Navigating the Ethics of AI in Assessment: A Data Governance-Centered Approach

Mary K. Thompson & Dan Voeks   |    Volume 21 Issue 3  |   

This article examines the ethical complexities introduced by artificial intelligence (AI) and teaching and learning data in higher education assessment. Although AI technologies provide increasingly granular insights into student learning and institutional effectiveness, they also intensify concerns related to privacy, fairness, transparency, and accountability, issues that directly shape assessment design, data use, and reporting decisions. Existing literature identifies broad agreement on ethical principles but reveals persistent gaps in their operationalization, leaving assessment professionals to navigate consequential choices without clear or consistent guidance. In response, this paper advances a data governance centered approach, conceptualizing data governance as a decision-making infrastructure rather than a purely technical function to support assessment professionals in making ethically informed, defensible decisions about data use while aligning practice with institutional responsibilities to students and other stakeholders.

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