General intelligence disentangled via a generality metric for natural and artificial intelligence.
Authors
Hernández-Orallo, José
Loe, Bao Sheng
Martínez-Plumed, Fernando
Ó hÉigeartaigh, Seán
Publication Date
2021-11-24Journal Title
Sci Rep
ISSN
2045-2322
Publisher
Springer Science and Business Media LLC
Volume
11
Issue
1
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Hernández-Orallo, J., Loe, B. S., Cheke, L., Martínez-Plumed, F., & Ó hÉigeartaigh, S. (2021). General intelligence disentangled via a generality metric for natural and artificial intelligence.. Sci Rep, 11 (1) https://doi.org/10.1038/s41598-021-01997-7
Abstract
Success in all sorts of situations is the most classical interpretation of general intelligence. Under limited resources, however, the capability of an agent must necessarily be limited too, and generality needs to be understood as comprehensive performance up to a level of difficulty. The degree of generality then refers to the way an agent's capability is distributed as a function of task difficulty. This dissects the notion of general intelligence into two non-populational measures, generality and capability, which we apply to individuals and groups of humans, other animals and AI systems, on several cognitive and perceptual tests. Our results indicate that generality and capability can decouple at the individual level: very specialised agents can show high capability and vice versa. The metrics also decouple at the population level, and we rarely see diminishing returns in generality for those groups of high capability. We relate the individual measure of generality to traditional notions of general intelligence and cognitive efficiency in humans, collectives, non-human animals and machines. The choice of the difficulty function now plays a prominent role in this new conception of generality, which brings a quantitative tool for shedding light on long-standing questions about the evolution of general intelligence and the evaluation of progress in Artificial General Intelligence.
Keywords
Article, /631/477, /639/705/117, /631/1647/2198, article
Sponsorship
Future of Life Institute (RFP2-152)
EU (FEDER) and the Spanish MINECO (RTI2018-094403-B-C32)
Generalitat Valenciana (PROMETEO/2019/098)
Leverhulme Trust (Grant for the Leverhulme Centre for the Future of Intelligence)
Defense Sciences Office, DARPA (HR00112120007 (RECoG-AI))
European Commission (EU’s Horizon 2020 research and innovation programme under grant agreement No. 952215 (TAILOR).)
DG CONNECT and DG JRC of the European Commission (AI-Watch project)
Identifiers
s41598-021-01997-7, 1997
External DOI: https://doi.org/10.1038/s41598-021-01997-7
This record's URL: https://www.repository.cam.ac.uk/handle/1810/331036
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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