Human-centered artificial intelligence in education: Seeing the invisible through the visible

Human-centered artificial intelligence in education: Seeing the invisible through the visible
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DOI：
10.1016/j.caeai.2021.100008
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发表时间：
2021
期刊：
Comput. Educ. Artif. Intell.
影响因子：
--
通讯作者：
Stephen J. H. Yang;H. Ogata;T. Matsui;N. Chen
Stephen J. H. Yang;H. Ogata;T. Matsui;N. Chen
中科院分区：
其他
文献类型：
--
作者：
Stephen J. H. Yang;H. Ogata;T. Matsui;N. Chen

文献摘要

相似文献

人工智能（AI）不可避免的兴起和发展并不是突然发生的。人工智能对人类的影响越大，我们就越迫切需要了解它。本文讨论了利用人工智能来评估新的设计方法和工具的研究，这些方法和工具可以用来推进人工智能研究、教育、政策和实践，以改善人类状况。人工智能有潜力教育、培训和提高人类的表现，使他们更好地完成任务和活动。人工智能的使用可以在许多方面提高人类福利，例如通过提高粮食、卫生、水、教育和能源服务的生产率。然而，由于算法偏见和缺乏治理而滥用人工智能可能会抑制人权，并导致就业、性别和种族不平等。我们设想人工智能可以演变为以人为中心的人工智能（HAI），即通过考虑人类的条件和背景，从人类的角度来看待人工智能。目前关于人工智能技术的大多数讨论都集中在人工智能如何使人类能够发挥作用。然而，我们探索人工智能也可以抑制人类状况，并倡导技术和人文研究人员之间的深入对话，以从不同角度提高对人工智能的理解。
The inevitable rise and development of artificial intelligence (AI) was not a sudden occurrence. The greater the effect that AI has on humans, the more pressing the need is for us to understand it. This paper addresses research on the use of AI to evaluate new design methods and tools that can be leveraged to advance AI research, education, policy, and practice to improve the human condition. AI has the potential to educate, train, and improve the performance of humans, making them better at their tasks and activities. The use of AI can enhance human welfare in numerous respects, such as through improving the productivity of food, health, water, education, and energy services. However, the misuse of AI due to algorithm bias and a lack of governance could inhibit human rights and result in employment, gender, and racial inequality. We envision that AI can evolve into human-centered AI (HAI), which refers to approaching AI from a human perspective by considering human conditions and contexts. Most current discussions on AI technology focus on how AI can enable human performance. However, we explore AI can also inhibit the human condition and advocate for an in-depth dialog between technology- and humanity-based researchers to improve understanding of HAI from various perspectives.