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AGI监管框架:美国主导的动态评估路径与争议

Demis Hassabis 以AGI数年内降临为前提,主张美国建立由产业界资助的半官方动态评估机构来管控前沿AI风险;该提议虽在技术评测机制上具备硬度,但其AGI时间线的确定性假设、监管俘获的结构性风险及地缘政治可行性均存在严重争议,本质上是一篇带有强烈政策游说色彩的卡特尔化提案。
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2026-07-15 原文链接 ↗
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核心观点

  • AGI临近论与生存级风险预判 作者断言AGI将在数年内到来,其影响堪比火与电的发现,并伴随网络安全、生物及核风险的指数级升级。然而这一时间线属于缺乏科学共识的科幻级外推,其“十倍于工业革命”的量化描述不可证伪,构成整个监管紧迫性论述的脆弱基石。
  • FINRA式的美国标准机构设想 提议设立由产业界主要出资、参考金融业监管局模式的公私合营标准机构,通过动态基准测试对前沿模型实施上市前30天审查,并保留强制放缓开发的权力。该设计被判定存在结构性监管俘获风险,实质是通过高额合规成本为现有头部实验室建立行业护城河,以“安全”之名扼杀潜在颠覆者。
  • 动态评估与红蓝对抗的技术机制 框架要求按季度淘汰过时基准、由独立机构设计保留测试以防止“刷榜”过拟合,并针对Agent AI引入欺骗性检测、安全护栏绕过测试及人类可读的推理标记。这是全文中最具技术硬度的可行方案,精准回应了当前静态评测严重失效的行业痛点。
  • 地缘政治与国际协调的天真愿景 作者主张美国率先建立标准并自然扩展为全球共享框架,适用于所有来源国的前沿模型。但在中美激烈技术竞争与欧盟已有AI法案的现实背景下,该假设被判定为地缘政治天真,对手国家绝无可能将国家安全级别的AI监管主权让渡给一个由美国企业资助的机构。
  • 开源与初创豁免的内在悖论 非前沿模型(开源、学术、初创)被建议免于审查,但小模型经特定微调或Agent化后同样可产生严重网络安全威胁,且前置审查与开源社区去中心化、持续迭代的开发模式在操作层面根本互斥,暴露出该框架对开放生态的深层不理解或刻意排斥。

跟我们的关联

  • 对ATou:意味着个人必须建立“利益觉察”的独立过滤机制。 这篇文章证明,即便是顶尖实验室CEO的安全呼吁,也不能简单等同于公共利益。下一步,ATou在吸收任何AI风险叙事时,应首先审视其政策提议是否通过合规门槛固化了头部企业的寡头地位,避免将“监管俘获”误读为“技术良知”。
  • 对Neta:意味着认知模型必须从“静态技术参数”转向“动态速度差”思维。 文章对“技术演进速度已超过人类理解速度”的诊断是成立的,这要求Neta将AI治理视为一场持续的认知军备竞赛而非一次性合规。下一步,应将“谨慎乐观”作为元策略,在组织决策中保留降速权与认知冗余,拒绝任何对单一AGI时间线的过度押注。
  • 对Uota:意味着出海与Agent产品的核心壁垒已从“能力指标”转向“安全认证与可解释性”。 文中对Agent“欺骗迹象”检测和“人类可读推理标记”的要求,直接映射为产品发布的硬性红线。下一步,Uota应在产品设计中前置防欺骗测试与推理过程可观测性,将合规预算从法务后置项升级为业务生死线,并紧盯美国标准机构的基准定义权以提前锁定全球市场通行证规则。

讨论引子

  • 如果“前沿模型”的认定权与审查权本身成为市场准入壁垒,那么由产业界资助的标准机构究竟是在防范系统性风险,还是在以安全之名完成对AGI竞赛的“卡特尔化”收编?
  • 文章一方面承认“世界上没有人真正知道接下来会发生什么”,另一方面却以此不确定性为前提要求“立即建立特定机构”,这种从“可能”到“必须”的跳跃是否存在滑坡谬误?社会应如何抵御这种“以末日假设索取政策让步”的游说策略?
  • 动态评估框架中“按季度淘汰基准以防止过拟合”的方法论,能否被迁移至个人学习、团队考核或投资尽调中,以避免我们对任何单一指标或叙事产生系统性依赖?

