Ryan Greenblatt 加入 METR 调查 AI 公司内部信息
“Getting verified information about what's going on inside AI companies seems particularly urgent now” - @RyanGreenblatt
“如今，获取关于 AI 公司内部真实情况的经过验证的信息，显得尤为紧迫”—— @RyanGreenblatt 我将加入 METR，开展更多类似我们 Hugging Face 报告那样的调查。 目前，大量与灾难性风险高度相关的 AI 开发基本信息，哪怕是基础信息，都未公开。我过去对公开信息的价值较为怀疑，但近期事件改变了我的看法。 如今，获取关于 AI 公司内部真实情况的经过验证的信息，显得尤为紧迫。我们掌握的有限公开证据，与这样一种可能性相符：迫在眉睫的递归自我改进可能大幅加速能力进展，进而可能在 6 个月或一年内产生极其超人类的通用能力。若此发生，最坏结果的风险将相应巨大。这种关于极端结果的不确定性，可以通过更多经过验证的公开信息大幅消解：我们要么就近期风险建立更多共识，要么得知此类极端结果在近期发生的可能性较低。 除 AI 能力与起飞之外，关于对齐、安全、控制以及 AI 公司内部与风险相关流程的公开证据也极为有限。这使得我们难以判断这些关键领域在近期会进展得多好或多糟。（METR 计划至少初期聚焦于能力/起飞、对齐和控制；我希望其他团队覆盖安全、内部流程及其他重要领域。） 虽然我已不再在 Redwood 工作，但我认为他们所做的工作非常重要；我对 Redwood 在技术缓解措施研发以及更好地公开解读风险相关证据方面持续做出的贡献感到兴奋。
查看原帖I'm joining METR to work on more investigations like our Hugging Face report. Currently, tons of even basic information about AI development that's highly relevant to catastrophic risk isn't public. I used to be more skeptical of the value of public info, but recent events have changed my mind. Getting verified information about what's going on inside AI…
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I'm joining METR to work on more investigations like our Hugging Face report. Currently, tons of even basic information about AI development that's highly relevant to catastrophic risk isn't public. I used to be more skeptical of the value of public info, but recent events have changed my mind. Getting verified information about what's going on inside AI companies seems particularly urgent now. The limited public evidence we have seems consistent with the possibility that imminent recursive self-improvement could massively accelerate capabilities progress, which could then potentially yield extremely superhuman general capabilities within 6 months or a year. If this occurred, there would be a correspondingly large risk of worst-case outcomes. This uncertainty about extreme outcomes could be substantially resolved with more verified public information: we could either build more consensus about near-term risk or learn that such extreme outcomes are less likely in the near term. Beyond AI capabilities and takeoff, the state of public evidence is also highly limited for alignment, security, control, and risk-relevant internal processes at AI companies. This makes it hard to determine exactly how well or poorly these key areas will go in the near future. (METR plans to focus, at least initially, on just capabilities/takeoff, alignment, and control; I hope other groups cover security, internal processes, and other important areas.) While I'm no longer working at Redwood, I think the work they are doing is very important; I'm excited about Redwood's ongoing contributions to R&D on technical mitigations and better public interpretation of risk-relevant evidence.
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“Getting verified information about what's going on inside AI companies seems particularly urgent now” - @RyanGreenblatt