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Abstract

The integration of artificial intelligence (AI) in educational measurement has transformed assessment methods, allowing for automated scoring, swift content analysis, and personalized feedback through machine learning and natural language processing. These advancements provide valuable insights into student performance while also enhancing the overall assessment experience. However, the implementation 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 risk perpetuating inequalities and affecting assessment outcomes. In response, various stakeholders, including educators, policymakers, and testing organizations, have developed guidelines to ensure the ethical use of AI in education. The National Council of Measurement in Education’s Special Interest Group on AI in Measurement and Education (AIME) is dedicated to 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.

DOI

https://doi.org/10.59863/MIQL7785

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