Explainable AI for the Arts: XAIxArts

Nick Bryan-Kinns, Corey Ford, Alan Chamberlain, Steven David Benford, Helen Kennedy, Zijin Li, Wu Qiong, Gus G. Xia, Jeba Rezwana

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

11 Citations (Scopus)

Abstract

This first workshop on explainable AI for the Arts (XAIxArts) brings together a community of researchers and creative practitioners in Human-Computer Interaction (HCI), Interaction Design, AI, explainable AI (XAI), and Digital Arts to explore the role of XAI for the Arts. XAI is a core concern of Human-Centred AI and relies heavily on HCI techniques to explore how complex and difficult to understand AI models such as deep learning techniques can be made more understandable to people. However, XAI research has primarily focused on work-oriented and task-oriented explanations of AI and there has been little research on XAI for creative domains such as the Arts. This workshop will: i) build an XAIxArts research community; ii) map out the current and future possible landscapes of XAIxArts; iii) critically reflect on the potential of XAI for the Arts, forming the basis for an edited book on XAIxArts and an international network of researchers.

Original languageEnglish
Title of host publicationC and C 2023 - Proceedings of the 15th Conference on Creativity and Cognition
PublisherAssociation for Computing Machinery
Pages1-7
Number of pages7
ISBN (Electronic)9781450383769
DOIs
Publication statusPublished - 19 Jun 2023
Event15th Conference on Creativity and Cognition, C and C 2023 - Virtual, Online
Duration: 19 Jun 202321 Jun 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference15th Conference on Creativity and Cognition, C and C 2023
CityVirtual, Online
Period19 Jun 202321 Jun 2023

Keywords

  • Artificial Intelligence (AI)
  • arts
  • explainable AI (XAI)
  • generative arts
  • Human-Computer Interaction (HCI)
  • Interaction Design

Fingerprint

Dive into the research topics of 'Explainable AI for the Arts: XAIxArts'. Together they form a unique fingerprint.

Cite this