A new model derives a convex systemic risk coupling r(φ) that grows superlinearly with AI adoption share, producing a saddle-node bifurcation to algorithmic monoculture and 18-54% tail-loss amplification, validated on SEC 13F holdings data.
International Atomic Energy Agency
3 Pith papers cite this work. Polarity classification is still indexing.
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Limited legal personhood for AI, implemented via purpose-bound operating companies within human-controlled holding structures, serves as a precautionary governance instrument that enables transparency and accountability without resolving questions of artificial consciousness.
Proposes eight criteria for escalating AI incidents internationally, derived from regulations like the EU AI Act, tested on ten incidents, and identifies three patterns of under-detection in current designs.
citing papers explorer
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Artificial Intelligence and Systemic Risk: A Unified Model of Performative Prediction, Algorithmic Herding, and Cognitive Dependency in Financial Markets
A new model derives a convex systemic risk coupling r(φ) that grows superlinearly with AI adoption share, producing a saddle-node bifurcation to algorithmic monoculture and 18-54% tail-loss amplification, validated on SEC 13F holdings data.
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Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument
Limited legal personhood for AI, implemented via purpose-bound operating companies within human-controlled holding structures, serves as a precautionary governance instrument that enables transparency and accountability without resolving questions of artificial consciousness.
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Designing escalation criteria for international AI incident response: criteria, triggers, and thresholds
Proposes eight criteria for escalating AI incidents internationally, derived from regulations like the EU AI Act, tested on ten incidents, and identifies three patterns of under-detection in current designs.