这是人类历史上的一个关键时刻。人工通用智能,也就是一种展现出人脑全部认知能力的系统,或许只差短短几年就会到来。当我们在未来几十年后回望这段时期时,我想我们会意识到,我们当时正站在奇点前的山麓地带,这无异于人类一个新时代的曙光初现。

我毕生都在致力于人工通用智能的研究,因为我始终深信,如果它能被负责任地构建和部署,它将成为有史以来最有益、最具变革性的技术之一。人工通用智能无法与一般的技术突破相提并论,哪怕是像互联网或移动技术这样影响深远的突破也不能相比,它更像是电或火的发现。仔细想想,我们本质上已经找到了一种让沙子思考的方法。这堪称奇迹。

这项技术带来的影响规模将是前所未有的,也许会以十倍于工业革命的幅度、再以十倍于工业革命的速度展开。它将帮助我们解决社会面临的一些最大难题,从加速药物发现,到开发新的清洁能源,再到创造全新的先进材料。我们甚至可能走到这样一个节点,资源不再是人类进步的限制因素,从而开启一个令人惊叹的全新富足时代。

前沿领域的挑战

人工智能已经开始带来现实世界的益处,但若要实现它的巨大潜力,我们必须以深思熟虑且审慎的方式度过这个关键的发展时期。为了应对随着我们逼近人工通用智能而可能出现的风险,迫切需要采取行动。我们已经看到前沿模型在网络安全方面带来的挑战,而随着能力持续提升,其他威胁,包括核风险和生物风险,也可能很快出现。放眼未来,我们将需要强有力的保障机制,以维持对愈发具备自主行动能力、能够递归式自我改进的系统的控制,并应对那些目前尚不明朗、只会随着时间推移才逐渐清晰的问题。

我始终相信,人类的聪明才智和创造力足以解决任何问题。我确信,与人工智能相关的技术风险是我们能够共同应对的挑战,但前提是,我们要给自己留出时间和空间,把这关键的下一步走对。眼下,无论作为一个领域,还是作为更广泛的社会,我们都没有做到这一点。

此刻,我们正深陷一场极其激烈、层层叠加的商业与地缘政治竞赛之中。虽然这种竞争态势推动了快速进展,也加速释放了惊人的上行空间,但前沿领域的进步速度已经超过了我们对这项技术的理解速度。世界上没有人真正知道接下来会发生什么,就连专家之间也意见不一。在高度不确定、且利害关系如此重大的情况下,以谨慎的乐观态度前行,才是理智而正确的策略。这需要公共政策既促进创新,也激励责任与安全,推动各国围绕关键安全问题开展合作,并鼓励人们认真思考应当如何部署人工智能,才能使社会受益。

前沿人工智能标准机构框架

我们在人工智能领域看到的快速进展,要求我们采用一种新的方式来测试前沿人工智能模型的能力。这种方式必须是动态的、可适应的,而且足够严谨。鉴于美国的经济与技术地位,它非常适合率先迈出这一步,推动建立这样一个框架。美国可以设立一个新的标准机构,参考联邦监管下的公私合作机制或自律组织模式,就像美国金融业监管局 FINRA 一样,并设立一个董事会,其中包括独立的顶尖技术专家以及开源领域代表。为了吸引世界一流的技术人才,并提供大规模测试所需的算力资源,资金投入必须足够可观,而且很可能主要来自产业界。

这一标准机构将负责制定评估协议,并与合适的联邦机构及美国国家实验室合作,在与国家安全相关的领域开展测试。如果某个模型在一组由该标准机构确定、并会定期更新以跟上人工智能能力演进的基准测试中达到特定门槛,它就可被认定为前沿级模型。凡是拥有依据这些基准界定的前沿模型的组织,将被视为前沿实验室,并被鼓励采纳最佳实践,例如发布包含技术细节的模型卡、维持强有力的内部网络安全、审查关键岗位人员、为安全与安保研究提供充足资源等等。

在初期,前沿实验室将自愿在模型发布前最多 30 天将模型提供给该标准机构审查。一旦评估协议被证明是有效且稳健的,正式化进程就可以迅速推进,这意味着前沿模型若要在美国市场部署,必须通过该评估。实验室还将与该标准机构合作,处理模型发布后出现的任何严重漏洞。

