Preliminaries to artificial consciousness: a multidimensional heuristic approach
K. Evers, M. Farisco, R. Chatila, B. D. Earp, I. T. Freire, F. Hamker, E. Nemeth, P. F. M. J. Verschure, M. Khamassi
arXiv Preprint Archive March 29, 2024 Peer reviewed via arXiv
Summary
Scientists have developed a groundbreaking framework for understanding artificial consciousness by breaking it down into measurable components. Rather than viewing consciousness as all-or-nothing, this approach maps it across multiple dimensions, bridging neurobiology (q-bio.NC) with artificial intelligence (cs.AI) and robotics (cs.RO). The model uses awareness as a test case, showing how complex mental states could be systematically recreated in artificial systems.
Abstract
The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges. This paper introduces a composite, multilevel, and multidimensional model of consciousness as a heuristic framework to guide research in this field. Consciousness is treated as a complex phenomenon, with distinct constituents and dimensions that can be operationalized for study and for evaluating their replication. We argue that this model provides a balanced approach to artificial consciousness research by avoiding binary thinking (e.g., conscious vs. non-conscious) and offering a structured basis for testable hypotheses. To illustrate its utility, we focus on "awareness" as a case study, demonstrating how specific dimensions of consciousness can be pragmatically analyzed and targeted for potential artificial instantiation. By breaking down the conceptual intricacies of consciousness and aligning them with practical research goals, this paper lays the groundwork for a robust strategy to advance the scientific and technical understanding of artificial consciousness.