Geist in the Machine: Simulating Recognition and Inner Dialogue in AI-Mediated Teaching and Research

TL;DR

This paper presents an AI tutoring system incorporating recognition and psycho-dynamic concepts, evaluated through a reflexive methodology that demonstrates improved performance and explores AI's impact on human relationships in education and research.

Contribution

It introduces recognition-enhanced prompts and a multi-agent ego/superego architecture, applying psycho-social theories to improve AI tutoring and reflexively analyze AI-human interactions.

Findings

Recognition-enhanced prompts significantly improve model performance (d=1.34-1.92).

Reflexive methodology demonstrates the AI system's effectiveness and impact on human relationships.

The approach offers new insights into AI-mediated teaching and research dynamics.

Abstract

This paper describes an AI tutoring system built upon two psycho-social theoretic constructs: Hegelian recognition and Freudian psychodynamics. Two related interventions are proposed: recognition-enhanced prompts that instruct an AI tutor to treat the learner as an autonomous subject, and a multi-agent ego/superego architecture where an internal critic reviews tutor output. The paper also describes the nature of the human/machine relationship involved in this research itself, employing a reflexive methodology: Claude Code (Opus 4.5/4.6) builds, evaluates, and documents the AI tutor by authoring a companion scientific paper - a process termed "vibe scholarship" - in conjunction with human prompting and suggestion, which is itself documented and analyzed. The companion paper, included as appendix, reports a factorial evaluation across three generation models (DeepSeek V3.2, Haiku 4.5, Gemini Flash 3.0), finding recognition-enhanced prompts produce large, model-independent improvements (d=1.34-1.92) through a calibration mechanism that raises the floor of tutor performance. This result, significant in itself, is combined with the qualitative reflections in this paper to consider impacts of AI on the delicate dynamics of student / teacher and assistant / researcher relations.