Futures of artificial intelligence through technology readiness levels

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 t...

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Detalles Bibliográficos
Autores: Martínez Plumed, Fernando, Gómez Gutiérrez, Emilia, 1975-, Hernández-Orallo, José
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/47064
Acceso en línea:http://hdl.handle.net/10230/47064
http://dx.doi.org/10.1016/j.tele.2020.101525
Access Level:acceso abierto
Palabra clave:AI technologies
Generality
Capabilities
Technology readiness
TRLs
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spelling Futures of artificial intelligence through technology readiness levelsMartínez Plumed, FernandoGómez Gutiérrez, Emilia, 1975-Hernández-Orallo, JoséAI technologiesGeneralityCapabilitiesTechnology readinessTRLsArtificial 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.We are grateful to the members of the panel of experts that provided valuable comments, suggestions and useful critiques for this work (in alphabetical order): Carlos Carrascosa, Blagoj Delipetrev, Paul Desruelle, Salvador España, Cèsar Ferri, Ross Gruetzemacher, Stella Heras, Alfons Juan, Carlos Monserrat, Daniel Nepelsky, Eva Onaindia, Barry O’Sullivan, MaJosé Ramírez-Quintana, Miguel Ámgel Salido and Laura Sebastià. 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. Martínez-Plumed acknowledges funding of the AI-Watch project by DG CONNECT and DG JRC of the European Commission. J. Hernández-Orallo is funded by an Future of Life Institute (FLI) grant RFP2-152.Elsevier202120212021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/47064http://dx.doi.org/10.1016/j.tele.2020.101525reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésTelematics and Informatics. 2021;58:101525info:eu-repo/grantAgreement/ES/2PE/RTI2018-094403-B-C3© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/470642026-06-12T07:21:37Z
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 Gutiérrez, Emilia, 1975-
Hernández-Orallo, José
author Martínez Plumed, Fernando
author_facet Martínez Plumed, Fernando
Gómez Gutiérrez, Emilia, 1975-
Hernández-Orallo, José
author_role author
author2 Gómez Gutiérrez, Emilia, 1975-
Hernández-Orallo, José
author2_role author
author
dc.subject.none.fl_str_mv AI technologies
Generality
Capabilities
Technology readiness
TRLs
topic AI technologies
Generality
Capabilities
Technology readiness
TRLs
description 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
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/47064
http://dx.doi.org/10.1016/j.tele.2020.101525
url http://hdl.handle.net/10230/47064
http://dx.doi.org/10.1016/j.tele.2020.101525
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Telematics and Informatics. 2021;58:101525
info:eu-repo/grantAgreement/ES/2PE/RTI2018-094403-B-C3
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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