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The Feeling Machines Proposal
Kingson Man and Damasio's 2019 Nature Machine Intelligence paper proposing that machines capable of homeostasis-like regulation might also acquire a source of motivation analogous to feeling — and the blueprint for how the evaluative gap could, in principle, be narrowed.
"Homeostasis and soft robotics in the design of feeling machines," published in Nature Machine Intelligence in 2019 by Kingson Man and Antonio Damasio, is the clearest articulation of how the somatic marker framework might apply to artificial systems. The paper proposes that machines implementing processes analogous to homeostasis — continuous self-regulation of internal states whose maintenance is existentially required for continued operation — might thereby acquire the evaluative capacity that current AI systems lack. The proposal is not a claim that current AI feels; it is a blueprint for what building feeling machines would require, and a concession that current systems do not meet the requirements.
In The You On AI Field Guide
The paper emerged from a conversation Kingson Man had with Damasio about the difference between a dog navigating a sidewalk and a Roomba navigating a living room. The dog, with vastly less computational power, moved with adaptive intelligence