This paper demonstrates that human-machine hybrids can achieve collective agency, indicating stable interactivity and functional complementarity.
Can human–machine hybrid systems (HMHs) constitute genuine collective agents? This paper defends an affirmative answer. I argue that HMHs achieve collective intentionality without shared consciousness by satisfying the following three functional criteria: goal alignment, functional complementarity, and stable interactivity. Against this functionalist account, the following two objections arise: (1) the cognitive bloat problem, that functional criteria cannot distinguish genuine cognitive integration from mere tool use; and (2) the phenomenological challenge, that AI’s lack of practical reason reduces human–AI interaction to subject–tool relations. I respond by distinguishing constitutive from instrumental functional contributions and showing that collective agency requires stable functional integration, not phenomenological fusion. The result is what I call Functional Hybrid Collective Agents (FHCAs), which are systems exhibiting irreducible collective intentionality through deep human–AI coupling.
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Ruili Wang (2025) studied this question.
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