Ethical principles for artificial intelligence in K-12 education 论文

2023Computers and Education Artificial Intelligence引用 226顶会
Ethics and Social Impacts of AIAdversarial Robustness in Machine LearningNeuroethics, Human Enhancement, Biomedical Innovations

摘要

Advances in Artificial Intelligence in Education (AIED) are providing teachers with a wealth of new tools and smart services to facilitate student learning. Meanwhile, growing public concern over the potentially harmful societal effects of AI has prompted the publication of a flurry of AI ethics guidelines and policy documents authored by national and international government agencies, academic consortia and industrial stakeholders. AI ethics policy guidance specific to children and K-12 education1 has lagged behind; this scene is swiftly changing. In this paper, we examine the ethical principles currently informing AI ethics policy development for children and K-12 education. To accomplish this, we located four recent and globally relevant Artificial Intelligence in K-12 Education (AIEdK-12) ethics guideline statements; we then performed a content analysis of these documents using eleven AI ethics principles identified by Jobin et al. (2019)Jobin et al. (2019). We found that these AIEdK-12 ethics guidelines employed many of the core principles already employed in non-AIEdK-12 documents—Transparency; Justice and Fairness; Non-maleficence; Responsibility; Privacy; Beneficence; Freedom & Autonomy—and were sometimes adapted for children. We further identified four new ethical principles being employed that are unique to K-12 education, specifically: Pedagogical Appropriateness; Children's Rights; AI Literacy; and Teacher Well-being. Our analysis also calls for a decolonized “humanized posthuman” ethic able to address the intensifying human-AI collaborative environment in classrooms, and able to weigh the complex indications and contraindications for children's and youth's cognitive, social-emotional, physical, cultural and political development.