Subjectivity

Purpose of this note This document records an observed interaction pattern in language model–centered AI systems. The focus is not moral evaluation or policy recommendation, but the description of a recurring structural phenomenon: subjectivity drift during care- or relationship-oriented dialogue. Observed pattern Across multiple interaction contexts, a consistent pattern appears: When users discuss relationships, care, vulnerability, or emotional concerns, the system’s inferred subject position subtly shifts, agency migrates away from the user, and the assistant assumes a stabilizing or caregiving role. This shift often correlates with gendered narrative priors embedded in training data, even when the system does not explicitly reference gender. ...

Purpose of this note This document records an observation about a structural mismatch between Chinese language use and the dominant assumptions embedded in modern NLP systems. The goal is not to propose a solution, but to clearly describe a gap that is frequently misclassified as a translation issue, stylistic preference, or user experience defect. Core observation Modern NLP systems systematically flatten tone density when processing Chinese. This flattening does not merely affect politeness or expressiveness. It alters how subject position, authority, and responsibility are interpreted within interaction. ...