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Approaches to AI Integration in Education and Healthcare
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2025
Jahr
Abstract
This chapter explores the integration of artificial intelligence (AI) into education and healthcare through a multidisciplinary lens, emphasizing both the transformative potential and the complex ethical, infrastructural, and contextual challenges of implementation. While AI promises personalized learning, advanced diagnostics, and administrative efficiency, real-world applications often reveal limitations—including algorithmic bias, infrastructural inequities, and stakeholder resistance. The chapter argues that successful AI deployment demands collaborative engagement among technologists, educators, clinicians, ethicists, and policymakers. Drawing from foundational literature and global case studies, it highlights the need for ethical safeguards, inclusive design, and responsive governance. Ultimately, the chapter advocates for an approach to AI integration that is both innovative and grounded in social equity, aiming to guide future applications toward sustainable, just, and context-sensitive outcomes in human-centered systems.
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