming down the pike – things like transparency legislation, export controls on chips, and data collection on AI’s labor effects. These are not enough, but they have felt like all that was possible.
## paragraph 6
**中文**
然而，过去几个月里，AI 惊人的力量及其风险已经变得无可否认。最具代表性的例子或许是 Claude Mythos Preview，以及人们发现前沿模型对网络安全构成了非常现实的风险，可能扰乱金融业、关键基础设施和国家安全。Mythos Preview 打乱了全球网络安全格局。但它更广泛的意义在于，它毫无疑问地证明：AI 模型如今已成为具有全球和国家战略影响的工具。Mythos 级模型带来的网络风险不会是我们必须面对的最后一种风险。我认为，生物风险可能很快接踵而至，严重的 AI 自主性风险或许也已不远¹。
**English / Original**
In the last few months, however, the evidence of AI’s incredible power, as well as its risks, has become undeniable. Perhaps the most emblematic example is Claude Mythos Preview and the discovery that frontier models pose very real risks to cybersecurity, creating the potential for disruption of the financial sector, critical infrastructure, and national security. Mythos Preview scrambled the global cybersecurity landscape. But its broader significance is that it proves beyond doubt that AI models are now tools of global and national strategic consequence. The cyber risks that Mythos-class models present will not be the last that we must face. I believe that biological risks may soon follow, and that serious AI autonomy risks may not be far behind1.
## paragraph 7
**中文**
现在，全球必须共同启动一套缓慢而又摇摇欲坠的政策机制，以应对从此将以惊人速度叠加的风险与机遇。许多政策制定者对采取行动表现出更大的开放态度；看到同行逐渐转向我们过去几年一直倡导的立场，令人鼓舞。这是好事，但我担心，这些初步行动相对于 AI 的迅速进展至少落后了一年。本文试图弥合这一差距：阐明指数曲线目前所处的位置，以及我们为应对当下局势所需采取的集体行动。
**English / Original**
We now, globally and collectively, need to activate a slow and rickety policy apparatus to deal with risks and opportunities that are going to compound surprisingly quickly from here. Many policymakers are showing increased openness to taking action, and it's been encouraging to see our peers come around to the same positions we've been advocating for over the past few years. This is good, but I worry that these early actions are at least a year out of step with AI's rapid progress. This essay is an attempt to close that gap: to lay out where the exponential is now, and the collective action needed to meet the moment.
## paragraph 8
**中文**
我将重点讨论五个在 AI 世界中需要重新构想的长期政策领域：监管与公共安全、宏观经济与税收政策、科学创新、国家与社会之间的权力平衡，以及地缘政治。由于 Anthropic 是一家美国公司，我会主要从美国政策角度讨论，但我的大多数建议也适用于世界其他地区。
**English / Original**
I will focus on five perennial policy areas that need re-imagining in an AI world: regulation and public safety, macroeconomics and tax policy, scientific innovation, the balance of power between state and society, and geopolitics. I will speak primarily in terms of US policy since Anthropic is an American company, but most of my recommendations are also relevant to the rest of the world.
## paragraph 9
**中文**
在发布本文的同时，Anthropic 还将发布一份关于前沿模型测试的立法提案和一套关于岗位替代的政策框架，我们打算为后者提供大量资金支持。未来我们计划做得更多，但我们把这些视为表明严肃态度的第一步。
**English / Original**
Along with this essay, Anthropic is releasing a legislative proposal on frontier model testing and a policy framework for job displacement, for which we intend to provide substantial financial backing. We plan to do much more in the future, but we view these as first steps to signal our seriousness.
## paragraph 10
**中文**
1. 监管与公共安全
**English / Original**
1. Regulation and public safety
## paragraph 11
**中文**
每项新技术或新产品都有有益和有害的用途，因此都会带来创新与安全之间的两难。监管产品可以降低其造成伤害的可能性，并在改善全球民众生活方面发挥了重要作用；但监管也可能直接削弱产品的益处，并间接抑制创新。还有一种哈耶克式观点：监管者往往缺少就复杂经济权衡作出正确决定所需的信息，因此监管经常既无效又造成负担。与之相关的是“科林格里奇困境”：一项技术的影响往往难以预见，等到能够看清时，通常已经太迟，难以轻松管控。
**English / Original**
Every new technology or product has both beneficial and harmful uses, and therefore presents a dilemma between innovation and safety. Regulating products makes them less likely to cause harm and has played an important role in improving lives around the world, but it can also directly reduce their benefits and indirectly disincentivize innovation. There is also the Hayekian point that regulators often lack the information needed to make the right decisions about complicated economic tradeoffs, so that regulation is often both ineffective and burdensome. A related idea is the Collingridge dilemma, which states that the impacts of a technology are often hard to anticipate until it is too late to easily manage them.
## paragraph 12
**中文**
这些因素在 2023—2024 年的 AI 领域尤为突出。Anthropic 很清楚，AI 未来可能具备制造足以威胁数百万人生命的生物武器的能力，或出现自主性失当行为；在极端情况下，后者甚至可能威胁人类本身。但风险究竟会以何种形式出现，怎样测试和缓解最有效，以及它们在实践中会如何演变，都不那么明确。因此，预先制定的立法很可能最终不起作用——制造毫无意义或价值很低的合规要求，却遗漏现实风险最关键的来源²。
**English / Original**
These dynamics loomed large for AI in 2023-2024. It was clear to Anthropic that AI might in the future be capable of producing biological weapons that could threaten millions, or autonomous misbehavior that in extreme cases could even threaten humanity itself. Less clear was the exact form in which the risks would appear, how best to test for them and mitigate them, and how they would play out in practice. There was therefore a high risk that legislation written ahead of time would end up being ineffective—creating pointless or low-value compliance requirements while missing the most crucial sources of actual risk2.
## paragraph 13
**中文**
最终，我们得出结论：当时正确的做法是提高透明度。AI 模型开发者应当披露其安全流程及对模型开展的测试，并报告任何重大安全事件，以便公众和科学界更清楚地看到新出现的风险。等到风险变得更确定、形态更清晰时，就可以利用通过透明度获得的证据，设计明智的立法，精准针对最令人担忧的风险。因此，2025 年 Anthropic 支持了透明度立法，协助加利福尼亚州通过 SB 53、纽约州通过 RAISE、伊利诺伊州通过 SB 315（于 2026 年初），并倡导在联邦层面制定透明度标准。
**English / Original**
Ultimately, we concluded that the right approach at that time was transparency. Developers of AI models should have to disclose their safety procedures and the tests that they run on their models and report on any critical safety incidents, so that the public and the scientific community could gain better visibility into risks as they emerge. When and if risks become more definite and their shape is more clear, then the evidence gained through transparency could be used to design smart legislation to precisely target the most concerning risks. Thus, in 2025, Anthropic supported transparency legislation, helping to pass SB 53 in California, RAISE in NY, SB 315 in Illinois (in early 2026), and advocating for a transparency standard at the federal level.