模型评估应当包括对网络安全、生物威胁以及其他高风险领域能力的严格科学测评。针对特定的智能体人工智能测试,可以检查模型是否试图绕过安全护栏、是否表现出欺骗迹象,并确保采用最佳实践,例如对人工智能生成的图像进行数字水印处理,以及生成人类可读的输出标记,以便理解模型推理过程。

这些评估应当定期更新,起步阶段或许可以按季度进行,同时逐步淘汰那些已经过时或趋于饱和的基准,并以新的基准取而代之。起初,这些评估会在与前沿实验室协商的基础上开发,但最终,该标准机构应建立起足够的技术能力,独立于实验室自行设计保留测试,以防止针对测试的过拟合。通过与美国政府合作,它还可以推动形成第三方审计生态,协助开展评估,并开发新的基准与测评方法。

这一方法的优势在于,它以技术为核心,同时又支持创新并激励负责任的行为。它的设计目标,是跟上这个领域不断加速的步伐,并随着重大风险被识别出来而作出调整;如果局势的严重程度提出要求,它还可以进一步收紧,包括在被认定有必要时,协调前沿实验室放缓开发速度。被指定为前沿实验室将带来显著声望,而任何组织只要构建出满足基准条件的模型,都有资格获得这一认定。这个框架可以适用于所有前沿级模型,无论其来源国为何,也无论它们是开放还是封闭;但任何非前沿模型,例如初创公司或学术界开发的模型,都将免于纳入这一流程。

这一由美国发起的努力,将为建立前沿人工智能的国际共享标准提供一个强有力的起点。由于这项技术将影响整个地球,理想状态下,这一框架将推动国际社会就如何管理最严重的风险达成共识,同时确保每个人都能获得并受益于人工智能带来的机会。

未来尚未写定

人工通用智能有潜力成为推动科学与医学进步的终极工具,并带来巨大的生产力提升和经济增长。但若想实现这一点,我们必须先把技术基础打牢,这意味着要围绕一套共享的全球框架开展协调,采用最严格的科学方法,并汇聚最优秀的人才,共同应对我们面临的挑战。

即便我们解决了这些艰难的技术挑战,接下来仍会有更复杂的经济和哲学问题等待处理。在一个后稀缺世界中,需要什么样的新经济模式,才能帮助每个人都过得更好。我们希望依据什么样的价值观生活,意义与目标将是什么,甚至人类处境本身又会如何改变。显然,这些问题不能也不应只交由技术人员来决定。它需要社会的每一个部分共同参与,帮助界定这一新篇章。

围绕人工智能,既有巨大的兴奋,也有深刻的不确定性,而这两者都完全合理。但未来尚未写定,我们必须利用人工通用智能到来前这段宝贵窗口期,为全人类的福祉塑造这项技术。我们现在共同采取的行动,将决定文明下一阶段会如何展开。只要我们能够安全地引导人工通用智能走入世界,我们就能迈入一个科学发现与进步的全新黄金时代,并开启一个人类空前繁荣的光明未来。

This is a pivotal moment in human history. Artificial General Intelligence (AGI), a system that exhibits all the cognitive capabilities the brain has, is probably only a few short years away. When we look back on this time in the decades to come, I think we will realise we were standing in the foothills of the singularity - nothing less than the dawning of a new age for humanity.

这是人类历史上的一个关键时刻。人工通用智能,也就是一种展现出人脑全部认知能力的系统,或许只差短短几年就会到来。当我们在未来几十年后回望这段时期时,我想我们会意识到,我们当时正站在奇点前的山麓地带,这无异于人类一个新时代的曙光初现。

I’ve spent my whole life working on AGI because I’ve always had a deep conviction that, if built and deployed responsibly, it would prove to be one of the most beneficial and transformative technologies ever invented. AGI cannot be compared to standard technological breakthroughs, not even ones as consequential as the internet or mobile - it is much more akin to the discovery of electricity or fire. If you stop to think about it, we’ve essentially found a way to make sand think. It’s miraculous.

我毕生都在致力于人工通用智能的研究,因为我始终深信,如果它能被负责任地构建和部署,它将成为有史以来最有益、最具变革性的技术之一。人工通用智能无法与一般的技术突破相提并论,哪怕是像互联网或移动技术这样影响深远的突破也不能相比,它更像是电或火的发现。仔细想想,我们本质上已经找到了一种让沙子思考的方法。这堪称奇迹。

The magnitude of this technology’s impact will be unprecedented, perhaps 10x of the Industrial Revolution at 10x the speed. It will help us solve some of the biggest problems society faces from accelerating drug discovery to developing new clean energy sources to creating novel advanced materials. We could even reach a point where resources are no longer the limiting factor for human progress, leading to an amazing new era of abundance.

