| Literature DB >> 33414712 |
Patrick Krauss1,2, Andreas Maier3.
Abstract
The question of whether artificial beings or machines could become self-aware or conscious has been a philosophical question for centuries. The main problem is that self-awareness cannot be observed from an outside perspective and the distinction of being really self-aware or merely a clever imitation cannot be answered without access to knowledge about the mechanism's inner workings. We investigate common machine learning approaches with respect to their potential ability to become self-aware. We realize that many important algorithmic steps toward machines with a core consciousness have already been taken.Entities:
Keywords: artificial intelligence; correlates of consciousness; deep learning; global workspace; machine consciousness; machine learning; philosophy of mind; theories of consciousness
Year: 2020 PMID: 33414712 PMCID: PMC7782472 DOI: 10.3389/fncom.2020.556544
Source DB: PubMed Journal: Front Comput Neurosci ISSN: 1662-5188 Impact factor: 2.380