Futures of artificial intelligence through technology readiness levels

[EN] Artificial Intelligence (AI) offers the potential to transform our lives in radical ways. However, the main unanswered questions about this foreseen transformation are its depth, breadth and timelines. To answer them, not only do we lack the tools to determine what achievements will be attained...

Descripción completa

Detalles Bibliográficos
Autores: Martínez Plumed, Fernando, Gómez, Emilia, Hernández-Orallo, José
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/189359
Acceso en línea:https://riunet.upv.es/handle/10251/189359
Access Level:acceso abierto
Palabra clave:AI technologies
Generality
Capabilities
Technology readiness
TRLs
id ES_221745676695c1e4dc56a005bf66b96c
oai_identifier_str oai:riunet.upv.es:10251/189359
network_acronym_str ES
network_name_str España
repository_id_str
spelling Futures of artificial intelligence through technology readiness levelsMartínez Plumed, FernandoGómez, EmiliaHernández-Orallo, JoséAI technologiesGeneralityCapabilitiesTechnology readinessTRLs[EN] Artificial Intelligence (AI) offers the potential to transform our lives in radical ways. However, the main unanswered questions about this foreseen transformation are its depth, breadth and timelines. To answer them, not only do we lack the tools to determine what achievements will be attained in the near future, but we even ignore what various technologies in present-day AI are capable of. Many so-called breakthroughs in AI are associated with highly-cited research papers or good performance in some particular benchmarks. However, research breakthroughs do not directly translate into a technology that is ready to use in real-world environments. In this paper, we present a novel exemplar-based methodology to categorise and assess several AI technologies, by mapping them onto Technology Readiness Levels (TRL) (representing their depth in maturity and availability). We first interpret the nine TRLs in the context of AI, and identify several categories in AI to which they can be assigned. We then introduce a generality dimension, which represents increasing layers of breadth of the technology. These two dimensions lead to the new readiness-vs-generality charts, which show that higher TRLs are achievable for low-generality technologies, focusing on narrow or specific abilities, while high TRLs are still out of reach for more general capabilities. We include numerous examples of AI technologies in a variety of fields, and show their readiness-vs-generality charts, serving as exemplars. Finally, we show how the timelines of several AI technology exemplars at different generality layers can help forecast some short-term and mid-term trends for AI.This material is based upon work supported by the EU (FEDER), and the Spanish MINECO under grant RTI2018-094403-B-C3, the Generalitat Valenciana PROMETEO/2019/098. F. Martinez-Plumed acknowledges funding of the AI-Watch project by DG CONNECT and DG JRC of the European Commission. J. Hernandez-Orallo is funded by an Future of Life Institute (FLI) grant RFP2-152.ElsevierDepartamento de Sistemas Informáticos y ComputaciónEscuela Técnica Superior de Ingeniería InformáticaInstituto Universitario Valenciano de Investigación en Inteligencia ArtificialEuropean CommissionGENERALITAT VALENCIANAFuture of Life InstituteAGENCIA ESTATAL DE INVESTIGACIONEuropean Regional Development FundRepositorio Institucional de la Universitat Politècnica de València Riunet20212021-05-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/189359reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-094403-B-C32 RAZONAMIENTO FORMAL PARA TECNOLOGIAS FACILITADORAS Y EMERGENTESGENERALITAT VALENCIANA GENERALITAT VALENCIANA PROMETEO%2F2019%2F098 DEEPTRUSTFuture of Life Institute FLI RFP2-152open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1893592025-07-13T07:49:11Z
dc.title.none.fl_str_mv Futures of artificial intelligence through technology readiness levels
title Futures of artificial intelligence through technology readiness levels
spellingShingle Futures of artificial intelligence through technology readiness levels
Martínez Plumed, Fernando
AI technologies
Generality
Capabilities
Technology readiness
TRLs
title_short Futures of artificial intelligence through technology readiness levels
title_full Futures of artificial intelligence through technology readiness levels
title_fullStr Futures of artificial intelligence through technology readiness levels
title_full_unstemmed Futures of artificial intelligence through technology readiness levels
title_sort Futures of artificial intelligence through technology readiness levels
dc.creator.none.fl_str_mv Martínez Plumed, Fernando
Gómez, Emilia
Hernández-Orallo, José
author Martínez Plumed, Fernando
author_facet Martínez Plumed, Fernando
Gómez, Emilia
Hernández-Orallo, José
author_role author
author2 Gómez, Emilia
Hernández-Orallo, José
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Sistemas Informáticos y Computación
Escuela Técnica Superior de Ingeniería Informática
Instituto Universitario Valenciano de Investigación en Inteligencia Artificial
European Commission
GENERALITAT VALENCIANA
Future of Life Institute
AGENCIA ESTATAL DE INVESTIGACION
European Regional Development Fund
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv AI technologies
Generality
Capabilities
Technology readiness
TRLs
topic AI technologies
Generality
Capabilities
Technology readiness
TRLs
description [EN] Artificial Intelligence (AI) offers the potential to transform our lives in radical ways. However, the main unanswered questions about this foreseen transformation are its depth, breadth and timelines. To answer them, not only do we lack the tools to determine what achievements will be attained in the near future, but we even ignore what various technologies in present-day AI are capable of. Many so-called breakthroughs in AI are associated with highly-cited research papers or good performance in some particular benchmarks. However, research breakthroughs do not directly translate into a technology that is ready to use in real-world environments. In this paper, we present a novel exemplar-based methodology to categorise and assess several AI technologies, by mapping them onto Technology Readiness Levels (TRL) (representing their depth in maturity and availability). We first interpret the nine TRLs in the context of AI, and identify several categories in AI to which they can be assigned. We then introduce a generality dimension, which represents increasing layers of breadth of the technology. These two dimensions lead to the new readiness-vs-generality charts, which show that higher TRLs are achievable for low-generality technologies, focusing on narrow or specific abilities, while high TRLs are still out of reach for more general capabilities. We include numerous examples of AI technologies in a variety of fields, and show their readiness-vs-generality charts, serving as exemplars. Finally, we show how the timelines of several AI technology exemplars at different generality layers can help forecast some short-term and mid-term trends for AI.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-05-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/189359
url https://riunet.upv.es/handle/10251/189359
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-094403-B-C32 RAZONAMIENTO FORMAL PARA TECNOLOGIAS FACILITADORAS Y EMERGENTES
GENERALITAT VALENCIANA GENERALITAT VALENCIANA PROMETEO%2F2019%2F098 DEEPTRUST
Future of Life Institute FLI RFP2-152
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1844165427602653184
score 15,638193

Similares en LA Referencia