Ethical Implications of AI

Abstract

Artificial intelligence in education has changed the learning process by enabling personalised instruction, adaptive assessments, and intelligent tutoring systems. Yet AI in education also raises enormous ethical concerns, particularly around issues of algorithmic bias and fairness. This chapter examines the ethical implications of AI in education, focusing on the understanding and mitigation of algorithmic bias. The following section gives an overview of the types and sources of bias in AI systems, strategies for the detection and mitigation of bias, important aspects concerning algorithmic fairness in educational contexts. It outlines approaches that need to be taken in the near future in order to further enhance fairness in AI-powered education. It also examines possibilities of useful biases in AI and makes a case for a shared framework that may help achieve responsible AI implementation in higher education.

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