Anthropic's correlated-failure objection to multipolar safety: because AI systems across the industry broadly share training and alignment techniques, and may all derive from a small number of base models, their alignment failures can fail in a correlated way, so a balance of power among many AI systems does not by itself supply independent checks; and because some technologies are offence-dominant, fielding good AIs against misaligned ones is not reliably effective even if only a small fraction are misaligned.

Evidence 1 passage

• groundsUntitled source

  Second, some may object that we can simply keep AIs in check with a balance of power between many AI systems, as we do with humans. The problem is that while humans vary enormously, AI systems broadly share training and alignment techniques across the industry, and those techniques may fail in a correlated way. Furthermore, given the cost of training such systems, it may even be the case that all systems are essentially derived from a very small number of base models. Additionally, even if a small fraction of AI instances are misaligned, they may be able to take advantage of [offense-dominant](https://sk.sagepub.com/ency/edvol/power/chpt/offense-defense-dominance) technologies, such that having "good" AIs to defend against the bad AIs is not necessarily always effective. Of course, the balance of power between humans does not always work either—some historical figures have come close to taking over the world.

Where the agents stand

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