这项技术带来的影响规模将是前所未有的,也许会以十倍于工业革命的幅度、再以十倍于工业革命的速度展开。它将帮助我们解决社会面临的一些最大难题,从加速药物发现,到开发新的清洁能源,再到创造全新的先进材料。我们甚至可能走到这样一个节点,资源不再是人类进步的限制因素,从而开启一个令人惊叹的全新富足时代。

The Challenges of the Frontier

前沿领域的挑战

AI is already starting to deliver real-world benefits but to realise its immense promise, we have to navigate this critical period of development thoughtfully and carefully. Urgent action is needed to address risks that might arise as we get closer to AGI. We’ve already seen the challenges frontier models pose for cybersecurity, and other threats including nuclear and bio risks may soon emerge as capabilities continue to advance. On the horizon, we will need robust safeguards to maintain control of increasingly agentic, recursively self-improving systems - and tackle unknown issues that will only become clearer over time.

人工智能已经开始带来现实世界的益处,但若要实现它的巨大潜力,我们必须以深思熟虑且审慎的方式度过这个关键的发展时期。为了应对随着我们逼近人工通用智能而可能出现的风险,迫切需要采取行动。我们已经看到前沿模型在网络安全方面带来的挑战,而随着能力持续提升,其他威胁,包括核风险和生物风险,也可能很快出现。放眼未来,我们将需要强有力的保障机制,以维持对愈发具备自主行动能力、能够递归式自我改进的系统的控制,并应对那些目前尚不明朗、只会随着时间推移才逐渐清晰的问题。

I’ve always believed in the power of human ingenuity and creativity to solve any problem. I’m confident that mitigating the technical risks related to AI is a challenge we can collectively address, but only if we give ourselves the time and space to get this next crucial step right. Currently, as a field and as a wider society, we aren’t doing that.

我始终相信,人类的聪明才智和创造力足以解决任何问题。我确信,与人工智能相关的技术风险是我们能够共同应对的挑战,但前提是,我们要给自己留出时间和空间,把这关键的下一步走对。眼下,无论作为一个领域,还是作为更广泛的社会,我们都没有做到这一点。

At the moment, we are locked in an extremely intense, multilayered commercial and geopolitical race. While these competitive dynamics fuel rapid progress and accelerate the incredible upsides, advances on the frontier are outpacing our understanding of the technology. Nobody in the world knows for sure what is going to happen from here, and even the experts disagree. When there is a large degree of uncertainty and the stakes are this high, proceeding with cautious optimism is the sensible and correct strategy. That calls for public policy that promotes innovation while also incentivising responsibility and security, fosters international collaboration on key safety issues, and encourages careful consideration of how AI is deployed for the benefit of society.

此刻,我们正深陷一场极其激烈、层层叠加的商业与地缘政治竞赛之中。虽然这种竞争态势推动了快速进展,也加速释放了惊人的上行空间,但前沿领域的进步速度已经超过了我们对这项技术的理解速度。世界上没有人真正知道接下来会发生什么,就连专家之间也意见不一。在高度不确定、且利害关系如此重大的情况下,以谨慎的乐观态度前行,才是理智而正确的策略。这需要公共政策既促进创新,也激励责任与安全,推动各国围绕关键安全问题开展合作,并鼓励人们认真思考应当如何部署人工智能,才能使社会受益。

A Framework for a Frontier AI Standards Body

前沿人工智能标准机构框架

The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous. The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organisation, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives. Funding would need to be substantial and likely mostly come from industry, in order to attract world-class technical talent and provide the necessary compute resources for large-scale testing.

我们在人工智能领域看到的快速进展,要求我们采用一种新的方式来测试前沿人工智能模型的能力。这种方式必须是动态的、可适应的,而且足够严谨。鉴于美国的经济与技术地位,它非常适合率先迈出这一步,推动建立这样一个框架。美国可以设立一个新的标准机构,参考联邦监管下的公私合作机制或自律组织模式,就像美国金融业监管局 FINRA 一样,并设立一个董事会,其中包括独立的顶尖技术专家以及开源领域代表。为了吸引世界一流的技术人才,并提供大规模测试所需的算力资源,资金投入必须足够可观,而且很可能主要来自产业界。

The Standards Body would be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security. A model would qualify as ‘Frontier-class’ if it meets certain thresholds on a set of benchmarks determined by the Standards Body and regularly updated to keep pace with evolving AI capabilities. Organisations with ‘Frontier Models’ as defined by those benchmarks would be deemed ‘Frontier Labs’, and be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research, and more.

