Preliminaries to artificial consciousness: a multidimensional heuristic approach
This work addresses the foundational problem of defining and operationalizing consciousness for researchers in AI and cognitive science, though it is incremental as it builds on existing theoretical frameworks.
The paper tackles the challenge of conceptual clarity in artificial consciousness research by introducing a multidimensional heuristic model to guide empirical study, focusing on awareness as a case study to demonstrate practical analysis.
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.