Axioms, properties and criteria: roles for synthesis in the science of consciousness.
Robert W. Clowes, Anil K. Seth
Artificial intelligence in medicine October 1, 2008 DOI: 10.1016/j.artmed.2008.07.009 (opens in new tab) via PubMed
Summary
AI-generated from the abstractSynthetic methods in science can aim to either instantiate a target phenomenon (strong approach) or simulate key mechanisms underlying it (weak approach). The strong approach assumes a mature theory, while the weak approach helps develop such theories. The authors argue that artificial consciousness is best pursued as a weak means of theory development in consciousness science, not as a strong axiom-driven project to build a conscious artifact. Like other sciences of the artificial, artificial consciousness can elaborate possibilities and limitations of candidate mechanisms, transform properties into mechanism-based criteria, and potentially unify distinct properties via new mechanism-based concepts. The arguments are illustrated by discussing both axiom-driven and neurobiologically grounded approaches to artificial consciousness.
Study at a glance
| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key finding | Argues that artificial consciousness is best pursued as a weak means of theory development in consciousness science, not as a strong axiom-driven project to build a conscious artefact. |
Abstract
Synthetic methods in science can aim at either instantiating a target phenomenon or simulating key mechanisms underlying that phenomenon; 'strong' and 'weak' approaches, respectively. While the former assumes a mature theory, the latter find its value in helping specify such theories. Here, we argue that artificial consciousness is best pursued as a (weak) means of theory development in consciousness science, and not as a (strong) axiom-driven project to build a conscious artefact. As with the other sciences of the artificial (intelligence, life), artificial consciousness can contribute by elaborating the possibilities and limitations of candidate mechanisms, transforming properties into mechanism-based criteria, and as a result potentially unifying apparently distinct properties via new mechanism-based concepts. We illustrate our arguments by discussing both axiom-driven and neurobiologically grounded approaches to artificial consciousness.