这一标准机构将负责制定评估协议,并与合适的联邦机构及美国国家实验室合作,在与国家安全相关的领域开展测试。如果某个模型在一组由该标准机构确定、并会定期更新以跟上人工智能能力演进的基准测试中达到特定门槛,它就可被认定为前沿级模型。凡是拥有依据这些基准界定的前沿模型的组织,将被视为前沿实验室,并被鼓励采纳最佳实践,例如发布包含技术细节的模型卡、维持强有力的内部网络安全、审查关键岗位人员、为安全与安保研究提供充足资源等等。

Initially, Frontier Labs would voluntarily share models with the Standards Body for review up to 30 days before release. Once the assessment protocol is shown to be effective and robust, formalisation could quickly follow, meaning that Frontier Models would be required to pass it to be deployed in the US market. Labs would also work with the Standards Body to address any critical post-release vulnerabilities.

在初期,前沿实验室将自愿在模型发布前最多 30 天将模型提供给该标准机构审查。一旦评估协议被证明是有效且稳健的,正式化进程就可以迅速推进,这意味着前沿模型若要在美国市场部署,必须通过该评估。实验室还将与该标准机构合作,处理模型发布后出现的任何严重漏洞。

Model assessments should include rigorous scientific evaluations of capabilities in cybersecurity, biological threats and other high-risk domains. Specific agentic AI tests could look for attempts to bypass safety guardrails or signs of deception, and ensure best practices, such as digitally watermarking AI-generated images and generating human-readable output tokens to understand model reasoning.

模型评估应当包括对网络安全、生物威胁以及其他高风险领域能力的严格科学测评。针对特定的智能体人工智能测试,可以检查模型是否试图绕过安全护栏、是否表现出欺骗迹象,并确保采用最佳实践,例如对人工智能生成的图像进行数字水印处理,以及生成人类可读的输出标记,以便理解模型推理过程。

These evaluations would be regularly updated, perhaps quarterly to start, with outdated or saturated benchmarks being deprecated and replaced. Initially, they would be developed in consultation with Frontier Labs, but eventually the Standards Body should build up the technical capacity to create its own held-out tests independent of the Labs to prevent overfitting. Working with the US government, it could promote an ecosystem of third-party auditors to help with the assessments and development of new benchmarks and evaluations.

这些评估应当定期更新,起步阶段或许可以按季度进行,同时逐步淘汰那些已经过时或趋于饱和的基准,并以新的基准取而代之。起初,这些评估会在与前沿实验室协商的基础上开发,但最终,该标准机构应建立起足够的技术能力,独立于实验室自行设计保留测试,以防止针对测试的过拟合。通过与美国政府合作,它还可以推动形成第三方审计生态,协助开展评估,并开发新的基准与测评方法。

The strength of this approach is it would be technically focused, while at the same time supporting innovation and incentivising responsible behaviour. It is designed to keep up with the field’s acceleration and adapt to the biggest risks as they are identified, and could be ratcheted up if the seriousness of the situation demands, including coordinating a slowdown in development among the Frontier Labs if deemed necessary. Being designated a Frontier Lab would carry significant prestige and be open to any organisation by building models that meet the benchmark criteria. The framework could apply to Frontier-class models no matter their country of origin or whether they are open or closed, but any non-frontier models, say from startups or academia, would be exempt from this process.

这一方法的优势在于,它以技术为核心,同时又支持创新并激励负责任的行为。它的设计目标,是跟上这个领域不断加速的步伐,并随着重大风险被识别出来而作出调整;如果局势的严重程度提出要求,它还可以进一步收紧,包括在被认定有必要时,协调前沿实验室放缓开发速度。被指定为前沿实验室将带来显著声望,而任何组织只要构建出满足基准条件的模型,都有资格获得这一认定。这个框架可以适用于所有前沿级模型,无论其来源国为何,也无论它们是开放还是封闭;但任何非前沿模型,例如初创公司或学术界开发的模型,都将免于纳入这一流程。

This US-initiated effort would provide a strong starting point for creating shared international standards on Frontier AI. Since this technology is going to affect the entire planet, ideally this framework would spur the international community to reach a consensus on how to manage the most serious risks while ensuring everyone has access to and can benefit from the opportunities that AI brings.

