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The algorithm will see you now

AI isn't replacing radiologists

Trey Causey

In many jobs, tasks are diverse, stakes are high, and demand is elastic. When this is the case, we should expect software to initially lead to more human work, not less. The lesson from a decade of radiology models is neither optimism about increased output nor dread about replacement. Models can lift productivity, but their implementation depends on behavior, institutions and incentives.

An excellent piece from Deena Mousa, lead researcher at OpenPhil, on why radiologists have not been replaced by AI despite the high accuracy and wide availability of radiology-specific models approved for clinical use.

The real takeaway, for me, though is wondering why people still listen to Hinton et al.’s predictions about the social and economic impact of AI? We need a “bitter lesson” for this kind of thing — most jobs aren’t just tasks and the implementation of technology into work is complex, political, and sociological.

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