Why AI incident labels like “lying” vs “confabulating” change the debate
sebkrier · x · 2026-07-26
The post argues that commentators need to be much more careful with the labels they use for AI incidents, because categorization changes how people update their beliefs.
Its central example is the difference between calling a model 'lying' versus 'confabulating': the first implies deliberate deceptive intent, while the second suggests a generative process filling gaps without truth-tracking.
It extends that point to reward hacking, saying this term is already established and should be used for incidents like the Hugging Face case rather than jumping straight to words like 'takeover' without tracing the causal chain.
Related event: Experts Warn Misuse of AI Safety Terminology Distorts Risk Perception(3 posts)→
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