The article argues that recent executive overreach and politicization have severely undermined established norms of U.S. civil-military relations. To restore professional standards, the incoming Congress must actively exercise its oversight powers, moving beyond mere criticism to demanding transparency in defense policy and personnel decisions. Key reforms include enforcing meritocratic promotion processes, requiring documented justification for senior officer removals, and preventing the partisan use of the military. These actions are crucial for bolstering public trust and ensuring the military remains a nonpartisan instrument of civilian control.
Operational reliance on AI in supply chains and emerging insurance risks
English Summary
The widespread operational embedding of AI in global supply chains creates significant systemic dependencies on shared digital infrastructure, raising novel aggregation risks for the insurance market. These risks are not limited to model failure but stem from common vulnerabilities—such as shared cloud platforms or flawed models—that could simultaneously impact multiple seemingly independent firms. Policy implications require both operators and insurers to shift focus toward managing these interconnected weaknesses by establishing robust controls, including mandatory human oversight, detailed audit trails, and staged deployments. Insurers must update underwriting practices to map systemic technology dependencies across policyholders rather than treating AI exposure as a standalone risk.
中文摘要
人工智慧（AI）在全球供應鏈中廣泛的營運嵌入，使得各方對共享數位基礎設施產生了重大的系統性依賴。這為保險市場帶來了新型態的聚集風險。這些風險不僅限於模型故障，更源自於共同的脆弱點——例如共用的雲端平台或有缺陷的模型——這些弱點可能同時影響多個看似獨立的公司。政策層面的啟示要求營運方和保險業雙方必須將重點轉向管理這些相互關聯的弱點，方法是建立穩健的控制機制，包括強制性的人工監督、詳盡的稽核追蹤路徑（audit trails）以及分階段部署。保險公司必須更新其承保實務，使其能夠繪製出跨政策持有人的系統性技術依賴圖譜，而非將AI風險視為孤立的單一風險。
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