02657nas a22003978i 4500 00006715 ES-MaONT 20220207165117.0 cr || |||||m|n 210922s2021 fr ad o i|0| 0 eng d doi 10.1787/2e278150-en ES-MaONT 5182 Samek, Lea The human capital behind AI : jobs and skills demand from online job postings / Lea Samek, Mariagrazia Squicciarini and Emile Cammeraat Paris : OECD Publishing, September 2021 99 p. : il., gráf. ; 1 documento PDF texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier OECD Science, Technology and Industry Policy Papers ; September 2021, No. 120 Bibliografía: p. 76-79 Building on recent OECD work, this paper analyses the skills sets (“skills bundles”) demanded in artificial intelligence (AI)-related online job postings. The analysis uses Burning Glass Technologies’ data for the United States and the United Kingdom and finds that skills related to the open source programming software Python and to machine learning represent “must-haves” for working with AI. Employers additionally value specialised skills related to robotics, AI development and applying AI. A comparison of the periods 2013-15 and 2017-19 shows that the latter two have become more interrelated over time, with “neural network” skills connecting both groups. Network analysis relating AI skills to general skills highlights the growing role of socio-emotional skills; and of skill bundles related to programming, management of big data and data analysis. Key results hold for both countries and time periods, though differences emerge across occupations and industries. The use of this work, whether digital or print, is governed by the Terms and Conditions to be found at http://www.oecd.org/termsandconditions ; OECD 4348 Inteligencia Artificial AI habilidades teletrabajo ofertas de trabajo en línea trabajo remoto 4922 Squicciarini, Mariagrazia 5183 Cammeraat, Emile Organización de Cooperación y Desarrollo Económico 2843 OECD Science, Technology and Industry Policy Papers 2724 https://www.oecd-ilibrary.org/docserver/2e278150-en.pdf?expires=1632322051&id=id&accname=guest&checksum=6F147E7302D582C8D2412BE41083D35B Acceso al documento 0 pdf INF udc 6715 6715 0 0 0 20201214 3 1 7662 01 01 online 2021-09-20 0 2020-12-14 1000020176908 2021-09-22 00:00:00 2021-09-22 INF pdf