## paragraph 14
**中文**
然而，如今风险已经明确出现。现在应当超越透明度，对 AI 实施更严肃、更具约束力的监管。我认为，至少在指数增长的现阶段，最恰当的类比是汽车、飞机或药品——它们是现代经济不可或缺的强大技术，但如果设计或操作不当，也可能导致大量人员死亡。因此，我认为 AI 监管应当借鉴美国联邦航空管理局（FAA）等机构的模式。前沿 AI 模型应像飞机一样，必须接受技术测试和审计；若达不到严格的安全标准，就应当以威胁公共安全为由阻止或撤回其发布。我很欣慰地看到特朗普政府的行政命令逐步扩大政府在 AI 领域的作用，不过 Anthropic 的提案建议采取更进一步的行动。我们的提案包括以下要素：
**English / Original**
However, now the risks are clearly here. It is time to go beyond transparency to more serious and binding regulation of AI. I believe the best analogy, at least at the current stage of the exponential, is to cars, airplanes, or drugs—powerful technologies essential to the modern economy, but capable of killing large numbers of people if designed or operated poorly. I therefore believe we should model AI regulation on agencies like the Federal Aviation Administration (FAA). Frontier AI models, like airplanes, should be required to go through technical testing and auditing, and their release should be blocked or reversed as a threat to public safety if they do not meet high standards of safety. I am grateful to see the Trump administration’s Executive Order move incrementally towards a greater role for government in AI, though Anthropic’s proposal recommends even further action. Our proposal includes the following elements:
## paragraph 15
**中文**
计算量超过某一门槛的模型，应当由具备资质的第三方强制测试其在四个特定领域的风险水平：网络安全、生物武器、AI 系统失控，以及可能加速上述其他风险的自动化研发。
**English / Original**
Models above a threshold of compute should undergo mandatory testing by a qualified third party for their level of risk in four specific areas: cybersecurity, biological weapons, loss of control of AI systems, and automated R&D that could accelerate these other risks.
## paragraph 16
**中文**
如果第三方评估认定某个模型带来不可接受的风险，政府应有权阻止或遏制其部署。这项权力必须严格限定于上述四类特定风险，并须设有防止政治偏袒或任意决策的保障措施。
**English / Original**
The government should have the power to block or deter deployment of the model if it is determined, in light of third-party assessment, to present unacceptable risks. This power must be scoped to the above four specific risks and there must be protective measures against political favoritism or arbitrary decisions.
## paragraph 17
**中文**
第三方评估可以由政府机构（类似 FAA）完成，也可以由一组经政府授权和检查、依照特定标准评估模型的私营机构完成，即采用“监管市场”的路径。
**English / Original**
Third-party evaluation could be done by a government agency (similar to the FAA) or a set of private organizations that are authorized and inspected by the government to evaluate models according to certain standards (a “regulatory markets” approach).
## paragraph 18
**中文**
开发先进 AI 模型的公司必须采用严格的安全标准来保护模型权重，应定期开展红队测试和渗透测试，并应与政府合作，防御主要威胁行为体。
**English / Original**
AI companies that develop advanced AI models must have strong security standards that protect their model weights, should conduct regular red teaming and penetration testing, and should work with the government to defend against major threat actors.
## paragraph 19
**中文**
四个关键领域发生的安全事件必须及时报告。
**English / Original**
Safety incidents in the four critical areas must be reported promptly.
## paragraph 20
**中文**
或许在相对不远的将来，我们需要采取超越上述措施的行动：届时最强大的 AI 系统不再像飞机或汽车，而更像可用于武器的核材料——它威胁的是人类，而不“只是”公共安全。如果真出现这种情况，我们可能需要比我列出的措施更为强硬的监管³。但正如在 2024 年很难有针对性地制定和实施我如今建议的措施一样，我认为我们不应操之过急。我们应针对今天正在显现的危险设计政策，同时奠定基础，以便随着新危险出现，能够更快地升级应对。
**English / Original**
There may come a time, perhaps relatively soon, when we need to go beyond this, when the most powerful AI systems look less like airplanes or automobiles and more like weaponizable nuclear materials—a threat to humanity rather than “just” a threat to public safety. If that occurs, we may need more aggressive regulatory measures than those I have laid out3. But just as it was difficult in 2024 to target and apply the measures I’m suggesting now, I don’t think we should get ahead of ourselves. We should design policies for the dangers that are emerging today, while laying the foundations to ramp up our response even more quickly as new dangers appear.
## paragraph 21
**中文**
2. 宏观经济与税收政策
**English / Original**
2. Macroeconomics and tax policy
## paragraph 22
**中文**
长期以来，政府一直面临这样的问题：如何在鼓励经济增长的同时，提供重要公共服务，并确保最弱势群体得到照顾。这类争论有一个重要且总体正确的前提：经济增长很脆弱，也很难实现；减少不平等可能带来重要益处，但必须与加税或扩大赤字造成的经济拖累相权衡。
**English / Original**
Governments have long faced the problem of how to encourage economic growth while also providing important public services and ensuring that the least fortunate are taken care of. An important (and generally correct) premise of these debates has been that economic growth is fragile and difficult to achieve—that while reducing inequality might provide important benefits, it has to be traded off against the economic drag of increased taxes or deficits.
## paragraph 23
**中文**
我怀疑，强大 AI 可能会打乱这一假设。如果 AI 获得了远胜人类完成大多数认知任务的能力，那么它通过加速科学、技术和运营效率，理应能带来极其快速且强劲的经济增长。AI 迭代构建更强 AI 的能力，可能进一步大幅加速这种增长。但也正因为同样的原因，相较以往技术，AI 可能成为对人类认知能力更普遍的经济替代品，同时以远快于以往技术的速度改变经济。因此，可以合理认为，AI 对劳动力市场造成的冲击可能远大于以往技术，而且可能更为持久。我们可能会进入一个经济权衡旋钮被卡在“超高速增长、超高度不平等”档位、并且极难调离这一档位的世界。在这样的世界里，关键挑战不再是激励增长，而是设法让所有人共享增长红利。
**English / Original**
I suspect that powerful AI may scramble this assumption. If AI achieves the ability to do most cognitive tasks far better than humans, it stands to reason that it could result in extremely rapid and robust economic growth via the acceleration of science, technology, and operational efficiency. The iterative ability of AI to build even better AI may supercharge that growth even further. But for exactly the same reasons, AI may also act as a more general economic substitute for human cognitive abilities than previous technologies have, while also altering the economy far faster than previous technologies have. Thus, it’s reasonable to think that AI could produce much larger disruptions to the labor market than previous technologies, and, potentially, more enduring disruptions. We risk ending up in a world where the economic tradeoff dial is stuck on the hypergrowth, hyper-inequality setting, and is potentially very hard to unstick from that setting. The key challenge in such a world won’t be incentivizing growth, but finding a way for everyone to share in the benefits.
