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Artificial intelligence (AI) has revolutionized educational technology (EdTech) platforms, offering innovative tools and personalized learning experiences. However, the integration of AI into EdTech also introduces significant risks that must be addressed. This study aims to systematically prioritize and evaluate these risks using the Analytic Hierarchy Process (AHP), a structured multi-criteria decision-making tool. Key risks identified include data privacy and security concerns, algorithmic bias and fairness issues, technical reliability and compatibility challenges, personalization and overreliance on AI, accessibility and equity risks, ethical and privacy concerns, operational and financial risks, governance and regulatory compliance risks, and the “black box” problem of lack of transparency in AI decision-making processes. Through an extensive literature review and expert inputs, the study employs the AHP methodology to capture the diverse dimensions of risk and determine their relative importance. The findings highlight technical reliability and compatibility (27.43%), the “black box” problem (17.31%), ethical concerns (17.29%), and personalization and overreliance on AI (17.25%) as the top-ranked risks. By identifying critical risk areas, this research informs the establishment of effective risk management strategies, ensuring the responsible and sustainable adoption of AI in EdTech platforms.

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Prioritizing Risks in AI-Enabled EdTech Platforms: An Analytic Hierarchy Process Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Ankita Priti Roy,
  • Kerena Anand,
  • N. Elangovan,
  • D. Halaswamy

摘要

Artificial intelligence (AI) has revolutionized educational technology (EdTech) platforms, offering innovative tools and personalized learning experiences. However, the integration of AI into EdTech also introduces significant risks that must be addressed. This study aims to systematically prioritize and evaluate these risks using the Analytic Hierarchy Process (AHP), a structured multi-criteria decision-making tool. Key risks identified include data privacy and security concerns, algorithmic bias and fairness issues, technical reliability and compatibility challenges, personalization and overreliance on AI, accessibility and equity risks, ethical and privacy concerns, operational and financial risks, governance and regulatory compliance risks, and the “black box” problem of lack of transparency in AI decision-making processes. Through an extensive literature review and expert inputs, the study employs the AHP methodology to capture the diverse dimensions of risk and determine their relative importance. The findings highlight technical reliability and compatibility (27.43%), the “black box” problem (17.31%), ethical concerns (17.29%), and personalization and overreliance on AI (17.25%) as the top-ranked risks. By identifying critical risk areas, this research informs the establishment of effective risk management strategies, ensuring the responsible and sustainable adoption of AI in EdTech platforms.