A Survey of Explainable AI Terminology

Miruna A. Clinciu, Helen F. Hastie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The field of Explainable Artificial Intelligence attempts to solve the problem of algorithmic opacity. Many terms and notions have been introduced recently to define Explainable AI, however, these terms seem to be used interchangeably, which is leading to confusion in this rapidly expanding field. As a solution to overcome this problem, we present an analysis of the existing research literature and examine how key terms, such as transparency, intelligibility, interpretability, and explainability are referred to and in what context. This paper, thus, moves towards a standard terminology for Explainable AI.
Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence
PublisherAssociation for Computational Linguistics
Pages8-13
Number of pages6
ISBN (Print)9781950737703
DOIs
Publication statusPublished - 29 Oct 2019
Event1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence 2019 - Tokyo, Japan
Duration: 29 Oct 2019 → …
Conference number: 1
https://sites.google.com/view/nl4xai2019/

Workshop

Workshop1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence 2019
Abbreviated titleNL4XAI 2019
Country/TerritoryJapan
CityTokyo
Period29/10/19 → …
Internet address

Keywords / Materials (for Non-textual outputs)

  • explainable AI
  • black-box
  • NLG
  • theoretical issues
  • transparency
  • intelligibility
  • interpretability
  • explainability

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