2026-04-13T07:55:16Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/470642025-12-18T01:19:57Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Martínez Plumed, Fernando author Gómez Gutiérrez, Emilia, 1975- author Hernández-Orallo, José author 2021-04-09T06:16:30Z 2021-04-09T06:16:30Z 2021 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. 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. AI technologies Generality Capabilities Technology readiness TRLs Futures of artificial intelligence through technology readiness levels