Triadic Loop Framework Proposes New AI Alignment Model for Livestreaming Platforms

A new conceptual framework called the Triadic Loop has been introduced to address AI alignment in co-hosted livestreaming environments. Unlike traditional dyadic models focusing on single user-AI relationships, this approach recognizes the complex, multi-party dynamics of platforms where streamers, audiences, and AI systems interact simultaneously. The framework conceptualizes alignment as a temporally reinforced process involving three bidirectional adaptation loops: between streamer and AI co-host, AI co-host and audience, and streamer and audience. This bidirectional alignment requires continuous mutual reshaping among all actors, meaning misalignment in any sub-loop can destabilize the entire system. The research draws on literature from multi-party interaction and collaborative systems to develop this model. The paper, identified as arXiv:2604.18850v1, presents this cross-disciplinary approach to understanding AI behavior in social environments where real-time affective and social feedback loops occur. The work challenges conventional instruction-following paradigms by emphasizing the dynamic, reciprocal nature of alignment in these settings.