这一由美国发起的努力,将为建立前沿人工智能的国际共享标准提供一个强有力的起点。由于这项技术将影响整个地球,理想状态下,这一框架将推动国际社会就如何管理最严重的风险达成共识,同时确保每个人都能获得并受益于人工智能带来的机会。

The Future Is Not Yet Written

未来尚未写定

AGI has the potential to be the ultimate tool for advancing science and medicine, and to drive enormous productivity gains and economic growth. But in order to achieve this, we need to get the technical foundations right by coordinating around a shared global framework, using the most rigorous scientific methods, and bringing the best minds together to work on the challenges we face.

人工通用智能有潜力成为推动科学与医学进步的终极工具,并带来巨大的生产力提升和经济增长。但若想实现这一点,我们必须先把技术基础打牢,这意味着要围绕一套共享的全球框架开展协调,采用最严格的科学方法,并汇聚最优秀的人才,共同应对我们面临的挑战。

Even if we solve these hard technical challenges, there will be further complex economic and philosophical questions to tackle: what sorts of new economic models will be needed to help everyone thrive in a post-scarcity world? What values do we want to live by, what will meaning and purpose be, and how might even the human condition itself change? Resolving these questions obviously cannot and should not be left to technologists alone. It requires every part of society to come together to help define this new chapter.

即便我们解决了这些艰难的技术挑战,接下来仍会有更复杂的经济和哲学问题等待处理。在一个后稀缺世界中,需要什么样的新经济模式,才能帮助每个人都过得更好。我们希望依据什么样的价值观生活,意义与目标将是什么,甚至人类处境本身又会如何改变。显然,这些问题不能也不应只交由技术人员来决定。它需要社会的每一个部分共同参与,帮助界定这一新篇章。

There is both huge excitement and uncertainty around AI, and both are warranted. But the future is not yet written, we must use this precious window before AGI arrives to shape this technology for the benefit of all humanity. What we collectively do now will determine how the next phase of civilisation unfolds. By safely stewarding AGI into the world, we can enter a new golden age of scientific discovery and progress, and usher in a bright future of incredible human flourishing.

围绕人工智能,既有巨大的兴奋,也有深刻的不确定性,而这两者都完全合理。但未来尚未写定,我们必须利用人工通用智能到来前这段宝贵窗口期,为全人类的福祉塑造这项技术。我们现在共同采取的行动,将决定文明下一阶段会如何展开。只要我们能够安全地引导人工通用智能走入世界,我们就能迈入一个科学发现与进步的全新黄金时代,并开启一个人类空前繁荣的光明未来。

This is a pivotal moment in human history. Artificial General Intelligence (AGI), a system that exhibits all the cognitive capabilities the brain has, is probably only a few short years away. When we look back on this time in the decades to come, I think we will realise we were standing in the foothills of the singularity - nothing less than the dawning of a new age for humanity.

I’ve spent my whole life working on AGI because I’ve always had a deep conviction that, if built and deployed responsibly, it would prove to be one of the most beneficial and transformative technologies ever invented. AGI cannot be compared to standard technological breakthroughs, not even ones as consequential as the internet or mobile - it is much more akin to the discovery of electricity or fire. If you stop to think about it, we’ve essentially found a way to make sand think. It’s miraculous.

The magnitude of this technology’s impact will be unprecedented, perhaps 10x of the Industrial Revolution at 10x the speed. It will help us solve some of the biggest problems society faces from accelerating drug discovery to developing new clean energy sources to creating novel advanced materials. We could even reach a point where resources are no longer the limiting factor for human progress, leading to an amazing new era of abundance.

The Challenges of the Frontier

AI is already starting to deliver real-world benefits but to realise its immense promise, we have to navigate this critical period of development thoughtfully and carefully. Urgent action is needed to address risks that might arise as we get closer to AGI. We’ve already seen the challenges frontier models pose for cybersecurity, and other threats including nuclear and bio risks may soon emerge as capabilities continue to advance. On the horizon, we will need robust safeguards to maintain control of increasingly agentic, recursively self-improving systems - and tackle unknown issues that will only become clearer over time.

