Georgetown University
Ver recurso originalGeorgetown University's SEST5734 course guide serves as a curated gateway into the complex intersection of artificial intelligence and national security policy. This academic resource stands out by bridging theoretical AI governance frameworks with practical national security applications, drawing heavily from the Brookings Institution's AIET Initiative research on governing transformative technologies. Rather than offering a single perspective, the guide synthesizes insights from multiple research programs to present a comprehensive view of how AI governance approaches are evolving in the national security context.
The course guide introduces students to the multifaceted challenges of governing AI in national security settings. You'll explore how traditional security paradigms are being challenged by AI's dual-use nature, where the same technologies can enhance both defensive capabilities and offensive threats. The resource emphasizes understanding governance approaches that can handle AI's rapid development cycle while maintaining democratic oversight and international cooperation frameworks.
Key learning areas include:
This Georgetown resource differs from typical policy briefs or think tank reports by providing structured academic scaffolding around AI governance research. The course guide format means you get not just the conclusions, but the analytical frameworks used to reach them. The connection to Brookings' AIET Initiative adds particular value, as this initiative specifically focuses on technologies with transformative potential rather than incremental improvements.
The academic setting also enables deeper exploration of contested concepts like "AI safety" and "beneficial AI" within national security contexts, where the stakes and trade-offs differ significantly from commercial AI development.
The guide's approach to policy research emphasizes cross-program synthesis, drawing from multiple research streams rather than promoting a single institutional viewpoint. This methodology reflects the reality that AI governance challenges don't fit neatly into traditional academic or policy silos. The resource helps you understand how different research programs - from computer science to international relations to public policy - contribute to comprehensive AI governance frameworks.
Publicado
2024
Jurisdicción
Estados Unidos
CategorÃa
Research and academic references
Acceso
Acceso público
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