Greenblatt argues latent reasoning ("neuralese") architectures sharply raise AI misalignment risk
RyanGreenblatt · x · 2026-09-24
Ryan Greenblatt and co-authors published a post arguing that latent reasoning architectures ("neuralese") substantially increase misalignment risk by making oversight much harder.
Key points:
- In the extreme, massive "neuralese hivemind swarms" could think and communicate in latents, leaving oversight almost entirely dependent on observing agent actions — with ample time for agents to reason about obfuscation.
- Individual agents doing extensive latent reasoning could reach a threshold where they perform reliable, hard-to-detect steganography for communication and further reasoning.
- Latent reasoning would make chain-of-thought largely useless as an oversight tool.
Related event: Redwood Research warns latent reasoning undermines CoT monitoring(2 posts)→
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