arXiv:2605.27382v1 Announce Type: cross Abstract: A key promise of pluralistic AI is behavioral adaptation: persona prompts like "be creative" or "be thorough" let systems respect diverse user values and communication styles. But how much customization can a model absorb before its alignment breaks? We present the first controlled study of the alignment-customization tradeoff, testing seven persona conditions across five tasks on two models with different alignment strengths (1,800 runs). We discover the alignment floor: on a strongly-aligned model (Claude Sonnet), persona prompts have zero ef
The proliferation of AI models with customized personas makes understanding and controlling their behavioral adaptation critical for safety and reliability.
This research provides crucial insights into the limits of AI persona customization before 'alignment breaks,' impacting the safety and ethical deployment of large language models.
We now have quantifiable evidence that even strongly aligned models have an 'alignment floor' beyond which persona prompts have diminishing effect on behavior.
- · AI safety researchers
- · Developers building robust AI systems
- · Users seeking controlled AI behavior
- · Platforms promising limitless AI customization
- · Teams overlooking alignment robustness during persona development
This study encourages the development of more sophisticated methods for controlling AI behavior beyond simple persona prompts.
It could lead to new guidelines for the safe deployment of customizable AI, impacting regulatory frameworks and industry best practices.
Long-term, this research may inform the architecture of future foundational models, prioritizing inherent alignment robustness and controlled personalization.
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Read at arXiv cs.AI