AI alignment and the language of risk
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AI alignment and the language of risk
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The terminology surrounding artificial intelligence often masks genuine hazards by framing critical safety threats as mere technical adjustments or misalignment issues. When abstract industry jargon replaces explicit descriptions of potential harm, decision-makers struggle to accurately assess the dangers of deploying autonomous systems. True accountability requires moving beyond reassuring labels like human in the loop to openly acknowledge specific risks, such as service disruption or the loss of operational control. Established safety frameworks from regulated fields like aviation and nuclear power demonstrate that robust protections must remain effective even when underlying technological assumptions fail. Ultimately, organizations must abandon vague euphemisms in favour of precise language that clearly defines what an algorithm can do, what damage it might trigger, and whether people retain the actual authority to intervene.
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