Explainable AI for the metaverse: A Short Survey

被引:0
|
作者
Selvi, Chemmalar G. [1 ]
Yenduri, Gokul [1 ]
Srivastava, Gautam [2 ]
Ramalingam, M. [1 ]
Reddy, Dasaradharami K. [1 ]
Uzair, Muhammad [4 ]
Gadekallu, Thippa Reddy [3 ]
机构
[1] Vellore Inst Technol, Vellore, Tamil Nadu, India
[2] Brandon Univ, Dept Math & Comp Sci, Brandon, MB R7A 6A9, Canada
[3] Lebanese Amer Univ, Dept Elect & Comp Engn, Byblos, Lebanon
[4] Univ Tartu, Inst Comp Sci, Tartu, Estonia
关键词
Explainable Artificial Intelligence; Virtual Reality; Augmented Reality; Virtual world; immersive environment;
D O I
10.1109/iMETA59369.2023.10294907
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Virtual reality, augmented reality, and immersive technologies have advanced rapidly, giving rise to the concept of the metaverse. As users delve into these virtual environments, it becomes crucial to understand the decision-making processes of intelligent systems within the metaverse. Explainable AI (XAI) provides a framework for interpreting and understanding the outcomes of artificial intelligence, making it an essential component for ensuring transparency, trust, and user engagement within the metaverse. This paper aims to explore the fusion of XAI in the context of the metaverse, including key enabling technologies, the impact of XAI on metaverse applications, integration challenges, and future directions.
引用
收藏
页码:182 / 187
页数:6
相关论文
共 50 条
  • [21] Explainable AI (XAI) in Smart Grids for Predictive Maintenance: A survey
    Onu, Peter
    Pradhan, Anup
    Madonsela, Nelson Sizwe
    [J]. 2024 1ST INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND ARTIFICIAL INTELLIGENCE, SESAI 2024, 2024, : 12 - 17
  • [22] Explainable AI
    Schmid, Ute
    Wrede, Britta
    [J]. KUNSTLICHE INTELLIGENZ, 2022, 36 (3-4): : 207 - 210
  • [23] Explainable Generative AI (GenXAI): a survey, conceptualization, and research agenda
    Schneider, Johannes
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2024, 57 (11)
  • [24] Explainable AI
    Matsuo, Tatsuru
    Todoriki, Masaru
    Tago, Shin-Ichiro
    [J]. Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers, 2020, 74 (01): : 30 - 34
  • [25] Explainable AI
    Ute Schmid
    Britta Wrede
    [J]. KI - Künstliche Intelligenz, 2022, 36 : 207 - 210
  • [26] Is explainable AI responsible AI?
    Taylor, Isaac
    [J]. AI & SOCIETY, 2024,
  • [27] A Survey of Data-Driven and Knowledge-Aware eXplainable AI
    Li, Xiao-Hui
    Cao, Caleb Chen
    Shi, Yuhan
    Bai, Wei
    Gao, Han
    Qiu, Luyu
    Wang, Cong
    Gao, Yuanyuan
    Zhang, Shenjia
    Xue, Xun
    Chen, Lei
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 34 (01) : 29 - 49
  • [28] Explainable AI in Manufacturing and Industrial Cyber-Physical Systems: A Survey
    Moosavi, Sajad
    Farajzadeh-Zanjani, Maryam
    Razavi-Far, Roozbeh
    Palade, Vasile
    Saif, Mehrdad
    [J]. ELECTRONICS, 2024, 13 (17)
  • [29] Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security
    Ali, Sikandar
    Abdullah, Tagne Poupi Theodore
    Armand, Tagne Poupi Theodore
    Athar, Ali
    Hussain, Ali
    Ali, Maisam
    Yaseen, Muhammad
    Joo, Moon-Il
    Kim, Hee-Cheol
    [J]. SENSORS, 2023, 23 (02)
  • [30] Diagnosing Cataracts in the Digital Age: A Survey on AI, Metaverse, and Digital Twin Applications
    Jones, Aida
    Vijayan, Thulasi Bai
    John, Sheila
    [J]. SEMINARS IN OPHTHALMOLOGY, 2024,