Ethical AIED and AIED Ethics: Toward Synergy Between AIED Research and Ethical Frameworks

被引:0
作者
Borchers, Conrad [1 ]
Liu, Xinman [2 ]
Lee, Hakeoung Hannah [3 ]
Zhang, Jiayi [4 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[2] Univ Cambridge, Cambridge, England
[3] Univ Texas Austin, Austin, TX 78712 USA
[4] Univ Penn, Philadelphia, PA 19104 USA
来源
ARTIFICIAL INTELLIGENCE IN EDUCATION: POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS, DOCTORAL CONSORTIUM AND BLUE SKY, AIED 2024, PT I | 2024年 / 2150卷
关键词
ethics; bias; fairness; equity; representation; design; justice; reflexivity;
D O I
10.1007/978-3-031-64315-6_2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Ethical issues matter for artificial intelligence in education (AIED). Simultaneously, there is a gap between fundamental ethical critiques of AIED research goals and research practices doing ethical good. This article discusses the divide between AIED ethics (i.e., critical social science lenses) and ethical AIED (i.e., methodologies to achieve ethical goals). This discussion contributes paths toward informing AIED research through its fundamental critiques, including improving researcher reflexivity in developing AIED tools, describing desirable futures for AIED through co-design with marginalized voices, and evaluation methods that merge quantitative measurement of ethical soundness with co-design methods. Prioritizing a synthesis between AIED ethics and ethical AIED could make our research community more resilient in the face of rapidly advancing technology and artificial intelligence, threatening public interest and trust in AIED systems. Overall, the discussion concludes that prioritizing collaboration with marginalized stakeholders for designing AIED systems while critically examining our definitions of representation and fairness will likely strengthen our research community.
引用
收藏
页码:18 / 31
页数:14
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