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A Comparative Study on Ethics Guidelines for Artificial Intelligence Across Nations

机译:各国人工智能伦理伦理指南的比较研究

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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.
机译:本研究旨在调查各国AI研究与发展(研发)指南的共同性和差异。在更经济发达国家发布的AI研发指南上进行了内容分析,因为他们可以指导基于AI的教育申请的趋势。具体而言,本研究由三个阶段组成:1)信息检索,(2)关键期限提取,和(3)数据可视化。首先,采用Fisher的确切考验,以确保不同的AI研发指南(例如,美国,欧盟,日本,大陆和台湾)的不同之处在于。其次,开发了关键词提取系统以检索指南中的基本信息。第三,数据可视化技术在多个指南上对关键术语进行。一个词云在颜色编码方案表明差异(例如,在指南内的指导方针的关键期限及其频率发生在指南内的关键期限)中,揭示了指南中的相似性(例如,这些指导方针的关键术语。重要的是,三个关键术语,即人,人类和发展,被确定为跨指南的必要性。对于仅从特定指导方针提取的关键术语,有趣的是,具有颜色编码方案的结果表明这些关键术语的加权不同取决于国家的发展强调。集体,我们讨论了这些调查结果如何阐述揭示AI对教育技术的研究和开发。

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