Grounded in interdisciplinary scholarship, this work integrates insights from AI ethics, educational theory, organizational leadership, and global policy to offer a comprehensive framework for navigating the challenges and opportunities of AI in academia. From historical origins and evolving paradigms of AI to empirical studies on AI-driven pedagogy, the book rigorously addresses academic integrity, bias, and equity concerns while illuminating case studies of institutions already leading the way.
Adapt or Obsolete not only analyzes key frameworks like UNESCO's AI guidelines, the IEEE Ethically Aligned Design, and the EU AI Act, but also critiques their practical limitations in academic contexts. It proposes evidence-based strategies for designing AI education policies, faculty training programs, and ethical curricula that foster digital literacy, critical thinking, and human-centered innovation.
This is an essential resource for university administrators, educators, policymakers, and researchers seeking to understand the imperatives of ethical AI adoption and how to position their institutions for sustainable, values-aligned technological advancement.
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