本文探讨了AI风险的最新发展，包括对不同AI风险观点的标签化，以及国际合作应对AI风险的必要性。文章还介绍了关于AI能力、政策和话语的最新进展，以及如何应对这些发展。

🤔 **标签化AI风险观点：** Rob Bensinger建议采用新的标签来区分不同观点，以改善AI风险的讨论。他认为“AI末日论者”这个标签缺乏一致的含义，并建议使用更精确的标签来描述不同的风险评估和应对策略。

🧠 **AI抽象化：** 研究人员John Wentworth和Eliezer Yudkowsky对AI抽象化的理解存在分歧。Eliezer认为，AI在处理预测性自然世界时会使用类似人类的抽象，但在处理价值观和可修正性等概念时则会有更大的差异。他仍然担心，即使AI使用类似的内部抽象，也难以可靠地引导高级机器学习系统。

🤝 **国际合作应对AI风险：** Eliezer Yudkowsky呼吁国际合作，共同停止前沿AI的发展。他认为，AI竞赛的唯一赢家将是AI本身，因此需要共同努力来控制AI的风险。

📣 **内部揭露机制：** OpenAI和Google DeepMind的前员工呼吁建立内部揭露机制，允许员工分享与风险相关的信息。这一呼吁源于OpenAI前员工遭受严格的保密政策，该政策后来被公司道歉并取消。

📰 **AI能力、政策和话语：** Rob Miles在视频文章中讨论了AI能力、政策和话语在过去一年中的重大发展，以及这些发展如何影响战略形势。Convergence Analysis发布了一份报告，概述了当前AI监管现状，总结了相关立法文本并对各种主题进行了简要分析。

Published on July 15, 2024 9:28 PM GMT

MIRI updates

Rob Bensinger suggests that AI risk discourse could be improved by adopting a new set of labels for different perspectives on existential risk from AI. One drawback of “AI doomer” (a label sometimes used in online discussions) is that it does not have a consistent meaning.
 AI researcher John Wentworth guesses that a central difference between his and Eliezer Yudkowsky’s views might be that Eliezer expects AI to not use abstractions which are similar to those used by humans. Eliezer clarifies that he expects similar abstractions for predictive parts of the natural world, but larger differences for utility-laden concepts like human values and reflectivity-laden concepts like corrigibility. Also, Eliezer says that he is still concerned about the difficulty of reliably steering advanced ML systems even if they do use similar abstractions internally.
 Eliezer joins Joscha Bach, Liv Boeree, and Scott Aaronson for a panel discussion (partly paywalled) on the nature and risks of advanced AI. Eliezer also speaks with Bloomberg’s Nate Lanxon and Jackie Davalos, making the case for international coordination to shut down frontier AI development. “Nobody wins an AI arms race except the AI.”

News and links

In an excellent new video essay, Rob Miles discusses major developments in AI capabilities, policy and discourse over the last year, how those developments have shaped the strategic situation, and what individuals can do to help.
 A report from Convergence Analysis gives a high-level overview of the current state of AI regulation. The report summarizes legislative text and gives short analyses for a range of topics.
 A group of current and former employees of OpenAI and Google DeepMind released an open letter calling on frontier AI companies to adopt policies that allow whistleblowers to share risk-related information. This comes in the wake of news that former OpenAI employees were subject to an extreme non-disclosure policy that the company has since apologized for and seems to have removed.

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