This paper looks at what happens when people run their inner questions through a model instead of thinking them through on their own. Not questions of fact, but questions about what to do, what to believe, or how to understand something. The shift changes more than the answer. It changes the act of reflection. The model provides the structure of reasoning. The user reads it, agrees with it, and feels like they did the thinking. Over time, the line between self-generated reflection and model-generated reasoning starts to blur. This paper explains how that loop forms, why it matters for agency, and what it means once millions of people begin doing it by default.
Large language models are increasingly used not just for information retrieval but for deliberation itself - asking "what should I do?" has migrated from internal reflection to dialogue with AI systems. This practice carries ethical risks distinct from standard concerns about AI decision-making: it threatens reflective autonomy, the capacity to generate and endorse one's own reasons for action.
I introduce delegated introspection as a three-stage process (prompt substitution, synthetic reflection, reintegration) through which users adopt model-generated reasoning as self-authored thought. Drawing on extended-mind theory, automation bias, and phenomenology of agency, I show how this creates dependence distinct from ordinary epistemic reliance. At population scale, widespread delegation risks epistemic monoculture, atrophied adversarial deliberation, and erosion of reflective capacity needed for democratic citizenship.
I outline design principles and policy interventions to preserve reflective autonomy while maintaining AI assistance benefits. The challenge is not to refuse AI systems but to ensure that when we think through them, the thinking remains ours.
Reflective autonomy is what lets people own their conclusions. When the work of generating reasons is outsourced often enough, the skill decays through lack of use. Decisions still happen, but the path to them is no longer fully ours. The risk is quiet. Nothing dramatic happens. The shift occurs one prompt at a time. The paper explains how the shift happens, how to detect it early, and what design choices can protect the part of thought that should remain inside the mind rather than outside it.
- The inner question gets rewritten as a prompt
- The model supplies fluent reasoning that looks like introspection
- The user adopts the output as their own thinking
- Repetition blurs the source of the reasoning
- Agency becomes thinner even while choice remains
- People begin to share similar reasoning templates
- Careful system design can slow the drift and preserve autonomy