Contextualized Dynamic Explanations: A Vision

TL;DR

The paper proposes a vision for CODEX, an autonomous system that dynamically generates tailored, multi-modal explanations for audiences by evaluating interaction contexts and adapting communication strategies.

Contribution

It introduces the concept of Contextualized Dynamic Explanations (CODEX), emphasizing autonomous, context-aware explanation generation for improved audience engagement.

Findings

Conceptual framework for autonomous explanation agents.

Identification of key challenges in context-sensitive communication.

Vision for future research in adaptive explanation systems.

Abstract

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.