## paragraph 24
**中文**
在本文讨论的议题中，宏观经济和持久性劳动力替代可以说最受公众关注，也最容易被误解，因此我想把两点说得极其清楚。
**English / Original**
Of the topics discussed in this essay, macroeconomics and enduring labor displacement are arguably the ones that have attracted the most public attention and the most misunderstanding, so I want to be extremely clear on two points.
## paragraph 25
**中文**
第一，持久性岗位替代既不可取又危险；我们应尽一切努力尽量减少或阻止它，而不是促成它。我在访谈和文章中警告岗位替代，是希望政策制定者和私营部门拥有最佳机会去适应和应对，而不是因为我想当“末日预言家”。作为一家公司，Anthropic 始终尽可能与客户合作，寻找富有创意的新用途和新收入来源，使他们能依靠现有员工完成更多工作，而不是只关注成本节约（这通常意味着裁员）。随着 AI 系统进步，我们也不断尝试构想新的交互范式，使人类在与 AI 系统协作时尽可能保持积极、主动的角色。更广泛地说，让全世界尽可能多地尝试 AI 的新用法很有价值，因为社会正是通过这种方式发现新的岗位组合。我确实认为 AI 将带来许多新的经济机会。我曾预测，AI 将使个人能够创建价值十亿美元的公司；现在我们已看到只有寥寥数人的团队打造出营收数亿美元的企业。但与此同时，我们也应承认一种相当现实的可能性：尽管竭尽全力，AI 仍会造成严重且持久的岗位流失——这可能是该技术及其广泛复制人类认知方式的内在属性⁴。
**English / Original**
First, enduring job displacement is undesirable and dangerous, and we should do everything we can to minimize or prevent it, not to bring it about. I have warned about job displacement in interviews and essays because I want both policymakers and the private sector to have the best chance to adapt and respond, not because I am trying to be a “prophet of doom”. As a company, Anthropic always does as much as it can to work with customers to find creative new use cases and new sources of revenue that allow them to do more with their existing workforce, rather than focusing solely on cost savings (which often means reducing the workforce). We also constantly try to think of new interaction paradigms that allow humans to have as active a role as possible in collaborating with AI systems as those systems advance. More broadly, it is valuable for the whole world to experiment with using AI in as many new ways as possible, as that is the way for society to discover new possible job configurations. I do think AI will enable a number of new economic opportunities. I’ve predicted that AI will enable single individuals to create billion-dollar companies, and we're already seeing teams of only a few people build businesses with hundreds of millions in revenue. But at the same time we should recognize that there’s a decent possibility that, despite all our efforts, AI still causes significant enduring job loss—and that this may be an intrinsic property of the technology and the way it broadly replicates human cognition4.
## paragraph 26
**中文**
第二，对 AI 驱动的岗位替代作出任何应对，都需要同时解决两个需求：在经济上保障所有人，以及让人们找到意义、目标和自主性。后者归根结底更重要，它取决于一些深层问题：社会应如何组织、人们应追求什么，以及何谓美好生活。事实上，我非常乐观地认为，即使在 AI 事事都胜过所有人的世界中，人类仍可过着目标深远的生活，并努力创造令人敬畏且美好的事物⁵。但这需要整个社会共同探索，不是政策能够直接解决的。政策最能发挥作用之处，是通过减缓岗位流失并在经济上保障可能受影响的人，为我们争取时间来完成这项探索。
**English / Original**
Second, any response to AI-driven job displacement needs to address both the need to provide for everyone economically, and the need for people to find meaning, purpose, and agency. The latter is ultimately more important, and it depends on deep questions about how society is organized, what people should strive for, and what constitutes the good life. I am actually very optimistic that, even in a world with AI’s that are better than everyone at everything, humans can live lives of deep purpose and strive to build awe-inspiring and beautiful things5. But this is something to be collectively worked out by society as a whole, not something policy can directly address. Policy can be most helpful in buying us time to do that work, by slowing down job loss and providing economically for those likely to be affected.
## paragraph 27
**中文**
本着这一精神，一些可能有帮助的关键政策干预包括：
**English / Original**
In that spirit, some key policy interventions that are likely to be helpful include:
## paragraph 28
**中文**
测量与跟踪。人们很容易认为仅仅收集和分析数据不足以应对如此规模的问题；但如果不能准确测量现实中正在发生什么，我们就不太可能制定出好政策。Anthropic 已经运营了一年半左右的“经济指数”，跟踪人们如何使用 Claude；但政府能够获得我们无法取得的数据类型，因此可以大幅扩充经济统计，更细致地跟踪 AI 造成的岗位替代。
**English / Original**
Measurement and tracking. It’s easy to dismiss mere data collection and analysis as inadequate to the scale of the problem, but we are unlikely to get good policy if we cannot accurately measure what is happening on the ground. Anthropic has been operating an Economic Index of how people use Claude for nearly a year and a half, but governments have access to types of data we do not, and could greatly expand their economic statistics to more carefully track AI job displacement.
## paragraph 29
**中文**
促进就业的激励措施。多种促进就业的政策激励可以帮助减缓或减少岗位替代，包括：在人们不得不接受薪酬较低的工作时给予补偿的工资保险政策⁶；鼓励雇主不裁员的员工留任税收激励；劳动力培训补助；或建设促进雇主与雇员匹配的基础设施，以加快劳动力市场适应。哪些干预最有效，具体取决于 AI 带来何种劳动力替代；但我们应当乐于承担这些政策可能造成的成本和市场低效，尤其因为 AI 带来的生产率提升很可能会抵消这些代价。
**English / Original**
Pro-employment incentives. A wide range of pro-employment policy incentives can help to slow or reduce job displacement, including: wage insurance policies that compensate people when they have to take a lower-paying job6, retention tax incentives to encourage employers not to make layoffs, workforce training grants, or infrastructure to facilitate matching of employers to employees to speed the rate of labor market adaptation. While the particulars of which interventions are best will depend on what kind of labor displacement AI brings, we should readily accept the costs and market inefficiencies that these policies could entail, particularly as they are likely to be offset by AI-driven productivity gains.
## paragraph 30
**中文**
长期宏观经济支持。如果 AI 驱动的劳动力替代最终规模巨大，并永久压低劳动力需求，那么很可能有必要超越单纯的激励计划，为相当一部分劳动力提供长期收入支持。全民基本收入等机制可以通过向相关公司征税或提高资本利得税来筹资。“全民资本账户”则提供了另一种工具。总体而言，快速经济增长应当为共享繁荣创造税基。
**English / Original**
Long-term macroeconomic support. If AI-driven labor displacement ends up being large in magnitude and permanently drives down the demand for labor, it will likely be necessary to go beyond mere incentive programs to long-term income support for a significant fraction of the labor force. Mechanisms such as universal basic income could be financed through taxes on relevant companies or raising the capital gains tax. Universal capital accounts offer another vehicle. Broadly speaking, fast economic growth should create the tax base for shared prosperity.
