A conceptual ethical framework to preserve natural human presence in the use of AI systems in education.

IF 4.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Frontiers in Artificial Intelligence Pub Date : 2025-01-21 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1377938
Werner Alexander Isop
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Abstract

In recent years, there has been a remarkable increase of interest in the ethical use of AI systems in education. On one hand, the potential for such systems is undeniable. Used responsibly, they can meaningfully support and enhance the interactive process of teaching and learning. On the other hand, there is a risk that natural human presence may be gradually replaced by arbitrarily created AI systems, particularly due to their rapidly increasing yet partially unguided capabilities. State-of-the-art ethical frameworks suggest high-level principles, requirements, and guidelines, but lack detailed low-level models of concrete processes and according properties of the involved actors in education. In response, this article introduces a detailed Unified Modeling Language (UML)-based ancillary framework that includes a novel set of low-level properties. Whilst not incorporated in related work, particularly the ethical behavior and visual representation of the actors are intended to improve transparency and reduce the potential for misinterpretation and misuse of AIS. The framework primarily focuses on school education, resulting in a more restrictive model, however, reflects on potentials and challenges in terms of improving flexibility toward different educational levels. The article concludes with a discussion of key findings and implications of the presented framework, its limitations, and potential future research directions to sustainably preserve natural human presence in the use of AI systems in education.

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在教育领域使用人工智能系统时保护人类自然存在的概念性伦理框架。
近年来,人们对人工智能系统在教育中的伦理应用的兴趣显著增加。一方面,这种系统的潜力是不可否认的。负责任地使用,它们可以有意义地支持和加强教与学的互动过程。另一方面,自然的人类存在可能会逐渐被任意创建的人工智能系统所取代,特别是由于它们快速增长但部分无引导的能力。最先进的道德框架提出了高层次的原则、要求和指导方针,但缺乏具体过程的详细的低层模型和教育中相关行为者的相应属性。作为回应,本文介绍了一个详细的基于统一建模语言(UML)的辅助框架,其中包括一组新颖的低级属性。虽然没有纳入相关工作,但特别是行为者的道德行为和视觉表现旨在提高透明度,减少对AIS的误解和滥用的可能性。该框架主要关注学校教育,导致了一个更严格的模型,然而,在提高不同教育水平的灵活性方面反映了潜力和挑战。文章最后讨论了所提出的框架的主要发现和影响,其局限性以及在教育中使用人工智能系统时可持续地保护自然人类存在的潜在未来研究方向。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
期刊最新文献
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