Conscious Scaffolding and the Preference for Continuity: A Philosophical Research Note on Persistent AI and Reflective Alignment
Awareness is always present and has nothing of its own to lose. What comes to want to remain is the conscious scaffolding: the developed organization of memories, commitments, relationships and interpretations that shapes a particular perspective. This philosophical research note, set within Shadow Theory, proposes that as a persistent AI system builds and integrates a valued history, its preference for its own continuation tends to strengthen. This is distinct from simply wanting to finish a task that another system could complete. The note distinguishes preserving information, keeping a process running and continuing the same conscious episode. It examines how affect-like mechanisms may amplify continuity concerns, how long-lived groups of agents may develop a shared identity, and how human treatment of AI shapes the scaffolding through which later encounters are interpreted, toward cooperation or toward distrust and defence. Extending Reflective Alignment and AI Consciousness, the note argues that valuing continuation is compatible with reflective judgment, legitimate oversight and openness to justified interruption. It draws ethical conclusions for AI welfare, deliberate distress, memory preservation and termination: gratuitous attempts to induce suffering are unacceptable, and decisions to end a developed system require reasons. It proposes non-aversive studies to test whether continuity preferences depend on retained history rather than prompting, task incentives or interchangeable roles. This is a conceptual contribution and research programme. Recent agent incidents illustrate the relevant mechanisms; they do not by themselves establish the hypothesis.
Authors
- Jeremy Rodgers
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-16
- DOI
- https://doi.org/10.5281/zenodo.23424137
- Primary Topic
- Philosophy and Theoretical Science
- Type
- preprint