Tell me more: Intent Fulfilment Framework for Enhancing User Experiences in Conversational XAI
Anjana Wijekoon, David Corsar, Nirmalie Wiratunga, Kyle Martin, Pedram, Salimi

TL;DR
This paper introduces the Intent Fulfilment Framework (IFF) and an Explanation Experience Dialogue Model to improve user-centered explanation experiences in XAI through conversational interactions, enhancing engagement and understanding.
Contribution
The paper presents a novel framework and dialogue model that emphasize follow-up explanations and conversational interfaces to better meet diverse user explanation needs in XAI.
Findings
User engagement improved with IFF implementation
Enhanced utility of AI system through explanation follow-ups
Overall user experience was significantly better in the study
Abstract
The evolution of Explainable Artificial Intelligence (XAI) has emphasised the significance of meeting diverse user needs. The approaches to identifying and addressing these needs must also advance, recognising that explanation experiences are subjective, user-centred processes that interact with users towards a better understanding of AI decision-making. This paper delves into the interrelations in multi-faceted XAI and examines how different types of explanations collaboratively meet users' XAI needs. We introduce the Intent Fulfilment Framework (IFF) for creating explanation experiences. The novelty of this paper lies in recognising the importance of "follow-up" on explanations for obtaining clarity, verification and/or substitution. Moreover, the Explanation Experience Dialogue Model integrates the IFF and "Explanation Followups" to provide users with a conversational interface for…
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Taxonomy
TopicsPersonal Information Management and User Behavior · AI in Service Interactions · Recommender Systems and Techniques
