Computational models of consciousness, known as artificial consciousness, have been developed over the last two decades with two main goals: to better understand human and animal consciousness and to create machines with conscious awareness. This review categorizes models into five types based on their central focus: global workspace, information integration, internal self-model, higher-level representations, or attention mechanisms. The review concludes that computational modeling is now an accepted scientific method for studying consciousness, and existing models have successfully simulated many neurobiological and cognitive correlates of conscious processing. However, no current approach has convincingly demonstrated phenomenal machine consciousness or provided clear evidence that it will eventually be possible.
Creating a conscious machine remains controversial and challenging. This work describes a humanoid cognitive robot that learns tasks by imitating human demonstrations, using cause-effect reasoning to infer a demonstrator's intentions rather than merely copying actions. Its cognitive components center on top-down control of working memory, which retains explanatory interpretations constructed during learning. Ongoing work aims to convert this imitation learning system into purely neurocomputational form, including low-level neuromotor components, working memory, and causal reasoning. Based on initial results, top-down cognitive control of working memory—especially its gating mechanisms—is argued to be an important potential computational correlate of consciousness in humanoid robots. Developing such neurocognitive control systems provides a credible route to ultimately developing a phenomenally conscious machine.
Conscious experience may arise from electromagnetic waves propagating through time, not just space. Standard Maxwell's equations are likely incomplete; extending them with complex-valued field components implies that electromagnetic fields extend temporally. Applied to the brain's self-generated fields, this hypothesis accounts for the extended duration of conscious moments and the subjective flow of time—phenomena unexplained by current physics. It also reframes episodic memory: recalling past experiences becomes partly a perceptual re-experiencing process rather than pure retrieval from storage. Complex-valued fields substantially increase the explanatory power of electromagnetic field theories of consciousness.