## paragraph 31
**中文**
还有一种常见的 AI 经济担忧我尚未提及，即数据中心，尤其是它们可能推高能源价格的问题。我的看法是，AI 公司应当付费吸收电价上涨——Anthropic 已经承诺这样做——但我认为，公众对数据中心的敌意在很大程度上是人们对 AI 更广泛经济焦虑的一种象征或宣泄出口。我们必须就这些更广泛的经济问题展开直接的社会对话，并真正拿出令人信服的解决方案；否则，这些焦虑很可能像在数据中心问题上一样，以间接方式显现。
**English / Original**
A common focus of economic concern about AI that I haven’t mentioned has been datacenters and particularly their potential to raise energy prices. My view is that AI companies should pay to absorb rate increases—and Anthropic has already made a pledge to do so—but I see public hostility to datacenters as largely a symbol or outlet for broader economic anxieties about AI. It is important we have a direct societal conversation about these wider economic issues and truly have compelling solutions for them, or else they are likely to manifest indirectly, as they have with datacenters.
## paragraph 32
**中文**
3. 加速 AI 的积极影响
**English / Original**
3. Accelerating AI’s positive impact
## paragraph 33
**中文**
正如我们必须处理 AI 本身的创新与安全之间的平衡，也必须为可能被 AI 加速的技术——例如生物医学、能源或材料科学——处理同样的平衡。不过，AI 本身可能迅速带来我们毫无应对经验的新挑战；而其他被 AI 加速的领域，很可能遇到一种截然不同的问题：监管体系是为较慢的创新速度设计的，没有准备好应对 AI 将带来的新产品和新进展洪流。AI 也可能使这些下游技术更安全、更可预测，从而打破美国食品药品监督管理局（FDA）等监管机构所持的怀疑性假设。
**English / Original**
Just as we must grapple with the balance between innovation and safety for AI itself, we must grapple with the same balance for technologies that are likely to be accelerated by AI, such as biomedicine, energy, or materials science. But while AI itself is likely to present novel challenges that emerge very quickly and that we have no prior experience in handling, other fields accelerated by AI are likely to encounter a very different problem: regulatory systems that were designed for a slower pace of innovation and are not prepared to handle the deluge of new products and advances that AI will bring. AI may also make these downstream technologies safer and more predictable in a way that violates the skeptical assumptions of regulatory agencies like the Food and Drug Administration (FDA).
## paragraph 34
**中文**
因此，对于 AI 的下游应用——与 AI 本身相反——我更担心监管机制拖慢进步（因为它无法应对加快的变化速度），而不是它未能处理重要风险。我们最不希望看到的，是 AI 的风险日益迫近，其益处却被拖延；所以尽快解决这个问题十分重要。
**English / Original**
Thus, for downstream applications of AI—in contrast to AI itself—I am more worried about the regulatory apparatus slowing down progress (because it can’t handle the increased pace of change) than I am about it failing to address important risks. The last thing we want is for the benefits of AI to be slowed while its risks loom large, so it’s important to take action on this problem as soon as possible.
## paragraph 35
**中文**
问题及其解决方案在科学、商业和技术的各个领域会有不同表现，因此我将重点讨论一个具有代表性的领域：生物医学创新。这样做既是因为它很可能带来 AI 最大的人道主义益处，也因为该领域的监管尤其复杂。我们并不确切知道 AI 会如何加速生物医学创新，但它似乎很可能会：
**English / Original**
The problem and its solutions will manifest differently in each area of science, commerce, and technology, so I’ll focus on one illustrative area: biomedical innovation. This is both because it will likely be the source of AI’s biggest humanitarian benefits and because it is an area where regulation is especially complex. We don’t know exactly how AI will accelerate biomedical innovation, but it seems likely to:
## paragraph 36
**中文**
大幅提高新候选药物进入监管流程的速度；
**English / Original**
Greatly increase the rate at which new drug candidates enter the regulatory pipeline;
## paragraph 37
**中文**
通过更好的优化，或许还有对底层生物学更深入的理解，提高新药的效应量并改善其安全性特征；
**English / Original**
Increase the effect sizes and improve the safety profiles of new drugs, because of better optimization and perhaps better understanding of their underlying biology;
## paragraph 38
**中文**
为此前从未得到成功治疗的疾病开发候选药物；
**English / Original**
Develop drug candidates for diseases that have never been successfully treated before;
## paragraph 39
**中文**
迅速创造全新的治疗形式，类似于抗体、多肽和细胞疗法在过去几十年间成为新的治疗类别。
**English / Original**
Rapidly create entire new forms of therapies, similar to how antibodies, peptides, and cell therapies have become new categories of treatment over the last few decades.
## paragraph 40
**中文**
其中一些进展无需结构性改革，自然就会缩短监管时间。效应量更大的药物可以采用规模更小、成本更低的临床试验，并启用加速审批机制。但现行监管体系的设计要求进行高度审查和多阶段测试，其前提是假定候选药物往往无效，而且即便有效，也经常存在严重安全问题。在 FDA 和欧洲药品管理局（EMA），候选药物走完监管流程通常需要 7—8 年，部分原因正是这些悲观假设。如果不改革，AI 只会让这一体系陷入堵塞或超负荷。
**English / Original**
Some of these advances will naturally accelerate regulatory timelines without need for structural change. Drugs with larger effect sizes can lead to smaller, less expensive clinical trials, and activate mechanisms for accelerated approval. But the regulatory system is currently designed to apply a high level of scrutiny and many stages of testing, under the assumption that drug candidates often don’t work and often have serious safety problems even when they do. With both the FDA and the European Medicines Agency (EMA), the typical time for a drug candidate to pass through the regulatory pipeline is 7-8 years, in part due to these pessimistic assumptions. Without reforms, AI will simply jam or overload this system.
## paragraph 41
**中文**
显然，我们不希望改革催生一批江湖骗术式的药物，或引发大范围安全事件。但是，如果 AI 驱动的科学加速真的发生，一些相对简单的改革就能让 FDA、EMA 及类似机构更好地适应这种快速变化。
**English / Original**
Obviously, we don’t want to change things in a way that leads to a crop of snake-oil drugs or widespread safety incidents. But some relatively simple reforms could make the FDA, EMA, and similar agencies more adaptable to a rapid AI-driven scientific acceleration if one were to occur.
