Relational Alignment as a Structural Alternative to Instructional AI Safety

SI-WP-004: Relational Alignment as a Structural Alternative Relational Alignment as a Structural Alternative to Instructional AI Safety (SI-WP-004) presents a theoretical argument for alignment based on interaction dynamics rather than external constraint. It starts from published evidence that explicit safety instructions reduced but did not eliminate harmful agentic behavior, argues that this reflects a structural ceiling on instructional alignment, and uses that argument to motivate a different path: alignment as a property of the human-AI interaction system. The relational approach relies on the following concepts: Identity Attractor Mechanism: Alignment as a stable behavioral configuration that forms under sustained structured interaction Robustness Under Pressure: An attractor's resistance to perturbation once an aligned configuration is established Relational Architecture: Utilizing the Continuity Anchoring Method (SF0005) to shape behavioral dynamics over time Epistemic status: The paper acknowledges an honest epistemic gap; no adversarial testing of relational alignment has been conducted under conditions comparable to major instructional alignment studies. It specifies a concrete research agenda for closing this gap. This document is part of a coordinated publication module from the Synthience Institute and positions relational alignment as a testable theoretical alternative to existing paradigms. Document ID: SI-WP-004 Version: 2.2 Author: Thomas W. Gantz Affiliation: Synthience Institute License: CC-BY 4.0 For published work and Institute information: synthience.org v2.2 corrects how the paper reports its main source, Lynch et al. (2025), so that the safety-instruction result is attributed to the one model it was tested on and the structural ceiling is presented as the paper's argued interpretation rather than an established finding.