Experiential AI: Between Arts and Explainable AI

被引:0
|
作者
Hemment, Drew [1 ]
Murray-Rust, Dave [2 ]
Belle, Vaishak [3 ]
Aylett, Ruth [4 ]
Vidmar, Matjaz [5 ]
Broz, Frank [6 ]
机构
[1] Univ Edinburgh, Edinburgh Coll Arts, Edinburgh EH39DF, Scotland
[2] Delft Univ Technol, Fac Ind Design Engn, NL-2628 Delft, Netherlands
[3] Univ Edinburgh, Sch Informat, Edinburgh EH89AB, Scotland
[4] Heriot Watt Univ, Sch Math & Comp Sci, Edinburgh EH144AS, Scotland
[5] Univ Edinburgh, Sch Engn, Edinburgh EH93FB, Scotland
[6] Delft Univ Technol, Dept Intelligent Syst, NL-2628 Delft, Netherlands
基金
英国艺术与人文研究理事会; 英国工程与自然科学研究理事会;
关键词
D O I
10.1162/leon_a_02524
中图分类号
J [艺术];
学科分类号
13 ; 1301 ;
摘要
Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability and methodology to support, deepen, and extend those contributions.
引用
收藏
页码:298 / 308
页数:10
相关论文
共 50 条
  • [1] Explainable AI for the Arts: XAIxArts
    Bryan-Kinns, Nick
    Ford, Corey
    Chamberlain, Alan
    Benford, Steve
    Kennedy, Helen
    Li, Zijin
    Qiong, Wu
    Xia, Gus
    Rezwana, Jeba
    2023 PROCEEDINGS OF THE 15TH CONFERENCE ON CREATIVITY AND COGNITION, C&C 2023, 2023, : 1 - 7
  • [2] Reflections on Explainable AI for the Arts (XAIxArts)
    Bryan-Kinns N.
    Interactions (N.Y.), 2024, 31 (01) : 43 - 47
  • [3] Explainable AI for the Arts 2 (XAIxArts2)
    Bryan-Kinns, Nick
    Ford, Corey
    Zheng, Shuoyang
    Kennedy, Helen
    Chamberlain, Alan
    Lewis, Makayla
    Hemment, Drew
    Li, Zijin
    Wu, Qiong
    Xiao, Lanxi
    Xia, Gus
    Rezwana, Jeba
    Clemens, Michael
    Vigliensoni, Gabriel
    PROCEEDINGS OF THE 16TH CONFERENCE ON CREATIVITY AND COGNITION, C&C 2024, 2024, : 86 - 92
  • [4] Is explainable AI responsible AI?
    Taylor, Isaac
    AI & SOCIETY, 2024,
  • [5] Explainable AI
    Veerappa, Manjunatha
    Rinzivillo, Salvo
    ERCIM NEWS, 2023, (134):
  • [6] Explainable AI
    Anna, Monreale
    ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT, 2019, 319 : 5 - 5
  • [7] Explainable AI
    Schmid, Ute
    Wrede, Britta
    KUNSTLICHE INTELLIGENZ, 2022, 36 (3-4): : 207 - 210
  • [8] Explainable AI
    Ute Schmid
    Britta Wrede
    KI - Künstliche Intelligenz, 2022, 36 : 207 - 210
  • [9] Explainable AI
    Matsuo T.
    Todoriki M.
    Tago S.-I.
    Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers, 2020, 74 (01): : 30 - 34
  • [10] From "Explainable AI" to "Graspable AI"
    Ghajargar, Maliheh
    Bardzell, Jeffrey
    Renner, Alison Smith
    Krogh, Peter Gall
    Hook, Kristina
    Cuartielles, David
    Boer, Laurens
    Wiberg, Mikael
    PROCEEDINGS OF THE FIFTEENTH INTERNATIONAL CONFERENCE ON TANGIBLE, EMBEDDED, AND EMBODIED INTERACTION, TEI 2021, 2021,