Abstract
The increasing applications of AI systems require personalized explanations for their behaviors to various stakeholders since the stakeholders may have various backgrounds. In general, a conversation between explainers and explainees not only allows explainers to obtain explainees’ background, but also allows explainers to tailor their explanations so that explainees can better understand the explanations. In this paper, we propose an approach for an explainer to tailor and communicate personalized explanations to an explainee through having consecutive conversations with the explainee. We prove that the conversation terminates due to the explainee’s justification of the initial claim as long as there exists an explanation for the initial claim that the explainee understands and the explainer is aware of.
| Original language | English |
|---|---|
| Article number | exaf008 |
| Number of pages | 23 |
| Journal | Journal of Logic and Computation |
| Volume | 35 |
| Issue number | 4 |
| Early online date | 5 Feb 2025 |
| DOIs | |
| Publication status | Published - 1 Jun 2025 |
Bibliographical note
Publisher Copyright:© The Author(s) 2025. Published by Oxford University Press. All rights reserved.
Funding
The research is financially supported by the Swiss National Science Foundation grant 20020_184625 and the Hight-end Expert Project from Zhejiang University. We would like to thank all the anonymous reviewers for their helpful comments.
| Funders | Funder number |
|---|---|
| Swiss National Science Foundation | 20020_184625 |
| Hight-end Expert Project from Zhejiang University |
Keywords
- conversation
- explanation
- justification logic
- modal logic
- personalization