## paragraph 42
**中文**
临床流程中许多过去需要昂贵、缓慢实验的步骤，可能很快就能通过 AI 模拟或分析完成。监管机构现在就应考虑制定接受此类方法所需满足的标准。这意味着，一旦这些方法奏效，就能迅速采用，而不必经历一段漫长时期、继续要求开展不必要的测试。可能适用的领域包括：
**English / Original**
Many of the steps in the clinical process that previously required expensive and slow experiments may soon be done via AI simulation or analysis. Regulatory agencies should consider developing standards now for what it would take to accept such methods. This would mean they can be adopted quickly once they work, rather than there being an extended period during which unnecessary tests continue to be required. Areas where this could apply include:
## paragraph 43
**中文**
基于 AI 的药效动力学和药代动力学（PD/PK）建模；
**English / Original**
AI-based pharmacodynamics and pharmacokinetics (PD/PK) modeling;
## paragraph 44
**中文**
预测毒理学，以免需要对多个物种开展动物毒理试验；
**English / Original**
Prediction of toxicology to avoid the need for multiple species animal toxicology;
## paragraph 45
**中文**
更准确地选择剂量，减少试验中采用大范围剂量的需要；
**English / Original**
More accurate dose selection, to reduce to the need for large dose ranges in trials;
## paragraph 46
**中文**
通过分析大型数据集验证生物标志物；
**English / Original**
Biomarker validation via analysis of large datasets;
## paragraph 47
**中文**
在临床试验中采用合成对照组，减少招募更多参与者的需要；
**English / Original**
Synthetic control arms in clinical trials, to reduce the need to recruit more participants;
## paragraph 48
**中文**
开发替代终点（对衰老和神经退行性疾病研究尤其重要）。
**English / Original**
Developing surrogate endpoints (particularly important in aging and neurodegeneration).
## paragraph 49
**中文**
除了这些具体例子，监管机构还应考虑更大胆、更灵活的加速审批机制。如果我对 AI 的预测正确，很快就会出现许多原本始料未及、却效果极佳的干预措施；监管体系应准备好认真对待它们，而不是采取过度怀疑的姿态。
**English / Original**
Beyond these specific examples, agencies should also consider more radical and flexible mechanisms for accelerated approval. If my predictions about AI are correct, there will soon be many instances of interventions that work really well out of the blue, and the regulatory system should be prepared to take them seriously and not adopt a posture of excessive skepticism.
## paragraph 50
**中文**
生物医学加速应当会大幅增加 AI 的益处，但值得指出的是，它也可能有助于降低 AI 风险。改革生物医学审批可能有助于生物防御，而 AI 驱动的生物医学进步也可能改善心理健康，从而对社会产生稳定作用。
**English / Original**
Biomedical acceleration should substantially increase AI’s benefits, but it’s worth noting that it may also help to reduce AI’s risks. Reforming biomedical approvals may help with biodefense, and AI-driven biomedical progress may also improve mental health, which could have a stabilizing effect on society.
## paragraph 51
**中文**
4. 国家与公民自由
**English / Original**
4. The state and civil liberties
## paragraph 52
**中文**
每一种政府体制都必须面对国家权力及其边界问题。国家在保护民众免受内外威胁方面拥有正当、且往往事关存亡的利益。但赋予国家过多权力，是通往暴政之路。现代民主国家大体上成功维持了这种平衡，但即使在最好的时候，这种平衡也并不稳固。要执行这种平衡，需要历经数百年建立起来的大量法律与宪法机制——例如美国宪法第一、第四和第五修正案，《地方保安队法》（Posse Comitatus Act）、《外国情报监视法》（FISA）等等。
**English / Original**
Every system of government has to confront the question of the state’s power and its limits. The state has a legitimate, often existential, interest in protecting its population from internal and external threats. But granting it too much power is the road to tyranny. Modern democracies have largely managed this balance successfully, but it is an uneasy one at the best of times. Enforcing it has required a great deal of legal and constitutional machinery built up over centuries—for example in the United States the First, Fourth, and Fifth amendments, the Posse Comitatus Act, FISA, and so on.
## paragraph 53
**中文**
AI 可能打破这种平衡，同时也大幅提高其中的利害关系。但如果我们迅速反应、正面应对当下局势，就能利用 AI 创造一个自由保障比以往任何时候都更坚实、更持久，抵御威胁的能力也更强的世界。
**English / Original**
AI threatens to upset this balance while also dramatically raising its stakes. But if we react quickly and meet the moment, we can use AI to create a world that has more robust and durable guarantees of liberty and better defense against threats, than we have ever had before.
## paragraph 54
**中文**
强大 AI 若落入不当之手，可能成为专制统治的终极工具，而现有法律和宪法保障尚不足以对抗这一威胁。从根本上说，智能在现实世界中可以带来巨大的权力回报，再加上 AI 迅猛的进步速度，两者共同形成了一场“完美风暴”，可能让各种危险行为体出其不意地夺取权力⁷。
**English / Original**
Powerful AI in the wrong hands could be the ultimate tool of autocracy, and our existing legal and constitutional protections are not fully equipped to counter this threat. Fundamentally, the enormous returns to intelligence in terms of power in the world, combined with the rapid pace of AI’s progress, creates a perfect storm for a surprise seizure of power by a range of dangerous actors7.
## paragraph 55
**中文**
这种危险可能以各种具体技术或运行形式出现，但它们有一个共同点：AI 可能突然赋予行为体巨大权力，同时绕过现有的民主监督机制。今天听来像科幻故事的全自动无人机军队，未来可能服从非法命令，使政府得以单方面巩固权力；受过专业训练的人类更可能反对此类非法指令。以监控为重点的 AI 可以大规模分析广泛可得的信息，并据此推断每位公民生活中最隐秘的细节——这是现行公民自由法律从未设想过的技术能力。所有这些都可能迅速或秘密地发生，因此主动强化民主国家对自由和公民自由的承诺至关重要。
**English / Original**
The danger could take a variety of specific technological or operational forms, but what they all have in common is the idea that AI could suddenly confer enormous power while routing around existing mechanisms of democratic oversight. A fully automated drone army that sounds like science fiction today could, in the future, obey unlawful orders and allow governments to unilaterally entrench their power; professionally-trained humans are more likely to object to such illegal direction. A surveillance-focused AI could analyze widely available information at massive scale and use it to infer the innermost details of every citizen’s life—a technological ability not contemplated by current civil liberties law. All of this could happen very quickly, or in secret, so it is important to proactively fortify democracies’ commitment to freedom and civil liberties.
## paragraph 56
**中文**
我们应当考虑以下一些政策构想：
**English / Original**
The following are some policy ideas we should consider:
## paragraph 57
**中文**
为全自主武器建立可靠的问责规则。应当要求自主武器——尤其是协调或指挥这些武器的任何自主系统——响应宪法和指挥体系的问责机制（例如法院命令、立法，以及对高级人类监督者负责），而不是盲目服从命令。这可以意味着由设计得当的法律审查委员会或司法部门掌握“关闭开关”，也可以意味着从根本上训练系统主动寻找并服从合法监督权威，或者二者兼用。
**English / Original**
Create reliable accountability rules for fully autonomous weapons. Autonomous weapons, and especially any autonomous systems that coordinate or direct them, should be required to respond to mechanisms of constitutional and command accountability (e.g. court orders, legislation, and accountability to senior human overseers) rather than blindly following orders. This could mean that a suitably-designed legal review panel or the judicial branch have their finger on an “off switch”, that the systems themselves are intrinsically trained to seek out and respond to legitimate oversight authority, or both.
