{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:02Z","timestamp":1747216142144,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643685489"}],"license":[{"start":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T00:00:00Z","timestamp":1729036800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,16]]},"abstract":"<jats:p>The concept of General-Purpose AI (GPAI) has recently been permeating research papers, policy reports and legal regulations, as a way of referring to current and future models with high levels of capability and generality. Yet precisely characterising GPAI models remains elusive. Current definitions often describe GPAI models as those that \u2018competently perform a wide range of distinct tasks\u2019. To properly characterise GPAI we need well-grounded definitions of capability and generality. In this paper, I will briefly introduce \u2013or revisit\u2013 the concept of capability, going well beyond aggregate performance on benchmarks, and discuss practical procedures to evaluate the capability profile of AI systems, and derive generality metrics from them.<\/jats:p>","DOI":"10.3233\/faia240459","type":"book-chapter","created":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T12:34:44Z","timestamp":1729168484000},"source":"Crossref","is-referenced-by-count":0,"title":["Caveats and Solutions for Characterising General-Purpose AI"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9746-7632","authenticated-orcid":false,"given":"Jose","family":"Hernandez-Orallo","sequence":"first","affiliation":[{"name":"VRAIN, Universitat Politecnica de Valencia"},{"name":"VALGRAI"},{"name":"Leverhulme Centre for the Future of Intelligence"},{"name":"Centre for the Study of Existential Risk"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2024"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA240459","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T12:34:46Z","timestamp":1729168486000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA240459"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,16]]},"ISBN":["9781643685489"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia240459","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"type":"print","value":"0922-6389"},{"type":"electronic","value":"1879-8314"}],"subject":[],"published":{"date-parts":[[2024,10,16]]}}}