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Security, Privacy, and Ethical Considerations in AI-Powered Academic Collaboration
Abstract
As AI-driven platforms reshape how scholars collaborate, new ethical, security, and privacy concerns have come to the forefront. This chapter explores the complex terrain of AI-powered academic collaboration, where the promise of efficiency and connectivity often coexists with heightened risks of data misuse, surveillance, and opaque decision-making. Drawing from current case studies and theoretical frameworks, we examine how personal data, intellectual property, and academic freedom are being redefined in this new landscape. Particular attention is given to how algorithmic bias and ethical blind spots may undermine equity and trust within global academic networks. We also explore institutional responsibilities and the emerging frameworks guiding the responsible use of AI in higher education. Ultimately, this chapter advocates for a careful, values-driven approach to technological integration—one that champions transparency, inclusivity, and the safeguarding of academic integrity in an era of unprecedented digital interdependence.
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