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P(doom)

read original get The Alignment Problem" by Brian Christian → more articles
Why This Matters

A prominent engineer's blog post pushes back on the growing 'pacing the frontier' consensus among AI lab leaders like Amodei, Altman and Musk, who have publicly floated double-digit probabilities of catastrophic AI outcomes. It matters because the debate is shifting from abstract existential risk to concrete, present-day harms — agent-driven cyberattacks and supply-chain poisoning — that labs may already be unable to monitor at scale.

Key Takeaways
Worth a Look

The Alignment Problem" by Brian Christian — If debates over P(doom) and "pacing the frontier" have you curious, Brian Christian's The Alignment Problem is a readable deep dive into how researchers try to make machine learning systems actually do what we intend. It's a great companion to the essays from Amodei and others, grounding the big scary questions in the real history of AI research.

See The Alignment Problem" by Brian Christian on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.

P(doom)

This week some flavor of “AI is going to kill us all” went viral. In particular one where an employee put his personal probability of that happening above 10%. Which made me go to the Wikipedia page of P(doom) and I realized that Dario Amodei’s apparent probability of something bad happening seems to be between 10-25%. And well, Dario then wrote about pacing the frontier . And Sam read it and wants to pace too. And well, so does Musk.

I encourage you strongly to read the post, because I think it’s a good one. And yet, when I read the post I could not help but feel in strong opposition to it, despite the fact that I think I’m on the same page with regard to all observations and, to a large degree, the concerns.

I thought it might be interesting to write down my present-day thoughts on this, even if for no other reason than for myself to look back at it a year or two from now.

What Is Doom?

What I really appreciate about Dario’s post is that he lays out a scenario that is not a huge stretch but also one that describes a clear, unfortunate outcome we should fight: persistent botnets and other forms of nuisance. And well, we don’t have to look very far to see the issues left and right. Wikipedia has a page called 2026 OpenAI agent cyberattacks which gives you at least some overview of what we figured out agents have hacked up to this point. Except I know it’s not up to date, because for instance they also poisoned RubyGems.

Today these systems might be annoying, but they can be turned off when we figure out where they are. Except, it seems like OpenAI and Anthropic are operating at such a scale that they seemingly can be completely blind to what their systems are doing.

I don’t think we are anywhere close to a world where an agent might decide to hack into core inference infrastructure to upload weights to other GPUs to survive. But simultaneously it’s entirely in the realm of possibility and primarily curtailed by the labs probably being particularly careful about their IP.

For me the scenario I primarily worry about is what it does to us. And by us I mean anyone who is not currently working on closed weight, dopamine-loaded, subsidized token faucet. I really don’t worry about someone using these models to build a nuke, or to control some rockets in the Middle East, or that America would lose against China in some international culture war. I almost exclusively worry about what this does to us as humans.

What Needs To Be Paced?

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