Alignment

Most people writing about AI risk in 2026 are recent arrivals. Roman Yampolskiy is not. He has been making the same argument - that advanced AI systems may be fundamentally uncontrollable - since before the field of AI safety had a settled name, which is partly because he is the one who gave it that name. Whether you find his conclusions alarmist, prescient, or somewhere in between depends mostly on how you read the gap between current systems and the ones he writes about. This post is an attempt to lay out the man, the argument, and the reasons it deserves more than a dismissal. ...

TL;DR “AI safety” covers four distinct layers - product safety, system safety, model alignment, and civilisational safety - and conflating them produces incoherent debates For engineers building production systems today, system safety dominates: most real incidents trace back to flawed system design around the model, not the model itself Practical mitigations are unglamorous: scope tool permissions, bound blast radius, require human approval for irreversible actions, validate outputs, and observe everything The hype conflates capability with intent, existential risk with ordinary risk, and refusal with safety - all three conflations make the conversation harder to act on The load-bearing principle across all four layers is the same: a system should fail in ways that are detectable, recoverable, and bounded The AI safety conversation has reached the point where the phrase has stopped meaning anything specific. In the same week, you will see “AI safety” used to describe content moderation on a chat product, the alignment of frontier models toward human values, the question of whether superintelligence ends civilisation, and a regulatory paper about copyright. These are not the same problem. Treating them as one conversation is the reason the conversation never resolves. ...