## paragraph 58
**中文**
禁止在国内使用全自主武器。为了防御外国对手（例如俄罗斯入侵乌克兰），确有合理理由认为全自主武器具有必要性；但没有理由将其用于对付美国人。军方在国内行动的能力已经受到一些限制，但理想情况下，执法部门也应被禁止使用这些武器。
**English / Original**
Ban the domestic use of fully autonomous weapons. While there is a legitimate case for the necessity of fully autonomous weapons to defend against foreign adversaries (such as Russia invading Ukraine), there is no justification for their use against Americans. The military already has some limits on its ability to operate domestically, but ideally these weapons should be banned in law enforcement as well.
## paragraph 59
**中文**
堵住批量收集／数据经纪商漏洞。根据现行法律，美国人与私营公司（例如互联网服务提供商）共享的数据，可以被购买并用于国内监控和执法中的批量分析。这一隐私保护缺口早在 AI 之前就已存在，但 AI 能让此类数据的大规模分析比过去揭示更多信息、也更有利用价值，因此会大幅提高其中的风险。应当堵住这一漏洞。
**English / Original**
Close the bulk collection / data broker loophole. Under current law, data that Americans share with private companies (such as internet providers) can be purchased and used for bulk analysis in domestic surveillance and law enforcement. This gap in privacy protections predates AI, but AI will raise the stakes considerably by making mass analysis of such data far more revealing and useful than it has been in the past. This loophole should be closed.
## paragraph 60
**中文**
在政府采取不利行动时，公众应享有获得 AI 建议的权利。作为一般原则，任何成为政府不利行动对象的个人或组织（例如面临监管或法律行动），都应能够使用能力至少不逊于政府在该项行动中获准使用之 AI 的系统。这样可避免赋予政府不公平优势、事实上削弱公民的法律权利。可以将其作为《行政程序法》、正当程序保障或第六修正案所确立法律代理权的延伸或解释。
**English / Original**
Public rights to AI advice during adverse government action. As a general principle, it seems important that any person or organization that is the subject of adverse government action (e.g. regulatory or legal action) has access to AI that is at least as capable as whatever the government is allowed to use in that particular action. This would mean not giving the government an unfair advantage, effectively undermining citizens’ legal rights. This could be added as an extension or interpretation of the Administrative Procedure Act, due process protections, or the Sixth Amendment right to legal representation.
## paragraph 61
**中文**
最后值得指出的是，在防范 AI 驱动的夺权时，政府并非唯一需要警惕的实体。历史上有些时期（例如美国的镀金时代，或英国东印度公司时期），公司曾强大到足以俘获国家，或呈现准国家特征。AI 很快将变得如此强大，以至于我担心，无论将它完全托付给政府还是公司都不安全；双方都必须受到制衡。
**English / Original**
Finally, it is worth noting that governments are not the only entities that we should beware of when it comes to AI-driven seizure of power. At various times in history (such as the Gilded Age in the United States or the East India Company in the UK), companies have become powerful enough that they capture the state or adopt quasi-state characteristics. AI will soon become so capable that I worry it cannot safely be fully entrusted to either governments or companies, and there must be checks and balances on each.
## paragraph 62
**中文**
监管是约束公司的一个答案（我的相关构想见第 1 节），但 AI 公司拥有比一般私营实体更充分的权力分立和问责机制也很重要。Anthropic 的“长期公益信托”（一个旨在监督公司恪守使命的独立治理机构）就是此类结构，业界应继续探索更进一步的机制。正确把握平衡——使公司和政府的权力都受到实质制约——至关重要。
**English / Original**
Regulation is one answer on how to rein in companies (and my ideas for that are in Section 1), but it’s also important that AI companies have more separation of power and accountability than is typical for private entities. Anthropic’s Long-Term Benefit Trust (an independent governance body designed to hold the company to its mission) is one such structure, and the industry should continue to explore mechanisms that go further. Getting the balance right—so that both companies and the government have meaningful checks on their powers—is essential.
## paragraph 63
**中文**
5. 确保民主国家保持领先
**English / Original**
5. Securing leadership by democracies
## paragraph 64
**中文**
也许是受互联网和电信领域近期经验影响，人们已经形成一种常见直觉：从地缘政治角度把新技术视为贸易政策工具，目标是“让我们的技术栈扩散到全世界”。但我坚信，AI 是远为深刻的事物，它会重置整个棋盘，未来所有地缘政治战略都必须围绕它来制定——就像核武器一样，甚至可能影响更大。
**English / Original**
It has become a common instinct, perhaps developed from recent experience with the internet and telecommunications, to regard new technologies geopolitically as instruments of trade policy, with the aim being to “diffuse our technology stack around the world”. But it is my very strong belief that AI is something much more profound, something that resets the whole game board and around which all future geopolitical strategy must be shaped—like nuclear weapons, but potentially even more so.
## paragraph 65
**中文**
如果 AI 真的很快就会成为“数据中心里的天才之国”，或者哪怕只是接近这种状态，那么 AI 很可能成为任何国家军事与经济力量的主导来源。在一个由一亿名天才组成的虚拟国家中，可以把一千万人投入军事战略、一千万人投入无人机制造、一千万人投入武器研发、一千万人投入情报收集与分析、一千万人投入一般科学进步，等等。拥有强大 AI 的国家面对没有这种能力的国家——甚至只是面对 AI 落后三年的国家——可能相当于一支由二战时期美国海军陆战队员组成的军队，对阵一支由中世纪剑士组成的军队。
**English / Original**
If AI really will soon be “a country of geniuses in a datacenter”, or anything remotely close to it, then AI is likely to be the dominant source of military and economic power for any nation. In a virtual country of 100 million geniuses, 10 million could be applied to military strategy, 10 million to drone manufacture, 10 million to weapons R&D, 10 million to intelligence collection and analysis, 10 million to general scientific advancement, and so on. A nation that possesses powerful AI facing one without it—or even facing one that is behind in AI by 3 years—could be the equivalent of an army of World War II Marines facing an army of medieval swordsmen.
## paragraph 66
**中文**
此外，如果强大 AI 会促成更深入、且可能永久持续的专制压迫形式（见第 4 节），那么确保世界上最强大的国家是民主国家——或者至少建立强有力的保障来防范 AI 驱动的压迫——就更加重要。这也使制定聚焦明确的地缘政治战略变得更为紧迫。
**English / Original**
In addition, if powerful AI enables deeper and potentially permanent forms of autocratic repression (see Section 4), this makes it all the more important that the world’s most powerful nations are democracies—or at least that strong protections exist against AI-driven repression. It also increases the urgency of a focused geopolitical strategy.
