August 11, 2025
AI Governance AI Safety
Today, I began Unit 1: How AI Systems Work of the BlueDot AI Governance course. Below is the resource I explored.
Resource: The AI Triad and What It Means for National Security Strategy
- Source: The AI Triad and What It Means for National Security Strategy by Ben Buchanan, Center for Security and Emerging Technology (CSET), August 2020.
- Summary: This paper introduces the “AI Triad” framework—algorithms, data, and computing power—to explain modern machine learning and its implications for national security. It describes algorithms as instructions for processing information, covering supervised learning (predicting outcomes from labeled data), unsupervised learning (finding patterns in unorganized data), and reinforcement learning (learning through trial and error). Data is critical for training AI systems, particularly for supervised learning, but requires careful management to avoid bias and address privacy concerns. Computing power is highlighted as a key driver of AI progress, with a 300,000-fold increase in compute used for top AI projects from 2012 to 2018. The paper connects these components to national security applications, such as analyzing drone footage, targeting propaganda, and powering autonomous military vehicles. It also discusses policy levers like talent recruitment for algorithms, privacy regulations for data, and export controls for compute.
