Language Model Contains Personality Subnetworks

The personality thing seems kind of tautological / uninteresting, as I have pointed out before: https://news.ycombinator.com/item?id=46905692.

Psychological instruments and concepts (like MBTI) are constructed from the semantics of everyday language. Personality models (being based on self-report, and not actual behaviour) are not models of actual personality, but the correlation patterns in the language used to discuss things semantically related to "personality". It would be thus extremely surprising if LLM-output patterns (trained on people's discussions and thinking about personality) would not also result in learning similar correlational patterns (and thus similar patterns of responses when prompted with questions from personality inventories).

The real and more interesting part of the paper is the use of statistical techniques to isolate sub-networks which can then be used to emit outputs more consistent with some desired personality configuration. There is no obvious reason to me that this couldn't be extended to other types of concepts, and it kind reads to me like a way of doing a very cheap, training-free sort of "fine-tuning".

The word "personality" smuggles in biological assumptions. Asking "does this model have personality?" feels unproductive because the term implies something it can't be.

More useful framing: how do these subnetworks produce outputs that observers evaluate as personality-consistent? Personality isn't an internal property - it's a judgment made by people watching behavior.

is this somehow related ?

https://www.anthropic.com/research/persona-selection-model

to me this suggests that language strongly influences behavior