The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid content analysis, and personalized feedback through machine learning and natural language processing. These advancements provide timely, consistent feedback and valuable insights into student performance, thereby enhancing the assessment experience. However, the deployment of AI in education also raises significant ethical concerns regarding validity, reliability, transparency, fairness, and equity. Issues such as algorithmic bias and the opacity of AI decision-making processes pose risks of perpetuating inequalities and affecting assessment outcomes. Responding to these concerns, various stakeholders, including educators, policymakers, and organizations, have developed guidelines to ensure ethical AI use in education. The National Council of Measurement in Education's Special Interest Group on AI in Measurement and Education (AIME) also focuses on establishing ethical standards and advancing research in this area. In this paper, a diverse group of AIME members examines the ethical implications of AI-powered tools in educational measurement, explores significant challenges such as automation bias and environmental impact, and proposes solutions to ensure AI's responsible and effective use in education.

翻译：人工智能（AI）在教育测量中的整合已彻底改变了评估方法，通过机器学习和自然语言处理实现了自动评分、快速内容分析和个性化反馈。这些进步为学生表现提供了及时、一致的反馈和宝贵见解，从而提升了评估体验。然而，AI在教育中的部署也引发了关于效度、信度、透明度、公平性与公正性的重大伦理关切。算法偏见和AI决策过程不透明等问题，可能导致不平等现象持续存在并影响评估结果的风险。针对这些关切，包括教育工作者、政策制定者和组织在内的多方利益相关者已制定指导方针，以确保AI在教育中的伦理使用。美国教育测量委员会下属的"测量与教育人工智能"特别兴趣小组（AIME）也致力于建立伦理标准并推动该领域的研究。本文汇集AIME成员的多元视角，审视AI驱动工具在教育测量中的伦理影响，探讨自动化偏见和环境影响等重大挑战，并提出确保AI在教育中负责任且有效应用的解决方案。