Trust and Ethics for Artificial Intelligence in Authentic Education

Abstract

The integration of Artificial Intelligence (AI) into authentic assessment has generated renewed ethical concerns in higher education. This study examined teachers’ and students’ perceptions of the ethical dimensions of AI tools used in authentic assessment, focusing on trustworthiness, transparency, fairness, and human oversight. Guided by the Ethics of AI in Education framework proposed by Holmes et al. (2022), the study employed a quantitative descriptive design using a Likert-scale survey administered to faculty members and students. Descriptive statistics, including means and standard deviations, were used to analyze perceptions across ethical domains. Results indicate that both groups perceived the ethical use of AI in authentic assessment at a moderate extent, with faculty members consistently reporting higher levels of trust, fairness, and confidence in human oversight than students. Students expressed more cautious views, particularly regarding the trustworthiness and transparency of AI-generated feedback and scoring. The findings suggest that while AI is generally accepted as a support tool in assessment, ethical concerns persist, underscoring the need for clearer transparency mechanisms, strengthened fairness safeguards, and visible human oversight. The study contributes empirical evidence to ethical AI discourse in education and offers insights for higher education institutions seeking to integrate AI into authentic assessment while preserving trust, integrity, and pedagogical authenticity

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