问题 1
Grady Booch
x.com/Grady_BoochSoftware engineer and UML co-creator who finds LLMs useful but unreliable and worries about corporate power and present harms, not superintelligence.
AI将如何改变世界?
横向:他表达的 Doom–Bloom 前景看法。 纵向:变革程度。
Doom–Bloom:100 中的 65。变革程度:100 中的 63。解读范围:横向为 50 至 75,纵向为 50 至 75。这些是解读坐标,而不是事件概率。
≈0%
“My p(doom) remains asymptotically close to zero.”
Not defined in the post; its context is humanity’s destruction by dangerous superintelligent AI
一个核心假设
A system capable of threatening civilization in that way would need to be not merely superintelligent but super-embodied, and I do not expect that.回答 1
如果这个假设实际并非如此,他的展望会如何变化?
什么可能使其改变看法
A genuine machine mind with robust abductive reasoning and consequential agency in the physical world would change my view most.回答 4
什么证据才足够,又会让他的观点朝哪个方向转变?
更多详情
预计将带来显著益处,但受到重要条件或分配方面的限制。
66 / 100
在定性尺度上,解读范围为 67 到 67。
仍有几种解读是合理的:预计会出现可控或局部的危害。 / 严重或广泛的危害预计将是未来不可忽视的一部分。
46 / 100
在定性尺度上,解读范围为 33 到 67。
根据你的回答得出的暂定估计;较宽的范围表示其他合理解读。
53 / 100
在定性尺度上,解读范围为 21 到 100。
停止或大幅放缓开发能力更强的AI。
模拟位置:在落实所述保障措施的前提下继续开发。
加快开发能力更强的AI。
在事先落实保护措施或获得许可之前,限制所讨论的AI用途。
模拟位置:允许所讨论的AI用途,同时实施有针对性的问责与保护措施。
尽量减少对所讨论AI用途的限制。
这些解读保留了他陈述的条件。益处和危害都可能很大。这些范围描述的是我们如何解读他的模拟回答,而不是统计置信区间。
相似的世界观
模拟世界观与 Grady Booch 最接近的意见领袖
模拟评估
来源
用于为此模拟用户提供事实依据的文章、访谈和著述。
Calls large language models unreliable narrators at best, useful when guided like an energetic intern but error-prone, and says he keeps an air gap between LLM output and production code. Argues they can induce and deduce but are architecturally incapable of abductive reasoning, so a model trained on science before the mid-1800s would not have discovered cells or viruses. Says he is not worried about superintelligence but about billionaires using these systems, likens software’s shift in the balance of power to nuclear weapons, and urges developers to apply their own ethics. Hosts’ remarks about Claude’s ubiquity are not his. Own turns in the automated transcript inspected.

Frames AI coding tools as another rise in abstraction, like compilers and libraries, rather than the end of software engineering. Calls Dario Amodei’s claim that software engineering will soon be automatable utter bullshit, arguing that engineers balance technical, human, economic and ethical forces automation does not address, and that agents mostly automate patterns they were trained on. Expects job losses in delivery-pipeline infrastructure and simple app building, with people needing to reskill toward systems. He uses Claude for unfamiliar libraries. Own turns in Substack’s automated transcript inspected; the host’s claims about recent model quality are not his.

你的立场在哪里?
描绘我的世界观