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New framework quantifies AI harms in critical infrastructure systems

By PulseAugur Editorial · [1 sources] ·

A new research paper proposes a framework to quantify the system-level harms that can arise from integrating AI into complex sociotechnical systems, such as Critical National Infrastructure. The proposed method connects structured hazard analysis, component-level testing, and probabilistic system modeling to assess the impact of AI failures on overall system risk. An application to the UK's Real Time Gross Settlement system demonstrated how adversarial manipulation of AI trading recommendations could lead to increased bank failures and financial contagion. AI

IMPACT Provides a method to assess the systemic risks of AI in critical infrastructure, enabling better governance and mitigation strategies.

RANK_REASON The cluster contains an academic paper detailing a new framework for AI safety research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework quantifies AI harms in critical infrastructure systems

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44 / 100
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The cluster contains an academic paper detailing a new framework for AI safety research. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, safety, policy
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Paul Vautravers, Oliver Chalkley, Gabriel Downer, Kate S, Damian Ruck ·

    Quantifying System-Level Harms from AI Adoption in Complex Sociotechnical Systems

    arXiv:2608.23906v1 Announce Type: new Abstract: Artificial Intelligence (AI) is increasingly integrated into complex sociotechnical systems, including Critical National Infrastructure (CNI), where harms emerge from interactions between technical, human, and organisational element…

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