02600nam a22004338c 4500 00006513 ES-MaONT 20211006062651.0 a o d i cr || |||m|n|| 210507s2021 sz d o i|0| 0 eng d 978-92-61-32771-2 (Paper version) 978-92-61-32781-1 (Electronic version) 978-92-61-32791-0 (EPUB version) 978-92-61-32801-6 (Mobi version) ES-MaONT 4995 Stankovic, Mirjana Emerging technology trends : Artificial intelligence and big data for development 4.0 / authors, Dr Mirjana Stankovic, Aminata Amadou Garba, Nikola Neftenov ; International Telecommunication Union Development Sector Geneva : ITU Publications, 2021 108 p. : gráf. ; 1 documento PDF texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier Bibliografía: p. 99-105 Despite its great promise, the AI and data revolution is yet to yield tangible dividends for most developing countries. More often than not, these countries do not have all the prerequisites in place in order to collect sufficient data to utilize AI algorithms for development. Furthermore, existing data too often remain unused because they are released too late or not at all, are not available in digital format or lack the level of granularity needed for decision-making and local innovation. This report has been designed to help overcome these barriers and embrace the huge development opportunities offered by AI and big data deployment. It is intended as a guide for policy-makers and other stakeholders in crafting a national AI and data strategy for development. Some rights reserved. This work is licensed to the public through a Creative Commons Attribution-NonCommercial-Share Alike 3.0 IGO license (CC BY-NC-SA 3.0 IGO) ; ITU Tecnologías habilitadoras digitales 18 Inteligencia Artificial 4348 Big data cibersecurity digital transformation policy and regulation 4996 Garba, Aminata Amadou 4997 Neftenov, Nikola Unión Internacional de Telecomunicaciones 1433 https://www.itu.int/en/myitu/Publications/2021/05/04/12/23/Emerging-technology-trends-Artificial-intelligence-big-data-for-development-4%20/ Acceso al documento 0 pdf INF udc 6513 6513 0 0 0 3 1 7457 01 01 online 2021-05-07 0 1000020176706 2021-05-07 00:00:00 2021-05-07 INF pdf