02565nam a22003857a 4500 5120 5120 00005120 ES-MaONT 20240116164423.0 190520s2019 xxud|||fr|||| 00| 0 eng d ES-MaONT 2905 Bughin, Jacques Tech for Good : Smoothing disruption, improving well-being : Discussion paper May 2019 / authors Jacques Bughin, Eric Hazan, Tera Allas, Klemens Hjartar, James Manyika, Pal Erik Sjatil, and Irina Shigina [Nueva York] : McKinsey Global Institute, may 2019 76 p. : tabl., gráf. ; 1 documento PDF texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier The development and adoption of advanced technologies including smart automation and artificial intelligence has the potential not only to raise productivity and GDP growth but also to improve well-being more broadly, including through healthier life and longevity and more leisure. Alongside such benefits, these technologies also have the potential to reduce disruption and the potentially destabilizing effects on society arising from their adoption. Examines the factors that can help society achieve such benefits and makes a first attempt to calculate the impact of technology adoption on welfare growth beyond GDP. Our modeling suggests that good outcomes for the economy overall and for individual well-being come about when technology adoption is focused on innovation-led growth rather than purely on labor reduction and cost savings through automation. This needs to be accompanied by proactive transition management that increases labor market fluidity and equips workers with new skills. Tecnologías habilitadoras digitales 18 AI impacto inteligencia artificial Tecnologías emergentes technology 2906 Hazan, Eric 2907 Allas, Tera 2908 Hjartar, Klemens Manyika, James 2909 2910 Sjatil, Pal Erik 2911 Shigina, Irina McKinsey Global Institute‏ 1298 https://www.mckinsey.com/~/media/mckinsey/industries/public%20and%20social%20sector/our%20insights/future%20of%20organizations/tech%20for%20good%20using%20technology%20to%20smooth%20disruption%20and%20improve%20well%20being/tech-for-good-mgi-discussion-paper.pdf 0 Acceso al documento udc INF 0 0 0 0 1 5867 01 01 online 2019-05-20 0 1000020175400 2019-05-20 00:00:00 2019-05-20 pdf INF