# The Triadic Loop: A Framework for Negotiating Alignment in AI Co-hosted Livestreaming

arXiv: https://arxiv.org/abs/2604.18850 · HTML: https://mlsanity.com/paper/2604.18850/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 58 references that are in the map.
- First posted on arXiv 20 Apr 2026.

## Builds on (most cited first, 9 of 9)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [A General Language Assistant as a Laboratory for Alignment](https://mlsanity.com/paper/2112.00861/) (2021)
- [Controlling AI Agent Participation in Group Conversations: A Human-Centered Approach](https://mlsanity.com/paper/2501.17258/) (2025)
- [Hate Raids on Twitch: Echoes of the Past, New Modalities, and Implications for Platform Governance](https://mlsanity.com/paper/2301.03946/) (2023)
- [Observe, Ask, Intervene: Designing AI Agents for More Inclusive Meetings](https://mlsanity.com/paper/2501.10553/) (2025)
- [My Favorite Streamer is an LLM: Discovering, Bonding, and Co-Creating in AI VTuber Fandom](https://mlsanity.com/paper/2509.10427/) (2025)
- [Will Your Next Pair Programming Partner Be Human? An Empirical Evaluation of Generative AI as a Collaborative Teammate in a Semester-Long Classroom Setting](https://mlsanity.com/paper/2505.08119/) (2025)
- [StoryChat: Designing a Narrative-Based Viewer Participation Tool for Live Streaming Chatrooms](https://mlsanity.com/paper/2304.03852/) (2023)
- [Hate Raids on Twitch: Understanding Real-Time Human-Bot Coordinated Attacks in Live Streaming Communities](https://mlsanity.com/paper/2305.16248/) (2023)

## Abstract (arXiv)

AI systems are increasingly embedded in multi-user social environments, yet most alignment frameworks conceptualize interaction as a dyadic relationship between a single user and an AI system. Livestreaming platforms challenge this assumption: interaction unfolds among streamers and audiences in real time, producing dynamic affective and social feedback loops. In this paper, we introduce the Triadic Loop, a conceptual framework that reconceptualizes alignment in AI co-hosted livestreaming as a temporally reinforced process of bidirectional adaptation among three actors: streamer leftrightarrow AI co-host, AI co-host leftrightarrow audience, and streamer leftrightarrow audience. Unlike instruction-following paradigms, bidirectional alignment requires each actor to continuously reshape the others, meaning misalignment in any sub-loop can destabilize the broader system. Drawing on literature from multi-party interaction, collaborative AI, and relational agents, we articulate how AI co-hosts function not only as mediators but as performative participants and community members shaping collective meaning-making. We further propose "strategic misalignment" as a mechanism for sustaining community engagement and introduce three relational evaluation constructs grounded in established instruments. The framework contributes a model of dynamic multi-party alignment, an account of cross-loop reinforcement, and design implications for AI co-hosts that sustain social coherence in participatory media environments.