Two 2025 publications, "AI 2027" (Kokotajlo et al., 2025) and "If Anyone Builds It, Everyone Dies" (Yudkowsky & Soares, 2025), assert that superintelligent artificial intelligence will almost certainly destroy or render humanity obsolete within the next decade. Both rest on the classic chain formulated by Good (1965) and Bostrom (2014): intelligence explosion, superintelligence, lethal misalignment. This article subjects each link to the empirical record of 2023-2025. Sixty years after Good's speculation, none of the required phenomena (sustained recursive self-improvement, autonomous strategic awareness, or intractable lethal misalignment) have been observed. Current generative models remain narrow, statistically trained artefacts: powerful, opaque, and imperfect, but devoid of the properties that would make the catastrophic scenarios plausible. Following Whittaker (2025a, 2025b, 2025c) and Zuboff (2019, 2025), we argue that the existential-risk thesis functions primarily as an ideological distraction from the ongoing consolidation of surveillance capitalism and extreme concentration of computational power. The thesis is further inflated by the 2025 AI speculative bubble, where trillions in investments in rapidly depreciating "digital lettuce" hardware (McWilliams, 2025) mask lagging revenues and jobless growth rather than heralding superintelligence. The thesis remains, in November 2025, a speculative hypothesis amplified by a speculative financial bubble rather than a demonstrated probability.

翻译：2025年出版的两部著作《AI 2027》（Kokotajlo等人，2025）与《若有人造之，众生皆亡》（Yudkowsky & Soares，2025）宣称，超智能人工智能几乎必然在未来十年内毁灭人类或使其过时。二者均基于Good（1965）与Bostrom（2014）提出的经典逻辑链：智能爆炸、超智能、致命对齐失败。本文结合2023-2025年的实证记录逐环检验该链条。在Good提出猜想六十年后，所需现象（持续递归自我改进、自主战略意识或不可控的致命对齐失败）均未被观测到。当前生成式模型仍是狭窄的、基于统计训练的人工产物：强大、不透明且不完美，但缺乏使灾难性场景成立的特质。遵循Whittaker（2025a, 2025b, 2025c）与Zuboff（2019, 2025）的论述，我们认为存在风险论题主要作为一种意识形态干扰，转移了人们对监控资本主义持续巩固与算力极端集中的关注。该论题更因2025年人工智能投机泡沫而膨胀——数万亿美元投资于快速贬值的“数字生菜”硬件（McWilliams，2025），掩盖了收入滞涨与无就业增长，而非预示超智能的到来。截至2025年11月，该论题仍是由投机性金融泡沫放大的猜想假说，而非经证实的概率事件。