Defense Against the AI Dark Arts: Threat Assessment and Coalition Defense
The United States must now start working very hard with allies to secure democratic advantage in the domain of frontier AI
published by on December 4, 2024
Hoover Institution
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Artificial IntelligenceAs artificial intelligence (AI) changes how people around the world live and work, new frontiers for international collaboration, competition, and conflict are opening. AI can, for example, improve (or detract) from international cyber stability, optimize (or bias) cloud-based services, or guide the targeting of biotechnology toward great discoveries (or terrible abuses). Carnegie partners with governments, industry, academia, and civil society to anticipate and mitigate the international security challenges from AI. By confronting both the short-term (2-5 years) and medium-term (5-10 years) challenges, we hope to mitigate the most urgent risks of AI while laying the groundwork for addressing its slower and subtler effects.
Measuring Changes Caused by Generative Artificial Intelligence: Setting the FoundationsInformed policy that leads to beneficial change is extremely challenging to develop without being able to measure the material impacts of GenAI.
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China Decoupling Beyond the United States: Comparing Germany, Japan, and IndiaKey U.S. partners are moving toward less technological integration with China. But their specific paths diverge significantly based on domestic circumstances and varied relationships with Beijing.
- AI Has Been Surprising for Years
AI presents a challenge for policymakers: a large number of potential risks have not emerged yet, but could emerge quickly. A first step toward navigating this challenge is recognizing that artificial intelligence doesn’t have the sort of stable, well-understood limitations it used to.
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Southeast Asia’s developers have sought to democratize AI by building language models that better represent the region’s languages, worldviews, and values. Yet, language is deeply political in a region as multiculturally diverse and complex as Southeast Asia. Can localized large language models truly preserve and project the region’s nuances?
