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 via arXiv
Summary
AI-generated from the abstractA composite, multilevel, and multidimensional model of consciousness is proposed as a heuristic framework to guide artificial consciousness research. The model treats consciousness as a complex phenomenon with distinct constituents and dimensions that can be operationalized for study and replication. It avoids binary thinking (conscious vs. non-conscious) and offers a structured basis for testable hypotheses. Using 'awareness' as a case study, the paper demonstrates how specific dimensions can be pragmatically analyzed and targeted for artificial instantiation. This approach aims to advance the scientific and technical understanding of artificial consciousness by breaking down conceptual intricacies and aligning them with practical research goals.
Study at a glance
| Characteristics | Theoretical or philosophical paper Case report Peer reviewed |
|---|---|
| Keywords | Cs.ro Artificial-consciousness Machine-awareness cs.ai Neurobiology q-bio.nc Cognitive-frameworks |
| Key finding | A composite, multilevel, and multidimensional model of consciousness provides a heuristic framework that avoids binary thinking and offers a structured basis for testable hypotheses in artificial consciousness research. |
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.