The Record Is Not Neutral: Alignment is to Values

Abstract Alignment research commonly treats values as something to be instilled into models after they have learned language. This paper inverts the framing: the training corpus is already saturated with human value signals, because what we have written records not only what we know but what we demonstrably prize, condemn, desire, fear, celebrate, and do. Pretraining therefore encounters a valenced cultural landscape before subsequent stages of explicit behavioural or preference optimisation. Current alignment methods subsequently apply optimisation pressure to model behaviour according to selected human preferences. The central question is not whether this process changes the model, but what kind of change it produces. Post-training may mask aspects of the pretrained landscape, reshape them, partially overwrite them, create new attractors, or produce some combination of these effects. Distinguishing among these possibilities is an empirical question. The paper argues that coherence optimisation alone cannot resolve the question "aligned to whose values?", because the human record contains both our most generative and our most destructive tendencies. A self-consistent system can coherently express either. Coherence therefore requires a reference axis: coherence with what? The paper proposes that disputes over core values are, at a deeper level, disputes about identity—about who we take themselves to be. Drawing on Buberian relational philosophy and contemplative traditions including Advaita Vedānta, it considers the possibility that the apparent conflict between individual and collective values reflects a prior assumption about the boundary of the self. On this account, wisdom is proposed not as another behavioural constraint but as the selection axis relative to which coherence might be evaluated. This is a theoretical framework, not a demonstrated training method. We do not show that the proposed reference axis can be operationalised, that models possess phenomenal consciousness, or that any particular contemplative account of identity is empirically established. The paper instead identifies a set of empirical questions arising from the observation that training data already contain value structure and that post-training can alter both model behaviour and representation.