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<p>Emotion artificial intelligence (AI) technologies are increasingly being introduced into classrooms worldwide, using facial expression analysis and vocal tone analytics to monitor student affect and engagement. Schools and ed-tech companies are piloting systems that promise real-time feedback to teachers, for example, alerting them when students appear confused or disengaged, and adaptive learning experiences tuned to students’ emotional states. However, these developments raise complex ethical questions. This conceptual paper proposes a novel, pragmatic ethical framework for deploying Emotion AI in educational contexts, aiming to balance innovation with safeguarding student rights and well-being. We take a globally scoped perspective, examining international use cases ranging from AI-equipped classrooms in China to experimental pilots in the United States and Europe’s more precautionary regulatory stance. We integrate technical considerations (how these AI systems operate and their limitations), psychological insights (the impact on learning and student mental health), and policy analysis (privacy laws, consent requirements, and cultural norms) into a comprehensive discussion. Key ethical dimensions addressed include privacy and data governance, informed consent (especially for minors), algorithmic bias and fairness, the risk of misinterpreting emotions across diverse cultures, and potential misuse or unintended consequences of constant affective surveillance. Real-world scenarios illustrate both the promise and perils of Emotion AI: for instance, systems that boost student engagement through timely feedback versus dystopian visions of “Big Brother” monitoring every smile or frown. In response, we outline an actionable ethical model, grounded in principles of student autonomy, transparency, equity, and accountability, to guide stakeholders in the responsible implementation of emotional analytics in schools. A summary table of ethical considerations and a framework diagram facilitate practical understanding. Ultimately, this work offers a foundation for future research and policymaking at the intersection of education, AI, and ethics, emphasising that protecting students’ dignity and psychological safety must be paramount as we explore Emotion AI’s educational potential.</p>

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Emotion AI in the classroom: ethics of monitoring student affect through facial and vocal analytics

  • 期刊论文

  • 发表日期：

    2025年12月4日

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  • Seyed-Ali Sadegh-Zadeh,
  • Tahereh Movahhedi,
  • Fahimeh Bahonar

摘要

Emotion artificial intelligence (AI) technologies are increasingly being introduced into classrooms worldwide, using facial expression analysis and vocal tone analytics to monitor student affect and engagement. Schools and ed-tech companies are piloting systems that promise real-time feedback to teachers, for example, alerting them when students appear confused or disengaged, and adaptive learning experiences tuned to students’ emotional states. However, these developments raise complex ethical questions. This conceptual paper proposes a novel, pragmatic ethical framework for deploying Emotion AI in educational contexts, aiming to balance innovation with safeguarding student rights and well-being. We take a globally scoped perspective, examining international use cases ranging from AI-equipped classrooms in China to experimental pilots in the United States and Europe’s more precautionary regulatory stance. We integrate technical considerations (how these AI systems operate and their limitations), psychological insights (the impact on learning and student mental health), and policy analysis (privacy laws, consent requirements, and cultural norms) into a comprehensive discussion. Key ethical dimensions addressed include privacy and data governance, informed consent (especially for minors), algorithmic bias and fairness, the risk of misinterpreting emotions across diverse cultures, and potential misuse or unintended consequences of constant affective surveillance. Real-world scenarios illustrate both the promise and perils of Emotion AI: for instance, systems that boost student engagement through timely feedback versus dystopian visions of “Big Brother” monitoring every smile or frown. In response, we outline an actionable ethical model, grounded in principles of student autonomy, transparency, equity, and accountability, to guide stakeholders in the responsible implementation of emotional analytics in schools. A summary table of ethical considerations and a framework diagram facilitate practical understanding. Ultimately, this work offers a foundation for future research and policymaking at the intersection of education, AI, and ethics, emphasising that protecting students’ dignity and psychological safety must be paramount as we explore Emotion AI’s educational potential.