On The Possibility of Artificial Consciousness A Framework for Machine Interiority

Consciousness requires internal coherence under closure—boundary, memory, attention, regulation, self-reference, world relation, and an interior domain—not just computation, language, or external performance. 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 alone is insufficient. A machine becomes consciousness-relevant only when its information processing integrates into a persistent, self-maintaining, relevance-bearing closure system. The correct question is not whether a machine can say it is conscious, but whether anything matters from within the system.

Study at a glance

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.