A Comparative Study on Ethics Guidelines for Artificial Intelligence Across Nations

Tony Szu Hsien Lee, Shiang Yao Liu, Yin Ling Wei, Li Yun Chang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This study aimed to investigate the commonality and differences among AI research and development (R&D) guidelines across nations. Content analysis was conducted on AI R&D guidelines issued by more economically developed countries because they may guide the trend of AI-based applications in education. Specifically, this study consisted of three phases: 1) information retrieval, (2) key term extraction, and (3) data visualization. First, Fisher’s exact test was employed to ensure that different AI R&D guidelines (e.g., the latest ones in the US, EU, Japan, Mainland, and Taiwan) were comparable. Second, the Key Word Extraction System was developed to retrieve essential information in the guidelines. Third, data visualization techniques were performed on key terms across multiple guidelines. A word cloud revealed the similarity among guidelines (e.g., key terms that these guidelines share in common) while a color-coding scheme showed the differences (e.g., occurrence of a key term across guidelines and its frequency within a guideline). Importantly, three key terms, namely, AI, human, and development, are identified as essential commonality across guidelines. As for key terms that only extracted from particular guidelines, interestingly, results with the color-coding scheme suggested that these key terms were weighted differently depends on the developmental emphasis of a nation. Collectively, we discussed how these findings concerning ethics guidelines may shed light on AI research and development to educational technology.

Original languageEnglish
Title of host publicationInnovative Technologies and Learning - Third International Conference, ICITL 2020, Proceedings
EditorsTien-Chi Huang, Ting-Ting Wu, João Barroso, Frode Eika Sandnes, Paulo Martins, Yueh-Min Huang
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages7
ISBN (Print)9783030638849
Publication statusPublished - 2020
Event3rd International Conference on Innovative Technologies and Learning, ICITL 2020 - Porto, Portugal
Duration: 2020 Nov 232020 Nov 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12555 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on Innovative Technologies and Learning, ICITL 2020


  • Artificial intelligence
  • Data visualization technique
  • Education
  • Ethics guidelines
  • Text mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'A Comparative Study on Ethics Guidelines for Artificial Intelligence Across Nations'. Together they form a unique fingerprint.

Cite this