Article ; Online: Major evolutionary transitions in individuality between humans and AI.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
2023 Volume 378, Issue 1872, Page(s) 20210408
Abstract: That humans might undergo future evolutionary transitions in individuality (ETIs) seems fanciful. However, drawing upon recent thinking concerning the origins of properties that underpin ETIs, I argue that certain ETIs are imminently realizable. Central ... ...
Abstract | That humans might undergo future evolutionary transitions in individuality (ETIs) seems fanciful. However, drawing upon recent thinking concerning the origins of properties that underpin ETIs, I argue that certain ETIs are imminently realizable. Central to my argument is recognition that heritable variance in fitness at higher levels of organization can be externally imposed (scaffolded) by specific ecological structures and cultural practices. While ETIs to eusociality seem highly improbable, ETIs involving symbioses between humans and artificial intelligence (AI) can be readily envisaged. A necessary requirement is that fitness-affecting interactions between humans and AI devices are inherited by offspring. The Mendelian nature of human reproduction ensures that offspring resemble parents. Reproduction of AI devices requires nothing more than transference of algorithms from parental AI devices to devices that are assigned to offspring. This simple copying, combined with societal structures that require humans to carry AI devices, ensures heritable variance in fitness at the level of both interacting partners. Selection at the collective level will drive alignment of replicative fates and increase co-dependency, thus alleviating need for continual imposition of externally imposed scaffolds. I conclude by drawing attention to the immediacy of such transitions and express concern over possibilities for malevolent manipulation. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'. |
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MeSH term(s) | Humans ; Artificial Intelligence ; Biological Evolution ; Reproduction ; Algorithms ; Symbiosis |
Language | English |
Publishing date | 2023-01-23 |
Publishing country | England |
Document type | Journal Article ; Review |
ZDB-ID | 208382-6 |
ISSN | 1471-2970 ; 0080-4622 ; 0264-3839 ; 0962-8436 |
ISSN (online) | 1471-2970 |
ISSN | 0080-4622 ; 0264-3839 ; 0962-8436 |
DOI | 10.1098/rstb.2021.0408 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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