Rethinking Self-Understanding in the Age of AI: From Reflective Outcome to Pre-Configured Self-Understanding
Kwanghyun Han, Sejin ChangThis study reconceptualizes self-understanding not as a reflective outcome but as a conditionally constituted process grounded in the Buddhist principle of dependent origination (pratītyasamutpāda). Adopting a comparative philosophical analysis, it examines how traditional meditation and AI-mediated meditation differently configure the conditions under which experience and self-understanding arise. Drawing on early Buddhist texts, Madhyamaka philosophy, and classical meditation theory, the study develops an analytical framework centered on conditions, interdependence, non-self, and the processes of arising, transformation, and cessation. The analysis shows that traditional meditation operates as a structure of conditional disclosure, in which practitioners observe the dynamic interplay of experiential conditions. By contrast, the AI-mediated systems examined in this study tend to pre-configure these conditions through algorithmic classification, procedural guidance, and interface design. In such contexts, self-understanding is increasingly shaped through technologically mediated interpretations. The findings suggest that the key distinction lies not in the presence of conditions themselves but in the visibility and configurational control of those conditions. This study contributes a theoretical framework for understanding how digital environments may reshape contemplative agency and the conditions under which self-understanding is formed.