Proceedings of The second international workshop on eXplainable AI for the Arts (XAIxArts)
Nick Bryan-Kinns, Corey Ford, Shuoyang Zheng, Helen Kennedy, Alan Chamberlain, Makayla Lewis, Drew Hemment, Zijin Li, Qiong Wu, Lanxi Xiao, Gus Xia, Jeba Rezwana
arXiv:2406.14485v8
Originality Synthesis-oriented
AI Analysis
It addresses the need for explainability in AI systems used in creative domains, but is incremental as it reports on a community event rather than presenting new research findings.
This paper describes a workshop that convened researchers from multiple fields to explore the application of explainable AI (XAI) in the arts, focusing on its role and implications.
This second international workshop on explainable AI for the Arts (XAIxArts) brought together a community of researchers in HCI, Interaction Design, AI, explainable AI (XAI), and digital arts to explore the role of XAI for the Arts. Workshop held at the 16th ACM Conference on Creativity and Cognition (C&C 2024), Chicago, USA.