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This arXiv paper introduces Contingent Exposure Routing (CER), a framework for assigning displaced financial decisions across AI model endpoints during outages to minimize market-impact risk, showing that shared backups create concentration floors and that randomized routing strategies reduce exposure risk by 3.3-10.5% in synthetic and replayed scenarios.
A conversational video starts from an AI reverse-engineering an entire game, then extrapolates the ripple effects on software business models, aging infrastructure, and the global trust ecosystem — warning that when AI breaks the assumption that "complexity serves as a security barrier," a systemic collapse could follow.
The article argues that super AI poses systemic risks due to potential recursive self-improvement, while generative and agentic AI do not, warning that over-regulation based on super AI fears could incur economic costs.
This position paper argues that AI safety research must address AI Lock-In, the phenomenon where excessive reliance on AI leads to human deskilling and systemic vulnerabilities, and provides guidance on mitigation strategies.
This article explores the systemic risk posed by ideologically-driven founders in AI, using Anthropic as a case study, and draws parallels with historical tech leaders.
This paper develops a formal theory of cognitive debt, where using AI as a substitute for first-principles reasoning builds up unverified obligations that lead to systemic fragility and a cognitive Minsky moment, showing that decentralized equilibrium over-adopts substitutive AI without accounting for externalities.
This position paper argues that current AI paradigms are insufficient for addressing global systemic risks and proposes Planet-Centered AI (PCAI) as a new design philosophy that treats Earth's interconnected systems as first-class concerns.