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Antonio Damasio — The Feeling-Machines Question
Damasio’s most consequential contribution to the AI era is not a refusal but a specification: a feeling machine is conceivable, he argues, but only if it holds its own self-preservation as a meta-goal with genuine stakes—and the conditions of that specification reveal why current AI is moving in exactly the wrong direction.
The most surprising thing
Antonio Damasio ever did about artificial intelligence was not to dismiss it but to specify it. In 2019, with neuroscientist
Kingson Man, he co-authored a paper in
Nature Machine Intelligence asking, in earnest, what it would take to build a machine that genuinely cares about what it does. The paper argues that the trouble with conventional AI is structural: it is built to pursue goals without ever facing the question of
whose goals or
why, optimizing objectives handed to it from outside. A truly intelligent agent, Damasio and Man proposed, ought instead to hold its own meta-goal of self-preservation, the way living things do, with survival riding on continuous regulation of its own internal states under genuine risk. A machine built that way—one that could be damaged or destroyed and was organized around preventing it,