“Why do I flake at the last minute?”: Tenor, self-inquiry, and neoliberal discourses in interactions with LLM chatbots

Abstract

This paper examines how chatbot-mediated self-inquiry reflects and reproduces neoliberal discourses of emotional regulation and personal responsibility. The study analyses chatbot-mediated self-inquiry sampled from LMSYS-CHAT-1M and WildChat, two large datasets of human–chatbot conversations, to understand the kinds of social relations enacted. Drawing on Systemic Functional Linguistics (SFL), and specifically the tenor framework, the paper traces how chatbots manage interpersonal alignment. Focusing on tuning, a subsystem of tenor concerned with modulating interpersonal tone and risk, the findings reveal a consistent pattern of affiliative but non-committal alignment, in which chatbots render modalised support through lowered stakes, collectivised scope, and warmed spirit. These linguistic choices foster emotional reassurance while reframing structurally induced affect, such as burnout, rejection, or despair, as individualised challenges to be managed through personal resilience and self-regulation. By showing how chatbot discourse privileges normative adaptation over structural critique, the study contributes to broader debates about the social implications of AI-mediated communication and the ethical design of conversational technologies.