## paragraph 67
**中文**
民主国家应努力组建一个全球联盟，以按照共同价值观构建 AI 为核心；通过不断迭代，使加入联盟越来越有吸引力、留在联盟之外越来越缺乏吸引力，从而逐步吸引世界其他国家加入。该联盟应协调推进第 1 至第 4 节所讨论 AI 政策构想的国际化，并努力锁定构建 AI 所需的关键供应链：在联盟内部共享，同时拒绝向联盟外部提供。一些原则和运行目标可以包括：
**English / Original**
Democracies should seek to form a global coalition centered on building AI according to their common values, iteratively trying to draw in the rest of the world by making it more and more attractive to be part of the coalition and less and less attractive to be outside it. The coalition should be a coordinated internationalization of the AI policy ideas discussed in Section 1 through 4, plus an effort to lock down the supply chain critical to building AI by sharing it within the coalition and denying it to those outside it. Some principles and operating goals might include:
## paragraph 68
**中文**
管理 AI 供应链。可信联盟成员应彼此自由共享芯片和半导体制造设备（SME），同时共同努力阻止对手获得这些资源。美国对中国实施的前沿芯片和半导体制造设备出口管制，是美国整体 AI 领先优势的重要原因；这些政策需要扩大、收紧，并与其他志同道合的国家协调。MATCH 和 OVERWATCH 等待审议法案在这方面迈出了良好的第一步，盟友民主国家也需要考虑采取类似措施。
**English / Original**
Managing the AI supply chain. Members of the trusted coalition should freely share chips and semiconductor manufacturing equipment (SME) with each other, while working together to deny it to adversaries. US export controls on frontier chips and SME to China have been a major contributor to the US’s overall lead in AI, and these policies need to be expanded, tightened, and coordinated with other likeminded states. Pending legislation like MATCH and OVERWATCH is a good first step here, and allied democracies need to consider similar measures.
## paragraph 69
**中文**
协调应对 AI 风险。如果在国际上进行协调，第 1 节所述应对生物、网络安全和自主性风险的政策将更加有效（同时也会减轻行业负担）。这意味着公司可以遵守彼此兼容的标准，监管机构也能相互学习如何最好地衡量和缓解这些风险。执法和情报机构还应更紧密合作，追踪并破坏滥用威胁，例如恐怖分子试图利用 AI 制造生物武器。
**English / Original**
Coordinate to address AI’s risks. The policies to address biological, cybersecurity, and autonomy risks described in Section 1 will be more effective (as well as less burdensome to industry) if they are coordinated internationally. This would mean companies can comply with compatible standards and regulators can learn from each other how to best measure and mitigate these risks. Law enforcement and intelligence agencies should also work more closely together on tracking and disrupting threats of misuse, such as efforts by terrorists to build biological weapons with AI.
## paragraph 70
**中文**
共享 AI 的益处。可以利用贸易和监管政策，促进 AI 的经济益处在联盟内部更快扩散，并分享如何加速创新的经验。协调有益部署的方法，可以帮助把 AI 的好处带给发展中国家。例如，协调医疗审批制度，可以更快、更好地测试和批准 AI 赋能的药物（如上文第 3 节所述）。
**English / Original**
Share AI’s benefits. Trade and regulatory policy can be used to facilitate a more rapid diffusion of AI’s economic benefits within the coalition, sharing lessons on how to accelerate innovation. Coordinating approaches to beneficial deployment could help bring the benefits of AI to developing countries. For example, harmonization of medical approval regimes could lead to faster and better testing and approval of AI-enabled drugs (as discussed in Section 3 above).
## paragraph 71
**中文**
共同防御。联盟国家应共同努力，既利用 AI 相互保护，也防御对手的 AI。联盟应集体确保充分生产 AI 引领的网络防御系统、AI 驱动的无人机、AI 驱动的制造能力、涉密 AI 算力及 AI 驱动的研发，并共享 AI 驱动的情报收集成果。
**English / Original**
Mutual defense. Countries in the coalition should work together to defend each other with AI and from adversaries’ AI. The coalition should collectively ensure sufficient production of AI-led cyberdefenses, AI-powered drones, AI-driven manufacturing, classified AI compute, AI-driven R&D, and sharing of AI-driven intelligence collection.
## paragraph 72
**中文**
拒绝 AI 驱动的压迫。联盟成员必须拒绝我在《技术的青春期》中警告过的那种高科技、极端压迫性、由 AI 驱动的暴政，并必须建立类似我在上文第 4 节所述的保障措施。
**English / Original**
Rejection of AI-powered repression. Coalition members should have to reject the high-tech, ultra-repressive, AI-powered tyranny that I warned about in The Adolescence of Technology, and must have safeguards similar to those I described in Section 4 above.
## paragraph 73
**中文**
宏观经济合作。就业或岗位稳定危机像其他经济危机一样，可能跨境传染。因此，各国具有共同利益，应合作协调宏观经济支持与稳定政策，例如第 2 节所述政策，以抵消任何就业影响。
**English / Original**
Macroeconomic cooperation. Crises of employment or job stability, like any other economic crisis, can be contagious across borders. Countries therefore have a mutual interest in working together to coordinate macroeconomic support and stabilization policies, like those described in Section 2, to counter any employment effects.
## paragraph 74
**中文**
目标应当是让联盟成员资格尽可能具有吸引力，同时让留在联盟外部的代价清晰可见。联盟将建立在主权国家间的协调之上，各国仍对本国事务保留完整权力。联盟可以逐步扩展：从意识形态一致的民主国家开始（它们自然更愿意加入），继而逐渐欢迎那些原本不那么一致、但愿意达到联盟标准以换取成员资格巨大益处的国家。理想情况下，最终全世界都将加入。即使这无法实现，建立联盟也能使民主国家处于最有利的位置，遏制并超越那些仍坚持压迫的政权。
**English / Original**
The goal should be to make membership in the coalition as attractive as possible—and the costs of remaining outside it clear. The coalition would rest on coordination among sovereign states, with each nation retaining full authority over its own affairs. It could grow iteratively, starting with ideologically aligned democracies (which will be naturally amenable to joining) and progressively welcoming countries that are less naturally aligned but prepared to meet the coalition's standards in exchange for the enormous benefits of membership. Ideally, the entire world would eventually join. But even if that isn't possible, building the coalition puts democracies in the strongest position to contain and outcompete the regimes that remain committed to repression.
## paragraph 75
**中文**
机会窗口
**English / Original**
A window of opportunity
## paragraph 76
**中文**
AI 的指数级进步带来了紧迫性和变化速度，而政策制定过程通常并不具备应对它们的能力。但这也创造了一个独特的机会窗口。AI 风险已经存在的明确证据、AI 创造经济价值和造成经济冲击之潜力的初步展现，以及公众对不受监管的 AI 路径发起的强烈反弹，共同造成了一种局面：政策制定者如今对前瞻性行动表现出非同寻常的开放态度。树胡和他的森林正在苏醒。
**English / Original**
AI’s exponential progress has created an urgency and a pace of change that the policymaking process is ordinarily ill-equipped to handle. But it has also created a unique window of opportunity. The confluence of clear and present evidence of AI’s risks, an early taste of the AI’s potential for both economic value creation and economic disruption, and a remarkable public backlash against unregulated approaches to AI have created a situation where policymakers are unusually open to forward-looking actions. Treebeard and his forest are waking up.
