On Theoretical Deconstruction,Risk Generation and Unmask-ing Strategies for Ethical Misconduct of Generative Artificial Intelligence in Education
In the era of digital intelligence,generative artificial intelligence(AI)has become a significant cat-alyst for educational reform due to its robust capabilities in content creation and logical inference.However,this has also given rise to a series of ethical issues.This analysis deconstructs the ethical problems of gener-ative AI by examining its role as a new form of productive force throughout its entire life cycle,revealing the inherent technological and behavioral mechanisms involved:Algorithm design serves as the technical origin of ethical issues,training data acts as a regulatory intermediary,and real human agents are the behav-ioral subjects causing these ethical dilemmas.The ethical risks driven by generative AI in transforming edu-cation primarily manifest as risks in algorithm operation,data storage,content creation,and technology mis-use.Given that humans are the behavioral agents behind its ethical issues,addressing the ethical risks of generative AI necessarily involves returning to"human"fundamentals.Based on this,the study proposes that managing AI's ethical risks should focus on broadening AI knowledge to enhance educators'technical awareness,accelerating AI technology research and its application in education,and significantly improv-ing educators and students'AI literacy.This approach aims to ensure that the use of AI in education ad-heres to ethical standards.
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