发表机构
Centre for Digital Music, Queen Mary University of London; Creative Computing Institute, University of the Arts London（伦敦玛丽女王大学数字音乐中心; 伦敦艺术大学创意计算学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究从物质能动性视角探讨可解释人工智能，提出物质可解释性，通过构建资源库案例研究，在音乐界面设计中探索神经音频模型，还给出在艺术实践中探索人工智能为材料的建议，以启发未来面向艺术家的可解释人工智能设计。
AI 中文摘要
近期人机交互（HCI）工作越来越将人工智能模型视为具有独特计算属性以塑造设计工件的设计材料。艺术家通过与模型“玩耍”来探索其新兴属性。在此观点下，可解释性旨在使一个制作和破解空间可见，以实现与人工智能的持续创造性实践。在本章中，我们提出物质可解释性，作为一系列将人工智能模型转变为艺术家、设计师和制作者工作空间中可及且包容的设计材料的活动和工件。我们展示了一个构建资源库的案例研究，以在音乐表达新界面（NIME）设计中实现对神经音频模型的艺术探索。反思我们的社区建设历程以及与一群艺术家制作一系列音乐界面设计的过程，我们提出了三条关于在艺术实践中实现将人工智能作为材料进行探索的建议，以启发未来面向艺术家的可解释人工智能设计。
英文摘要
Recent work in Human-Computer Interaction (HCI) increasingly treats AI models as design materials that have distinctive computational properties to shape design artifacts. Artists learn to work with the model "at play" to explore their emerging properties. The aim of explainability, in this view, is to make visible a crafting and hacking space to enable sustained creative practices with AI. In this chapter, we propose material explainability as a range of activities and artifacts that transform AI models into accessible and inclusive design materials in the workspace of artists, designers, and makers. We present a case study of building a repository of resources to enable artistic explorations of neural audio models in New Interfaces for Musical Expression (NIME) design. Reflecting on our community-building journey and the making of a collection of musical interface designs with a group of artists, we raise three recommendations on enabling the exploration of AI as materials in artistic practices to inspire future XAI design for artists.
CommentsUnder review for "Explainable AI for the Arts" (N. Bryan-Kinns, Ed.), Springer
