Consciousness in non-biological substrates: possibilities and limitations of contemporary cognitive research

Consciousness in artificial systems may require spatiotemporal complexity, embodied sensorimotor coupling, and multiscale modeling, but no current AI meets these conditions. The article examines philosophical and scientific preconditions for non-biological consciousness, critiquing the Turing Test and legal definitions of AI. It discusses functionalism, modularity, and connectionism, and reviews large-scale brain projects (Blue Brain, Human Brain Project, BRAIN Initiative) and neuromorphic platforms (SpiNNaker, BrainScaleS). A thought experiment involving a neuromorphic implant (EnTwin) that creates a digital twin raises questions of self-identity and copy multiplicity. The authors propose necessary conditions for artificial consciousness: thresholds of complexity (PCI, FDI), embodied sensorimotor coupling, and multiscale modeling, arguing that empirical testing of consciousness hypotheses is approaching through neuroengineering and computational neurobiology.

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Abstract

The article explores the philosophical and scientific preconditions for the emergence of consciousness in non-biological substrates and identifies conditions under which artificial systems might generate conscious states. It examines the epistemological status of contemporary AI as probabilistic algorithms, critically analyzes the legal definition of AI and the unreliability of the Turing Test as a criterion of consciousness. Key cognitive paradigms—functionalism, modularity (J. Fodor), and connectionism—and their contributions to modeling mental processes are discussed. Drawing on major international projects (the Blue Brain Project, the Human Brain Project/EBRAINS, the BRAIN Initiative), the article demonstrates the limitations of computational brain modeling and the significance of neuromorphic platforms (SpiNNaker/BrainScaleS). Central to the discussion is a thought experiment involving a neuromorphic implant (EnTwin) that creates a digital twin of a person, raising questions of self-identity and the multiplicity of copies. As avenues for operationalization, the article considers indices of brain-dynamics complexity (PCI, FDI), as well as BCI-based advances in speech decoding and vision restoration. In doing so, it connects the philosophy of consciousness with neuroengineering and computational neurobiology, offering an integrated view of the problem. The methodology combines conceptual analysis and an interdisciplinary review: a theoretico-philosophical reconstruction of approaches to consciousness, a comparative analysis of PCI/FDI and IIT, developments in brain–computer interfaces (speech, vision), an analytical examination of large neuroproject infrastructures, and a thought experiment on mind transfer. The scientific novelty lies in integrating philosophical and neuroengineering approaches to operationalize the problem of artificial consciousness. The article proposes a framework of necessary (though not sufficient) conditions for its emergence: (1) achieving thresholds of spatiotemporal complexity measured by PCI/FDI; (2) embodied sensorimotor coupling with the world via neuromorphic embodiment; (3) multiscale modeling that accounts for computational resource constraints. The EnTwin thought experiment highlights the problem of personal identity under multiple replication of copies. Practical cases demonstrate the growing transferability of cognitive functions into non-biological substrates. The conclusion argues for a comprehensive program: the development of neuromorphic platforms grounded in fundamental theories and large-scale brain research projects, together with the systematization of resulting data. This brings closer the empirical testing of hypotheses about consciousness and refines the boundaries of the technological transfer of subjective experience.