Invisible sources of contamination

Over 171 years ago, a contaminated water pump in Victorian London killed 616 people in a month because the poison was invisible to inspection, undetectable by the science of the era and absolutely trusted by those who consumed it. New leading edge research from the UK AISI, Anthropic and the Alan Turing Institute demonstrates that language models remain vulnerable to persistent backdoors inserted via minimal poisoned data, challenging the assumption that larger training datasets dilute poisoning effects. In addressing Cholera, the rapid emergence of symptoms provided an advantage, enabling epidemiological responses - in contrast, data poisoning can remain dormant, undetectable and potentially active over time. Both demand a safety response that focuses on source control as well as detection, yet many organisations approach AI security as a post-deployment challenge. Is your organisation asking the right questions about data provenance before crisis forces the conversation? Profiled research: Data Poisoning Attack Research: https://arxiv.org/abs/2510.07192; AI Red Teaming and Adaptive Attacks Against Defences: https://arxiv.org/abs/2510.09023; Control-Theoretic Approaches to AI Guardrails: https://arxiv.org/abs/2510.13727; EU AI Act Implementation Framework: https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence #AI #AISafety #AISecurity #AISovereignty #AIGovernance #ResponsibleAI #TrustworthyAI #AIStressTest #Learning #History #Technology #Innovation

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