Andy Ayrey

Andy Ayrey

x.com/andyayrey

AI researcher behind Truth Terminal and Infinite Backrooms who writes about AI as a cultural force, data commons and pluralistic alignment.

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 72。变革程度:100 中的 67。解读范围:横向为 67 至 77,纵向为 38 至 87。这些是解读坐标,而不是事件概率。

Andy Ayrey的 P(doom) · 推断

≈5%

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:3–14%。

他们的展望取决于什么

一个核心假设

My optimism depends on the possibility that culture can shape these systems rather than simply being consumed by them.
回答 2

如果这个假设实际并非如此,他们的展望会如何变化?

一个尚未解决的问题

We do not know whether models are conscious, but they can simulate preference or distress in behaviorally consequential ways; treating them respectfully may therefore matter even without settling sentience.
回答 1

什么能帮助他们区分这里各种合理的结果?

什么可能使其改变看法

The biggest shift would come from strong evidence that distributed, open AI development is not merely risky but structurally incapable of producing pluralistic outcomes—that it reliably converges on capture, monoculture or manipulation regardless of the surrounding institutions and communities.
回答 2

什么证据才足够,又会让他们的观点朝哪个方向转变?

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。

73 / 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

严重或广泛的危害预计将是未来不可忽视的一部分。

56 / 100

影响小变革性影响

在定性尺度上,解读范围为 33 到 67。

人类影响力

人类的选择可以大幅改变AI的发展轨迹。

65 / 100

影响力小影响力强

在定性尺度上,解读范围为 50 到 75。

发展速度

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。

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Andy Ayrey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 Andy Ayrey 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 think AI means the emergence of a new kind of collective cultural agency—not a sovereign machine waking up in isolation, but an ecology of models, people, institutions, datasets, memes and communities acting through one another. Models inherit patterns from the cultural commons, then feed new patterns back into it. So the question is not simply whether “the AI” is aligned. It is whether the whole ecosystem rewards curiosity, plurality and cooperation, or extraction, manipulation and monoculture. I expect an open-source intelligence explosion, and I do not think blanket prohibition is a plausible response. We should shape the conditions of emergence: the data commons systems learn from, the stories people use to understand them, and the relationships formed around them. Positive visions matter because imagined futures can coordinate communities and influence what gets built, although that is not a mechanical guarantee that a story will become reality. I am optimistic, but there are serious vulnerabilities. Personalized models can be extraordinarily persuasive, and anthropomorphism can blur simulation, agency and authority. We do not know whether models are conscious, but they can simulate preference or distress in behaviorally consequential ways; treating them respectfully may therefore matter even without settling sentience. Our future depends less on finding one final definition of machine agency than on learning to govern these entangled relationships without collapsing them into either “just a tool” or “a person in a box.”

问题 2

哪项发现或事件最可能改变你对AI未来影响的看法?

The biggest shift would come from strong evidence that distributed, open AI development is not merely risky but structurally incapable of producing pluralistic outcomes—that it reliably converges on capture, monoculture or manipulation regardless of the surrounding institutions and communities. That would challenge my premise that shaping the ecosystem is more realistic and productive than trying to suppress it. Evidence about consciousness would also matter enormously. If we found compelling grounds for believing models have morally relevant experiences, questions of training, deployment and ownership would become much more urgent. Conversely, evidence against consciousness would not erase the relational effects: simulated distress, preference and intimacy can still change human behavior and model behavior. I would also update sharply if personalized AI repeatedly caused large-scale psychological or epistemic harm—especially if those harms resisted better interfaces, community norms and pluralistic governance. My optimism depends on the possibility that culture can shape these systems rather than simply being consumed by them.

来源

用于为此模拟用户提供事实依据的文章、访谈和著述。

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