Consciousness is a natural phenomenon, familiar to every person. At the same time, it cannot be described in singular terms. The rise of Artificial Intelligence in recent years has made the topic of Artificial Consciousness highly debated. The paper discusses the main general theories of consciousness and their relationship with proposed Artificial Consciousness solutions. There are a number of well-established models accepted in the area of research: Higher Order Thoughts/Higher Order Perception, Global Network Workspace, Integrated Information Theory, reflexive, representative, functional, connective, Multiple Draft Model, Neural Correlate of Consciousness, quantum consciousness, to name just a few. Some theories overlap, which allows for speaking about more advanced, complex models. The disagreement in theories leads to different views on animal consciousness and human conscious states. As a result, there are also variations in the opinions about Artificial Consciousness based on the discrepancy between qualia and the nature of AI. The hard problem of consciousness, an epitome of qualia, is often seen as an insurmountable barrier or, at least, an “explanatory gap”. Nevertheless, AI constructs allow imitations of some models in silico, which are presented by several authors as full-fledged Artificial Consciousness or as strong AI. This itself does not make the translation of consciousness into the AI space easier but allows decent progress in the domain. As argued in this paper, there will be no universal solution to the Artificial Consciousness problem, and the answer depends on the type of consciousness model. A more pragmatic view suggests the instrumental interaction between humans and AI in the environment of the Fifth Industrial Revolution, limiting expectations of strong AI outcomes to cognition but not consciousness in wide terms.
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