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The role of knowledge graph on responsible AI realization: research opportunities, gaps and challenges


Li, Xiang and Liu, Q and Bai, Q and Xu, X, The role of knowledge graph on responsible AI realization: research opportunities, gaps and challenges, Computer pp. 2-11. ISSN 1558-0814 (2023) [Refereed Article]

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DOI: doi:10.1109/MC.2022.3227580


As the development of AI algorithms the performance of AI systems has been largely improved. It, in turn, extends AI-empowered applications and makes AI play an increasingly important role in humans’ life. Thus, building Responsible AI which can be trusted by human has drawn much research attention in recent years. Linking various studies on Responsible AI through commonly accepted ethical values facilitates realizing it in the practice of designing, developing and deploying AI systems. Knowledge graph, as its advanced representation capability on facts and knowledge, can be used to represent and link heterogeneous information to support realizing Responsible AI. In this work, we reveal that knowledge graph brings opportunities for representing and processing unstructured information in legal documents, AI systems, and human interaction. Meanwhile, we intend to identify research gaps and challenges to smooth the future work.

Item Details

Item Type:Refereed Article
Keywords:knowledge graph, knowledge representation, responsible AI
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Knowledge representation and reasoning
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Computer systems
UTAS Author:Li, Xiang (Ms Xiang Li)
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:154604
Year Published:2023
Deposited By:Information and Communication Technology
Deposited On:2022-12-14
Last Modified:2023-01-30

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