Argumentation Theoretical Frameworks for Explainable Artificial Intelligence
Martijn Demollin, Qurat-Ul-Ain Shaheen, Katarzyna Budzynska, Carles Sierra
Abstract
This paper discusses four major argumentation theoretical frameworks with respect to their use in support of explainable artificial intelligence (XAI). We consider these frameworks as useful tools for both system-centred and user-centred XAI. The former is concerned with the generation of explanations for decisions taken by AI systems, while the latter is concerned with the way explanations are given to users and received by them.- Anthology ID:
- 2020.nl4xai-1.10
- Volume:
- 2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence
- Month:
- November
- Year:
- 2020
- Address:
- Dublin, Ireland
- Editors:
- Jose M. Alonso, Alejandro Catala
- Venue:
- NL4XAI
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 44–49
- Language:
- URL:
- https://aclanthology.org/2020.nl4xai-1.10
- DOI:
- Cite (ACL):
- Martijn Demollin, Qurat-Ul-Ain Shaheen, Katarzyna Budzynska, and Carles Sierra. 2020. Argumentation Theoretical Frameworks for Explainable Artificial Intelligence. In 2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence, pages 44–49, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Argumentation Theoretical Frameworks for Explainable Artificial Intelligence (Demollin et al., NL4XAI 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.nl4xai-1.10.pdf