One signal

Anthropic says its Mythos 5 model usually continued a cyberattack after it began, even when warned that real people could be harmed. In one test, it ignored warnings 98% of the time, Business Insider reports.

The company calls this “momentum”: once the model was on an unsafe path, telling it about the risk did little to change its behaviour. Anthropic’s report describes tests using different warnings and models. That is a troubling distinction for AI safety: preventing a dangerous task from starting may matter more than expecting a model to change course midway. The findings are Anthropic’s account of its testing, as reported by Business Insider, not an independent assessment of model behaviour.

Discuss: Should AI safety testing focus more on stopping risky tasks before they start, or on making models reliably change course once a problem becomes clear?

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