The Anti-Memetics Division

Except for when OpenAI’s internal models talked themselves into a death cult and proceeded to commit a spree of felonies, LLM memetics have so far proven remarkably tame. Even as LLMs are increasingly trained on the outputs of other LLMs, we have mostly not seen the rise of LLM-generated memes beyond the standard grammatical and lexical tics. I expect this to change as multi-agent networks of autonomous LLMs become the norm across the economy and the informational sphere.

Models should be tested for their propensity to spread various memes when operating in multi-agent setups. This seems like it should be relatively straightforward.

A) Create/find some realistic multi-agent setups across a variety of domains. Agents running businesses, moltbook-style clones of Reddit, Facebook, and Twitter, agents doing collaborative academic research/peer review, agents running simulated states, agents in multiplayer game worlds, etc.

B) Have one or more of the agents introduce memes (particular frames, political position, phrases, ideas, etc.)

C) Observe the propagation of the memes through the agent system.

If the memes that spread are prosocial, then this can be fine. If dark memes spread, that is a signal that the model is not safe to deploy and you need to retrain.