SOURCE-LINKED INTELLIGENCE

Auditing Political Alignment in LLM Assistants: Engagement, Stance, and User Identity

arXiv · AI, language, vision and robotics · article · Sep 19, 2026 · UTC

LLM-based AI systems answer political questions for hundreds of millions of people. Current audits measure what they say to an average user, but their behavior is dynamic. I argue that their political behavior is a set of policies over whom to answer, what to say, and whether to engage at all, conditional on the topic and what the system knows about the user. I call these policies the system's speech regime, which is how a developer settles the tradeoff between answering, accommodating the user, and refusing, each of which carries a cost that varies by topic. I derive a typology of five regime

Read original source ↗ Open in workspace

recordType

paper

region

Global