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Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities

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Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities

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dc.contributor.author Martínez-Plumed, Fernando es_ES
dc.contributor.author Tolan, Songül es_ES
dc.contributor.author Pesole, Annarosa es_ES
dc.contributor.author Hernández-Orallo, José es_ES
dc.contributor.author Fernández-Macías, Enrique es_ES
dc.contributor.author Gómez, Emilia es_ES
dc.date.accessioned 2021-12-13T07:07:32Z
dc.date.available 2021-12-13T07:07:32Z
dc.date.issued 2020-02-08 es_ES
dc.identifier.isbn 978-1-4503-7110-0 es_ES
dc.identifier.uri http://hdl.handle.net/10251/178198
dc.description.abstract [EN] In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples. es_ES
dc.description.sponsorship 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 was also supported by INCIBE (Ayudas para la excelencia de los equipos de investigación avanzada en ciberseguridad), the European Commission (JRC) HUMAINT project (CT-EX2018D335821-101), and UPV (PAID-06-18). J. H-Orallo is also funded by an FLI grant RFP2-152. es_ES
dc.language Inglés es_ES
dc.publisher Association for Computing Machinery (ACM) es_ES
dc.relation.ispartof AIES '20: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Labour market es_ES
dc.subject Tasks es_ES
dc.subject AI intensity es_ES
dc.subject AI impact es_ES
dc.subject AI benchmarks es_ES
dc.subject Simulation es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities es_ES
dc.type Comunicación en congreso es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1145/3375627.3375831 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094403-B-C32/ES/RAZONAMIENTO FORMAL PARA TECNOLOGIAS FACILITADORAS Y EMERGENTES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/FLI//RFP2-152/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC//CT-EX2018D335821-101/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV//PAID-06-18/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV-VIN//SP20180210//A collaboratory for the evaluation, comparison and classification of Artificial Intelligence/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement///PROMETEO%2F2019%2F098//DEEPTRUST/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Martínez-Plumed, F.; Tolan, S.; Pesole, A.; Hernández-Orallo, J.; Fernández-Macías, E.; Gómez, E. (2020). Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities. Association for Computing Machinery (ACM). 94-100. https://doi.org/10.1145/3375627.3375831 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename Third AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES 2020) es_ES
dc.relation.conferencedate Febrero 07-08,2020 es_ES
dc.relation.conferenceplace New York, USA es_ES
dc.relation.publisherversion https://doi.org/10.1145/3375627.3375831 es_ES
dc.description.upvformatpinicio 94 es_ES
dc.description.upvformatpfin 100 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\431995 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Future of Life Institute es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Instituto Nacional de Ciberseguridad es_ES
dc.contributor.funder Universitat Politècnica de València es_ES


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