DOI: https://doi.org/10.61957/joerai-20240109

Title: Demystifying AI in Education: A Critical Review of Transparency, Ethical Implications, and Practical Applications in Gillani et al.'s 'Unpacking the Black Box

Author: Malik Saad Nawaz, Yanfang Fu1, Xiaojun Bai

Abstract

Artificial Intelligence (AI) is transforming education through technologies like intelligent tutoring systems, adaptive learning platforms, automated grading, and predictive analytics. These innovations promise personalized learning, enhanced instructional support, and administrative efficiency. However, the "black box" nature of AI, where decision-making processes are opaque, raises significant concerns about transparency, ethics, and equity. This review critically examines Gillani et al.'s exploration of these issues in their paper "Unpacking the 'Black Box' of AI in Education." The authors emphasize the necessity of explainable AI (XAI) to foster trust and ensure ethical use. They also discuss practical applications and case studies, such as Carnegie Learning's Mathia and Dream Box Learning, highlighting both the potential and challenges of AI in educational settings. This paper underscores the importance of transparency, fairness, and comprehensive stakeholder collaboration in developing AI systems that enhance educational opportunities while mitigating risks of bias and inequality. The review concludes with a call for continued research and thoughtful implementation to realize AI's full potential in education responsibly.
　

Keywords: Artificial intelligence (AI); Education; Transparency; Ethics; Explainable AI (XAI); Black box; Intelligent tutoring systems (ITS); Adaptive learning platforms (ALPs); Automated grading systems; Predictive analytics; Bias; Data privacy; Equity; Accessibility; Teacher support; Collaborative learning; Personalized learning; Machine learning; Deep learning; Algorithmic bias; Fairness; Educational technology