Prediction machines
the simple economics of artificial intelligence /Autor(es):
Agrawal, Ajay | Gans, Joshua | Goldfarb, Avi
Editor: Boston, Massachusetts : Harvard Business Review Press, [2018]Fecha de copyright: 2018Descripción: X, 250 p. : gráf. ; 25 cmTipo de contenido: texto (visual)Tipo de medio: sin mediación
Tipo de soporte: volumen ISBN: 9781633695672Tema(s): Tecnologías habilitadoras digitales | Inteligencia artificialClasificación CDD: 658/.0563 Recursos en línea: Haga clic para acceso en línea
Tipo de ítem | Ubicación actual | Colección | Signatura | Estado | Notas | Fecha de vencimiento | Código de barras |
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CDO
El Centro de Documentación del Observatorio Nacional de las Telecomunicaciones y de la Sociedad de la Información (CDO) os da la bienvenida al catálogo bibliográfico sobre recursos digitales en las materias de Tecnologías de la Información y telecomunicaciones, Servicios públicos digitales, Administración Electrónica y Economía digital.
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Colección impresa | 579 | Prestado (Solo red.es) | papel | 1000020175269 |
MSC 68Txx ; 90B50 ; 60G25
Incluye referencias bibliográficas (p. 225-238) e índice
Cheap changes everything -- The magic of prediction -- Why it's called intelligence -- Data is the new oil -- The new division of labor -- Unpacking decisions -- The value of judgment -- Taming complexity -- What machines can learn -- Fully automated decision-making -- Deconstructing workflows -- Decomposing decisions -- Job redesign -- AI in the C-suite -- When AI transforms your business -- Managing AI risk -- Beyond business
The idea of artificial intelligence--job-killing robots, self-driving cars, and self-managing organizations--captures the imagination, evoking a combination of wonder and dread for those of us who will have to deal with the consequences. But what if it's not quite so complicated? The real job of artificial intelligence, argue these three eminent economists, is to lower the cost of prediction. And once you start talking about costs, you can use some well-established economics to cut through the hype. The constant challenge for all managers is to make decisions under uncertainty. And AI contributes by making knowing what's coming in the future cheaper and more certain. But decision making has another component: judgment, which is firmly in the realm of humans, not machines. Making prediction cheaper means that we can make more predictions more accurately and assess them with our better (human) judgment. Once managers can separate tasks into components of prediction and judgment, we can begin to understand how to optimize the interface between humans and machines. More than just an account of AI's powerful capabilities, Prediction Machines shows managers how they can most effectively leverage AI, disrupting business as usual only where required, and provides businesses with a toolkit to navigate the coming wave of challenges and opportunities.-- Provided by publisher
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