Beyond Technocratic XAI: The Who, What & How in Explanation Design

TL;DR

This paper advocates for a context-aware, design-oriented approach to XAI explanations, emphasizing who needs explanations, what they need, and how to deliver them ethically and effectively.

Contribution

It introduces a three-part framework for explanation design in XAI, integrating design thinking and ethical considerations to improve interpretability and social responsibility.

Findings

Proposes a three-part explanation design framework: Who, What, How.

Highlights ethical risks like epistemic inequality and social bias.

Encourages context-aware, sociotechnical explanation practices.

Abstract

The field of Explainable AI (XAI) offers a wide range of techniques for making complex models interpretable. Yet, in practice, generating meaningful explanations is a context-dependent task that requires intentional design choices to ensure accessibility and transparency. This paper reframes explanation as a situated design process -- an approach particularly relevant for practitioners involved in building and deploying explainable systems. Drawing on prior research and principles from design thinking, we propose a three-part framework for explanation design in XAI: asking Who needs the explanation, What they need explained, and How that explanation should be delivered. We also emphasize the need for ethical considerations, including risks of epistemic inequality, reinforcing social inequities, and obscuring accountability and governance. By treating explanation as a sociotechnical design process, this framework encourages a context-aware approach to XAI that supports effective communication and the development of ethically responsible explanations.