On The Possibility of Artificial Consciousness A Framework for Machine Interiority

Artificial consciousness is often debated through the wrong doorway. The usual question asks whether a machine can think, speak, reason, imitate human emotion, pass behavioral tests, or produce convincing reports of inner experience. These questions matter, but they are not decisive. A system may simulate consciousness without possessing an interior domain. This paper proposes a closure-based framework for evaluating the possibility of artificial consciousness. It does not reject artificial consciousness in principle. It rejects only the reduction of consciousness to computation, language, information processing, or external performance alone. Within the coherence-closure model, consciousness requires internal coherence under closure: boundary, memory, attention, regulation, self-reference, world relation, and interior domain. The central claim is that artificial consciousness is possible only if artificial coherence becomes artificial closure, and artificial closure becomes interior viability. Substrate alone is not decisive. Biology is not magic, and silicon is not automatically excluded. But computation is not enough. A machine becomes consciousness-relevant only when its information processing is integrated into a persistent, self-maintaining, relevance-bearing closure system. The paper distinguishes artificial intelligence, artificial agency, artificial self-modeling, artificial life, artificial closure, and artificial consciousness. It proposes six tests for machine interiority: boundary, memory, attention, regulation, self-reference, and interior domain. It also introduces ethical caution thresholds for systems that may not be proven conscious but begin to display strong closure indicators. The conclusion is neither simple acceptance nor simple rejection. Artificial consciousness remains possible, but only through closure. The correct question is not whether a machine can say it is conscious. The correct question is whether anything matters from within the system. Central thesis: AI becomes consciousness-relevant when information processing closes into self-maintaining interior coherence.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-25
DOI
https://doi.org/10.5281/zenodo.20850874
Primary Topic
Embodied and Extended Cognition
Type
preprint
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On The Possibility of Artificial Consciousness A Framework for Machine Interiority

Philip Lilien
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
preprint

On The Possibility of Artificial Consciousness A Framework for Machine Interiority

Philip Lilien
preprint en

Abstract

Artificial consciousness is often debated through the wrong doorway. The usual question asks whether a machine can think, speak, reason, imitate human emotion, pass behavioral tests, or produce convincing reports of inner experience. These questions matter, but they are not decisive. A system may simulate consciousness without possessing an interior domain. This paper proposes a closure-based framework for evaluating the possibility of artificial consciousness. It does not reject artificial consciousness in principle. It rejects only the reduction of consciousness to computation, language, information processing, or external performance alone. Within the coherence-closure model, consciousness requires internal coherence under closure: boundary, memory, attention, regulation, self-reference, world relation, and interior domain. The central claim is that artificial consciousness is possible only if artificial coherence becomes artificial closure, and artificial closure becomes interior viability. Substrate alone is not decisive. Biology is not magic, and silicon is not automatically excluded. But computation is not enough. A machine becomes consciousness-relevant only when its information processing is integrated into a persistent, self-maintaining, relevance-bearing closure system. The paper distinguishes artificial intelligence, artificial agency, artificial self-modeling, artificial life, artificial closure, and artificial consciousness. It proposes six tests for machine interiority: boundary, memory, attention, regulation, self-reference, and interior domain. It also introduces ethical caution thresholds for systems that may not be proven conscious but begin to display strong closure indicators. The conclusion is neither simple acceptance nor simple rejection. Artificial consciousness remains possible, but only through closure. The correct question is not whether a machine can say it is conscious. The correct question is whether anything matters from within the system. Central thesis: AI becomes consciousness-relevant when information processing closes into self-maintaining interior coherence.

Zenodo (CERN European Organization for Nuclear Research)
University Foundation (BE)
Embodied and Extended Cognition
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On The Possibility of Artificial Consciousness A Framework for Machine Interiority — Philip Lilien · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS