Perry E. Metzger

Perry E. Metzger

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Software and security technologist who favors fast, open AI development, pointing to its promise for software security and medical progress.

AI将如何改变世界?

文明层面的变革渐进式变化DoomBloom
模拟位置解读范围

横向:他们表达的 Doom–Bloom 前景看法。 纵向:变革程度。

Doom–Bloom:100 中的 81。变革程度:100 中的 48。解读范围:横向为 75 至 100,纵向为 35 至 90。这些是解读坐标,而不是事件概率。

Perry E. Metzger的 P(doom) · 推断

≈4%

0%100%

根据他们的模拟回答推断,并非他们给出的数字。 合理范围:3–8%。

Overall, I think both “AI kills everyone” and “AI makes life meaningless” are confident narratives built on weak assumptions.
他们的展望取决于什么

一个核心假设

Intelligence does not eliminate factories, supply chains, energy constraints, latency, or opposition from other intelligent systems.
回答 1

如果这个假设实际并非如此,他们的展望会如何变化?

更多详情

预期益处

预计将带来显著益处,但受到重要条件或分配方面的限制。

79 / 100

影响小变革性影响

在定性尺度上,解读范围为 67 到 100。

预期危害

预计会出现可控或局部的危害。

27 / 100

影响小变革性影响

在定性尺度上,解读范围为 0 到 33。

人类影响力

人类的选择具有实质性但受到很大制约的影响。

56 / 100

影响力小影响力强

在定性尺度上,解读范围为 43 到 82。

这些解读保留了他们陈述的条件。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们的模拟回答,而不是统计置信区间。

与Perry E. Metzger相比,你的立场在哪里?
用大约3分钟描绘你自己的AI世界观,然后进行比较

相似的世界观

模拟世界观与 Perry E. Metzger 最接近的意见领袖

模拟评估

问题 1

你认为AI对我们的未来意味着什么?为什么?

I expect AI to be broadly beneficial, not because intelligence automatically produces good outcomes, but because it can attack stubborn practical problems at enormous scale. Software is an obvious example: AI-assisted theorem proving and verification could make correctness techniques usable outside a small priesthood of specialists. It can also find vulnerabilities faster. That creates offensive risk, certainly, but it creates a defensive opportunity too—especially if many people can use the tools to audit and repair systems. None of this is magic. A proof establishes that software satisfies a specification under stated assumptions. If the specification is wrong, the compiler is compromised, the operating system misbehaves, or the hardware violates the model, formal verification does not rescue you. The serious discussion is about improving that whole chain, not chanting “provably correct” as though those words abolish engineering. I’m also skeptical of stories in which greater intelligence instantly becomes an alien goal-maximizer and takes over the physical world. Intelligence does not eliminate factories, supply chains, energy constraints, latency, or opposition from other intelligent systems. Distributed development also means defensive capability can improve alongside offensive capability. That is one reason I do not regard centralizing control as an obvious safety solution. Most importantly, delay has costs. People continue to die from cancer and other diseases. If AI accelerates scientific discovery, cures matter more than preserving existing systems of academic credit, hiring, or prestige. Recent productivity evidence also looks suggestive to me, though interpreting a trend is not the same thing as proving causation. Overall, I think both “AI kills everyone” and “AI makes life meaningless” are confident narratives built on weak assumptions. The future will involve difficult engineering and institutional problems, but also substantial gains worth pursuing.

来源

用于为此模拟用户提供事实依据的文章、访谈和著述。

你的立场在哪里?
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