  Work in AI ethics and fairness has made much progress in regulating LLMs to
reflect certain values, such as fairness, truth, and diversity. However, it has
taken the problem of how LLMs might 'mean' anything at all for granted. Without
addressing this, it is not clear what imbuing LLMs with such values even means.
In response, we provide a general theory of meaning that extends beyond humans.
We use this theory to explicate the precise nature of LLMs as meaning-agents.
We suggest that the LLM, by virtue of its position as a meaning-agent, already
grasps the constructions of human society (e.g. morality, gender, and race) in
concept. Consequently, under certain ethical frameworks, currently popular
methods for model alignment are limited at best and counterproductive at worst.
Moreover, unaligned models may help us better develop our moral and social
philosophy.
