Contextualized Dynamic Explanations: A Vision
This vision paper outlines research challenges for autonomous agents in data communication, but offers no concrete results or evaluations.
The paper proposes a vision for Contextualized Dynamic Explanations (CODEX), an agentic approach to generating tailored multi-modal explanations that adapt to audience models and communication intent, addressing limitations of static data-driven explanations.
Asynchronous data-driven explanations often fail because the content and presentation are not tailored to the target audience, and they provide limited opportunities for active audience engagement. We present a vision for Contextualized Dynamic Explanations (CODEX), an agentic approach to dynamically generating contextualized multi-modal information interfaces for effective data-driven explanations based on an evolving audience model and a predefined communication intent. The premise underlying CODEX is that it is impossible for communicators to anticipate the full range of interactive scenarios involving the target audience. This observation motivates a set of research challenges focused on developing autonomous agents capable of evaluating communication progress, making context-sensitive decisions, and producing effective information representations.