What is it about?

Purpose: This study investigates the ethical, practical, and educational implications of integrating artificial intelligence (AI) into language education. The focus is on identifying the challenges of algorithmic bias, data privacy, inclusivity, and the impact on teacher-student dynamics, aiming to provide insights that can guide the responsible and effective use of AI in education. Findings: The research reveals that algorithmic bias poses a significant threat to educational equity, potentially perpetuating existing inequalities. Data privacy concerns are prevalent, necessitating strict regulatory measures. Inclusivity remains a challenge, with AI risks widening the educational gap between socioeconomic groups. Additionally, the study highlights the potential erosion of the teacher-student relationship due to over-reliance on AI, which could undermine the human elements crucial to the learning process. Design/Methodology/Approach: The study employs a qualitative research methodology, utilizing thematic analysis to explore literature, case studies, and expert interviews. This approach allows for an in-depth understanding of the multifaceted issues surrounding AI in language education and provides a nuanced perspective on its implications. Originality/Value: This research contributes to the emerging discourse on AI in education by addressing the often-overlooked ethical and social dimensions. It offers a unique perspective by examining the intersection of AI with cultural and socioeconomic factors, providing valuable insights for educators, policymakers, and AI developers.

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Why is it important?

The research reveals that algorithmic bias poses a significant threat to educational equity, potentially perpetuating existing inequalities. Data privacy concerns are prevalent, necessitating strict regulatory measures. Inclusivity remains a challenge, with AI risks widening the educational gap between socioeconomic groups. Additionally, the study highlights the potential erosion of the teacher-student relationship due to over-reliance on AI, which could undermine the human elements crucial to the learning process

Perspectives

The research reveals that algorithmic bias poses a significant threat to educational equity, potentially perpetuating existing inequalities. Data privacy concerns are prevalent, necessitating strict regulatory measures. Inclusivity remains a challenge, with AI risks widening the educational gap between socioeconomic groups. Additionally, the study highlights the potential erosion of the teacher-student relationship due to over-reliance on AI, which could undermine the human elements crucial to the learning process

Dr. Dwi Mariyono
Universitas Islam Malang

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This page is a summary of: Navigating Ethical Dilemmas in AI-Enhanced Language Education: Addressing Bias and Ensuring Inclusivity, January 2024, Elsevier,
DOI: 10.2139/ssrn.4936530.
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