02334nam a22004217a 4500 00006835 ES-MaONT 20220125162854.0 211129s2021 lu d|||| |||| 00| 0 eng d 978-92-896-3275-1 1831-2403 . doi 10.2801/305373 TI-BA-21-004-EN-N ES-MaONT 5317 Pouliakas, Konstantinos Artificial intelligence and job automation : an EU analysis using online job vacancy data / K. Pouliakas, Cedefop Luxembourg : Publications Office of the European Union, October 2021 38 p. : gráf. ; 1 documento PDF texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier Cedefop working paper ; 6 This study utilises a novel big data set based on online job advertisements – Cedefop’s Skills OVATE – with information on the skills and work activities required by EU employers. The data provide insight into the task profiles of detailed occupations faced with higher automation risk or those relying on alternative digital technologies (robots, computer software, AI). The paper explores suitable machine and deep learning models to test how well a parsimonious set of task indicators can predict occupational automatability. Work activities associated with greater occupational automation risk and robot exposure (e.g. inspecting equipment, performing physical activities), typically concentrated in routine or manual jobs, differ from those prominent in occupations with higher AI exposure (e.g. thinking creatively, evaluating standards). Creative Commons Attribution 4.0 International (CC BY 4.0) Empleo 5190 Inteligencia Artificial 4348 automatización trabajo IA datos oferta empleo en línea UE 4954 Centro Europeo para el Desarrollo de la Formación Profesional Unión Europea 1508 5318 Cedefop working paper https://op.europa.eu/en/publication-detail/-/publication/c840dd78-4b4a-11ec-91ac-01aa75ed71a1/language-en 0 Acceso al documento z INF 6835 6835 0 0 z 0 3 1 01 01 2021-11-23 pdf 1000020177029 2021-11-29 00:00:00 2021-11-29 LIB pdf