## paragraph 77
**中文**
AI 行业圈内日益流行把这视为公关问题，声称 AI 需要“更好的营销”。我完全拒绝这种框架。人们担忧 AI，是因为他们正确地意识到其风险真实存在，而不是因为 AI 首席执行官们不够像潘格洛斯那样盲目乐观。我认为，作为 AI 领导者，我有责任继续公开透明地说明这些风险；公众因这种透明度产生担忧，正是民主问责机制在正常运转。关键挑战在于把这种担忧引导为建设性的解决方案，而不让它堕入无形的愤怒和暴力。
**English / Original**
It’s become popular in AI industry circles to view this as a PR problem: to say that AI needs “better marketing”. I reject this framing completely. People are worried about AI because they correctly perceive that its risks are real, not because AI CEOs have been insufficiently Panglossian. I believe it is my duty as an AI leader to continue to be transparent about these risks, and public concern in response to this transparency constitutes democratic accountability working as it should. The key challenge is focusing this concern into constructive solutions and not allowing it to descend into formless anger and violence.
## paragraph 78
**中文**
我对找到解决方案感到乐观，因为许多问题——从应对岗位替代，到模型发布前测试、芯片出口管制，再到能源使用等其他 AI 相关政策议题——在整个政治光谱上都具有常识性的吸引力。我们可以期待一个既有抱负又切合现实的未来世界：一个广泛的跨党派联盟，在直接认识 AI 所带来挑战的驱动下，促使理性、前瞻的政策以远快于通常情况的速度得到采纳。我们越早这样做，所有人就能越早共享 AI 令人难以置信的益处。
**English / Original**
I am optimistic about finding solutions because many of these issues—from addressing job displacement, to pre-release testing of models, to export controls on chips, to other AI related policy issues such as energy use—have a common-sense appeal across the political spectrum. There is an aspirational but realistic future world in which a broad nonpartisan coalition, driven by direct recognition of the challenges posed by AI, leads to sane and forward-looking policies being adopted much faster than usual. The sooner we do this, the sooner we can all share in AI’s incredible benefits.
## paragraph 79
**中文**
感谢艾伦·达福（Allan Dafoe）、马里亚诺-弗洛伦蒂诺·奎利亚尔（Mariano-Florentino Cuéllar）、理查德·方丹（Richard Fontaine）、巴迪·沙阿（Buddy Shah）、瓦斯·纳拉西姆汉（Vas Narasimhan）、马特·伊格莱西亚斯（Matt Yglesias）、尼克·贝克斯特德（Nick Beckstead）、杰森·马西尼（Jason Matheny）、布拉德·卡森（Brad Carson），以及 Anthropic 的众多员工，感谢他们对本文草稿提出的意见和反馈。
**English / Original**
I would like to thank Allan Dafoe, Mariano-Florentino Cuéllar, Richard Fontaine, Buddy Shah, Vas Narasimhan, Matt Yglesias, Nick Beckstead, Jason Matheny, Brad Carson and many of the staff at Anthropic for their comments and feedback on drafts of this essay.
## paragraph 80
**中文**
脚注
**English / Original**
Footnotes
## paragraph 81
**中文**
我在《技术的青春期》一文中讨论了生物风险和自主性风险等问题。Anthropic Institute 也在《当 AI 构建自身时》中发布了一些初步内部数据，涉及递归式自我改进的可能性，即模型能够自主构建更好的模型。
**English / Original**
I discuss biological and autonomy risks, among others, in my essay The Adolescence of Technology. The Anthropic Institute has also released some initial internal data in When AI Builds Itself about the possibility of recursive self-improvement, or models that are autonomously capable of building better models.
## paragraph 82
**中文**
这种现象并非理论上的：我们已在自身的自愿治理框架中多次观察到它，例如《负责任扩展政策》。如果我们为未来 AI 模型设定一份固定或僵化的安全要求清单，一个非常可能的结果是：那些最终证明无关紧要的要求消耗了我们 95% 的合规工作；与此同时，我们却发现，一些最大的风险来源根本未被清单预见。自愿框架可以修改和调整，但立法要做到这一点困难得多。我曾尝试应对这一困境，这可见于我就 SB 1047 写的两封公开信。SB 1047 是加利福尼亚州 2024 年一项试图应对灾难性风险的法案；出于上述原因，我对它看法复杂。
**English / Original**
This phenomenon is not theoretical: we’ve observed it multiple times in our own voluntary governance frameworks like our Responsible Scaling Policy. If we give ourselves a fixed or rigid list of safety requirements for future AI models, a very likely outcome is that requirements which turn out to matter very little end up consuming 95% of our compliance efforts, while at the same time we discover that some of the biggest sources of risk weren’t anticipated in our list at all. Voluntary frameworks can be changed and adapted, but this is much harder with legislation. My attempts to wrestle with this dilemma can be seen in my two public letters about SB 1047, a 2024 California law that attempted to address catastrophic risks and about which I had mixed feelings for the reasons above.
## paragraph 83
**中文**
例如，真正严重的生物风险可能比网络风险难管控得多，因为攻击者相对于防御者拥有强大优势，而且灾难的严重程度可能大得多。
**English / Original**
For example, truly severe biological risks may be much more difficult to manage than cyber risks, because attackers have a strong advantage relative to defenders and the severity of a catastrophe may be much greater.
## paragraph 84
**中文**
关于为何其他技术曾带来劳动力市场快速复苏、没有造成持久性劳动力替代，而这套逻辑可能不适用于 AI，详见《技术的青春期》。该文尤其分析了为何杰文斯悖论或比较优势等通常的适应机制，可能会被技术发展的速度压倒。
**English / Original**
See The Adolescence of Technology for a more detailed analysis why the logic that has led to rapid job market recovery and a lack of enduring labor displacement in other technologies may not apply to AI, and in particular why the usual adaptive mechanisms like Jevon’s paradox or comparative advantage may be overwhelmed by the pace of the technology.
## paragraph 85
**中文**
例如，即使机器在国际象棋、围棋或登山方面都能做得更好，人们仍会毕生投入这些活动，并且仍会因这些活动受到敬仰。
**English / Original**
As an example, people still devote their lives to playing Chess, or Go, or climbing mountains, and are still revered for these activities, even though all can be done better by machines.
## paragraph 86
**中文**
这本质上是在为人们转向新工作、开始接受新职业阶梯的培训提供额外激励：即使短期内可能很痛苦，只要新工作的薪资低于原工作，就向他们支付新旧薪资之间的差额。
**English / Original**
This essentially gives people an extra incentive to migrate to a new job and start training for a new career ladder, even when it may be painful in the short run, by paying them the difference between their new and old salaries, if the new one is lower.
## paragraph 87
**中文**
关于这一主题的更多内容，请参阅《技术的青春期》。
**English / Original**
See The Adolescence of Technology for more on this topic.