Data Privacy and Security in AI-Driven Education Systems

Abstract

The integration of AI in education introduces profound ethical and operational challenges, particularly in legal compliance, regulatory frameworks, and institutional accountability. This chapter how AI-driven systems are associates with data privacy laws, intellectual property rights, and evolving regulations governing AI-generated content. It underscores the necessity for institutions to ensure transparency in student consent and align internal policies with legal mandates. The discussion emphasizes institutional accountability in mitigating algorithmic bias, addressing surveillance risks, and bridging gaps in ethical guidelines. Regulatory challenges, including compliance with fragmented global standards and resolving ambiguities in AI deployment, are analyzed alongside the role of institutions in fostering innovation while safeguarding equity and autonomy. By prioritizing legal adherence, regulatory agility, and institutional responsibility, this chapter advocates for frameworks that harmonize AI's potential with ethical imperatives in education.

Ähnliche Arbeiten