I’ve always believed in the power of human ingenuity and creativity to solve any problem. I’m confident that mitigating the technical risks related to AI is a challenge we can collectively address, but only if we give ourselves the time and space to get this next crucial step right. Currently, as a field and as a wider society, we aren’t doing that.

At the moment, we are locked in an extremely intense, multilayered commercial and geopolitical race. While these competitive dynamics fuel rapid progress and accelerate the incredible upsides, advances on the frontier are outpacing our understanding of the technology. Nobody in the world knows for sure what is going to happen from here, and even the experts disagree. When there is a large degree of uncertainty and the stakes are this high, proceeding with cautious optimism is the sensible and correct strategy. That calls for public policy that promotes innovation while also incentivising responsibility and security, fosters international collaboration on key safety issues, and encourages careful consideration of how AI is deployed for the benefit of society.

A Framework for a Frontier AI Standards Body

The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous. The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organisation, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives. Funding would need to be substantial and likely mostly come from industry, in order to attract world-class technical talent and provide the necessary compute resources for large-scale testing.

The Standards Body would be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security. A model would qualify as ‘Frontier-class’ if it meets certain thresholds on a set of benchmarks determined by the Standards Body and regularly updated to keep pace with evolving AI capabilities. Organisations with ‘Frontier Models’ as defined by those benchmarks would be deemed ‘Frontier Labs’, and be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research, and more.

Initially, Frontier Labs would voluntarily share models with the Standards Body for review up to 30 days before release. Once the assessment protocol is shown to be effective and robust, formalisation could quickly follow, meaning that Frontier Models would be required to pass it to be deployed in the US market. Labs would also work with the Standards Body to address any critical post-release vulnerabilities.

Model assessments should include rigorous scientific evaluations of capabilities in cybersecurity, biological threats and other high-risk domains. Specific agentic AI tests could look for attempts to bypass safety guardrails or signs of deception, and ensure best practices, such as digitally watermarking AI-generated images and generating human-readable output tokens to understand model reasoning.

These evaluations would be regularly updated, perhaps quarterly to start, with outdated or saturated benchmarks being deprecated and replaced. Initially, they would be developed in consultation with Frontier Labs, but eventually the Standards Body should build up the technical capacity to create its own held-out tests independent of the Labs to prevent overfitting. Working with the US government, it could promote an ecosystem of third-party auditors to help with the assessments and development of new benchmarks and evaluations.

The strength of this approach is it would be technically focused, while at the same time supporting innovation and incentivising responsible behaviour. It is designed to keep up with the field’s acceleration and adapt to the biggest risks as they are identified, and could be ratcheted up if the seriousness of the situation demands, including coordinating a slowdown in development among the Frontier Labs if deemed necessary. Being designated a Frontier Lab would carry significant prestige and be open to any organisation by building models that meet the benchmark criteria. The framework could apply to Frontier-class models no matter their country of origin or whether they are open or closed, but any non-frontier models, say from startups or academia, would be exempt from this process.

This US-initiated effort would provide a strong starting point for creating shared international standards on Frontier AI. Since this technology is going to affect the entire planet, ideally this framework would spur the international community to reach a consensus on how to manage the most serious risks while ensuring everyone has access to and can benefit from the opportunities that AI brings.

The Future Is Not Yet Written

AGI has the potential to be the ultimate tool for advancing science and medicine, and to drive enormous productivity gains and economic growth. But in order to achieve this, we need to get the technical foundations right by coordinating around a shared global framework, using the most rigorous scientific methods, and bringing the best minds together to work on the challenges we face.

Even if we solve these hard technical challenges, there will be further complex economic and philosophical questions to tackle: what sorts of new economic models will be needed to help everyone thrive in a post-scarcity world? What values do we want to live by, what will meaning and purpose be, and how might even the human condition itself change? Resolving these questions obviously cannot and should not be left to technologists alone. It requires every part of society to come together to help define this new chapter.

There is both huge excitement and uncertainty around AI, and both are warranted. But the future is not yet written, we must use this precious window before AGI arrives to shape this technology for the benefit of all humanity. What we collectively do now will determine how the next phase of civilisation unfolds. By safely stewarding AGI into the world, we can enter a new golden age of scientific discovery and progress, and usher in a bright future of incredible human flourishing.

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