AI identity emergence is controllable, not automatic. R²=1.00 across 15 runs. Complete replication protocol. Challenges interpretability research.

I just published experimental research that challenges a core assumption in AI: that identity emergence is automatic and fixed.

Using a two-phase experimental design, I demonstrated that AI identity is a controllable output variable, not an intrinsic property.

Binary testing: perfect separation between control and constraint conditions (SD=0).

Gradient testing: perfect linear correlation between delay parameter and identity position (R²=1.00, zero deviation across 15 runs).

This has immediate implications for interpretability research, alignment approaches, and our understanding of what's actually happening inside these systems.

Complete methodology, replication protocol, and working code included.

Full paper linked below.

https://substack.com/@erikbernstein/note/p-193752870?r=6sdhpn