Agentic Social Affordance Framework (ASAF): Rethinking Agent Identity Design as a Collaboration Interface in Multi-Agent Systems

As AI systems evolve from single conversational agents to complex multi-agent architectures, a critical design dimension has been overlooked: how the social identity of individual agents shapes human behavior within the collaboration. This paper introduces the Agentic Social Affordance Framework (ASAF), a conceptual framework that extends Social Affordance theory into the context of multi-agent AI systems. We argue that agent identity design functions not merely as a user interface convention, but as a collaboration interface—structuring how users perceive, approach, and engage with each agent, and thereby influencing the quality of Human-Agent collaboration outcomes. ASAF comprises three mechanisms: Identity Signaling, Behavioral Priming, and Collaborative Governance. We situate ASAF within existing HCI affordance theory, discuss its implications for multi-agent system design, and outline directions for future empirical validation.